Atomic spectrometry update—X-ray fluorescence spectrometry
Margaret
West†
*a,
Andrew T.
Ellis
b,
Philip J.
Potts
d,
Christina
Streli
c,
Christine
Vanhoof
e,
Dariusz
Wegrzynek
f and
Peter
Wobrauschek
c
aWest X-ray Solutions, 405 Whirlowdale Road, Sheffield S11 9NF, UK. E-mail: margaretwest@blueyonder.co.uk
bOxford Instruments X-ray Technology, 360 El Pueblo Road, Scotts Valley, CA 95066, USA
cVienna University of Technology, Atominstitut, Stadionallee 2, 1020, Vienna, Austria
dFaculty of Science, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK
eFlemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
fAGH University of Science and Technology, Faculty of Physics and Applied, Computer Science, Al. Mickiewicza 30, 30-059 Krakow, Poland
First published on 7th August 2012
Abstract
This review demonstrates advances in XRF instrumentation, techniques and data processing algorithms published during the last year. Pixellated detectors and EDXRF imaging/mapping using a variety of materials and readout technologies have set a trend that will undoubtedly continue due to improved sensor array fabrication and readout devices that are now more widely available. Instrumental development took place at synchrotron beamlines with reports that described the measurement and data processing methodologies for use with combinations of μ-analytical techniques (μ-SRXRF, μ-XANES and μ-PIXE) that offer chemical imaging to researchers interested in spatial distribution and speciation of elements within plants and cell tissue for environmental studies and medical diagnostics. Archaeological and cultural heritage applications similarly benefit with insight of the original fabrication or subsequent alteration of artefacts. Although recent developments in hand-held instrumentation have substantially improved the capabilities of this form of XRF, advances in instrumentation continue to be reported. TXRF is a growing analytical technique with systematic studies in sample preparation, sample shape and influence of absorption on both the incident and fluorescent radiation bringing benefits for the analysis of environmental samples. A new method of elemental depth profiling has been developed and the corrosion process has been characterised with an unprecedented level of detail. A large proportion of geological studies focused on evidence for climate and environmental change over geological time periods.
1 Introduction and reviews
This update refers to papers published approximately between April 2011 and March 2012 and continues the series of Atomic Spectroscopy Updates in X-ray Fluorescence Spectrometry1 that should be read in conjunction with other related reviews in the series.2–6 The shrinking of the X-ray beams in synchrotron beamlines has reached the sub-micrometre and nano-beam level with imaging of elements particularly of interest in the life and environmental sciences. Cotte and Susini7 reviewed the use of synchrotron sources for the analysis of artworks and cultural heritage artefacts where new insights have been reported on chemical reactions mastered during the original fabrication or subsequent alteration of objects. Fittschen and Falkenberg8 highlighted the performance of confocal μ-XRF for the provision of 3D imaging for environmental applications. Molloy and Sieber9 assessed micro-scale heterogeneity in batches of reference materials whilst Palmer10 stimulated interest from the academic community for the incorporation of handheld XRF into undergraduate chemistry. Other reviews included Kuczumow and Wolski11 on new applications for WDXRF, Sudarshan et al.12 on EDXRF and Grindlay et al.13 offered a critical evaluation of atomic spectrometric methods for the analysis of wine. Revenko14 reviewed developments of XRF analysis in Russia between 1991 and 2010 whereas Kawai and Hayakawa15 edited the annual advances in X-ray chemical analysis from Japan. The writing team welcome feedback on this update via e-mail contact with the lead author.2 Instrumentation
2.1 General instrumentation and excitation sources
In the current review period a few brand new instrument concepts as well as new ideas for further advancement and improvements of well-established technologies were announced. Not surprisingly, due to a growing demand for improved medical diagnostic instruments, this field of research was well represented. Sato et al.16 constructed an XRF CT system and performed XRF tomography with an X-ray tube-generated cone-beam and a collimated X-ray detector to map the distribution of iodine in a phantom model. Their system was based on a low power tungsten target X-ray tube operated at 80 kV with a 3 mm thick aluminium filter. The iodine K-series X-rays were registered using a collimated CdTe detector. The same research group, in a report by Hagiwara et al.,17 described a similar experiment for mapping iodine distribution by XRF CT. This time, a cerium-target X-ray tube was applied. The detection system remained the same as described in the earlier work.16 Both reports confirmed the capability of the constructed detection system to be used in the “SPECT” (single-photon emission computed tomography) medical diagnostic technique. Jones and Cho18 described a Monte Carlo study that demonstrated the feasibility of polychromatic cone-beam XRF CT imaging of gold nanoparticle-loaded objects. The authors developed a bench-top XRF CT system capable of determining the spatial distribution and concentration of gold nanoparticles in vivo using a diagnostic energy range polychromatic (i.e. 110 kVp) pencil-beam source. Accurate images of a gold nanoparticle-containing phantom were successfully reconstructed for three different phantom configurations, with both spatial distribution and relative concentration of gold nanoparticles identified. The pixel intensity of regions containing nanoparticles was linearly proportional to the gold concentration. The authors suggested that this Monte Carlo study offered the possibility of developing a bench-top, polychromatic, cone-beam XRF CT system for in vivo imaging.A few interesting reports were published during the review period concerning new ideas for laboratory-scale instruments devoted to general XRF applications. Fujisaki et al.19 designed an automated system for reconstructing the shape and elemental composition of minute samples. The system combined an XRF mapping spectrometer with a high-precision milling/polishing machine. The surface of the analysed sample was mirror-finished and then the distributions of elements were mapped by the XRF technique. In the next step, a layer of controlled thickness was removed and the whole process was repeated. After a few iterations of this procedure, the obtained maps of elements were combined in a 3D volumetric reconstruction of the sample. Consequently, the method is destructive and applicable only to samples that can be ground and polished. Tsuji et al.20 constructed a WDXRF imaging spectrometer utilising a custom-made area detector with straight channel polycapillary optics in front. The optics replaced the original Soller slits used in a conventional WDXRF spectrometer. The X-ray energy to be mapped was selected by the LiF(200) crystal. The overall energy resolution of the spectrometer was in the range 130 to 150 eV for Zn-Kα peak. Nakaye and Kawai21 demonstrated the capability of an ordinary audio digitiser applied as the ADC for digitising the signal from reset-type charge-sensitive silicon drift detector preamplifiers. The signal was subsequently fully software-processed in a PC to obtain the pulse-histogram in the form of an energy dispersive X-ray spectrum. The authors reported FWHM of 178 eV at 5.9 keV using a shaping constant 93 μs. Due to the sampling rate of the digitiser (192 kS s−1) the counting rate of the spectrometer was limited to maximum 10 kcps.
As one might expect the majority of instrumental developments took place at the synchrotron beamlines. The synchrotron set ups were dominated by combination of X-ray emission, absorption, and diffraction techniques very often available in micro-spot configuration. Grochulski et al.22 published a detailed report on the capabilities and performance of the techniques available at the Canadian Macromolecular Crystallography Facility, Canadian Light Source. This facility was established a few years ago with two beamlines, an undulator beamline and a bending-magnet beamline. The facility was devoted to macromolecular crystallography, in particular well suited to small crystals and crystals with large cell dimensions. Cotte et al.23 reported the construction of a polycapillary-based WDXRF spectrometer at the ESRF beamline ID21. The spectrometer was coupled to an X-ray microscope with a μ-XANES capability. It was devoted to the analysis of complex matrices and specifically for samples and objects from the cultural heritage area. With an energy resolution of a few tens of electronvolts, it could resolve most of the spectral interferences that energy dispersive detectors cannot handle. Kleymenov et al.24 constructed a wavelength dispersive Johann-type X-ray spectrometer utilising five spherically bent crystals and a pixelated detector with a single photon counting capability and an accurate energy calibration (precision better than 1.5 eV). The spectrometer covered the Bragg angle range from 60° to 88°, it had an energy resolution from sub-eV up to a few eV, and a detection limit of 0.4% m/m for Cu-Kα1. The system was designed for operation at the Swiss Light Source. Kujala et al.25 developed a short focal length bent crystal Laue analyser for measuring copper speciation in biological systems. The analyser could be operated in the incidence and emission energy scan modes with an energy resolution of about 14 eV. Deng et al.26 announced the establishment of the XRF-CT technique at the Shanghai Synchrotron Radiation Facility, beamline BL13W1. In their report, the first results for the XRF-CT measurements of the distribution of Cd in a polymethyl methacrylate phantom test sample were published.
Several very interesting reports were published describing the measurement and data processing methodologies for use with combinations of μ-analytical techniques. Bozzini et al.27 applied a unique combination of X-ray microscopic techniques available at the Elettra Synchrotron Facility, Italy, including soft X-ray scanning transmission microscopy and μ-spot XAS/XRF to characterise the spatial and chemical state changes occurring during an in situ experiment monitoring the corrosion of Ni electrodes in contact with ionic liquids at room-temperature. The morphological changes induced by the corrosion process were characterised with an unprecedented level of detail. Cong et al.28 proposed a quantitative reconstruction algorithm to obtain the distribution of nanophosphors within biological objects by combined scattering-compensated X-ray luminescence/fluorescence tomography. Nanophosphors emitting in the near-IR upon excitation by X-rays were used as optical probes to visualise molecular pathways in biological processes. The feasibility and merits of this combined approach were demonstrated in the report. Fauquet et al.29 proposed a combination of microanalytical techniques, including shear force microscopy with local detection of synchrotron μ-beam X-ray induced luminescence and XRF emission, for the simultaneous mapping of surface topography and chemical composition. They reported an excellent performance of the combined measurements for characterisation of thin layer samples. Lagomarsino et al.30 successfully merged nano-beam XRF analysis of the magnesium intensity distribution in whole cells with the data on the distribution of the cell thickness obtained with AFM to determine magnesium concentration maps. The XRF and AFM data were obtained in independent measurements and then carefully registered and merged to produce the magnesium distribution map normalised to the thickness data. This work demonstrated that the thickness-normalised magnesium distribution, which could be considered as the magnesium concentration image, could be very different from the distribution of the amount of magnesium obtained when XRF data was not normalised.
In some very specific and focused research, related to fusion and plasma physics, Maddox et al.31 applied various methods of X-ray detection for plasma diagnostics in high energy density experiments to determine X-ray spectra and conversion efficiency of laser energy into X-ray line emission. X-rays were produced by shooting short-pulse laser beams at Ag, Mo, and plastic targets. The employed energy calibrated X-ray detection systems included a CCD camera in single-photon counting mode (5–25 keV), crystal spectrometers (10–90 keV), Ross pairs (18–70 keV) and filter stacks (80 keV–2 MeV).
Last but not least in this section, a significant contribution towards expanding our understanding of the universe with the use of X-ray spectrometry was offered by Oakley et al.,32 who reported the development of a soft X-ray spectrometer with a wavelength resolution of about 100 (Δλ/λ) to be carried by rocket for suborbital studies of large sources of radiation such as the remnants of nearby supernova. The instrument was durable and could also be operated over long-time periods for orbital missions designed to collect data on soft X-rays from diffused regions.
2.2 Detectors
It is pleasing to note in this year's review the predominance of pixellated detectors and EDXRF imaging/mapping using a variety of materials and readout technologies. This trend will undoubtedly continue due to the improved sensor array fabrication and ASIC readout devices that are nowadays more widely available. In what was described by the authors33 as an “X-ray colour camera” a pnCCD silicon-based pixellated detector array was described for use as a full-field XRF imaging detector. The detector sensor was 450 μm thick, providing a usefully high quantum efficiency of 30% at 20 keV, making it highly suited to EDXRF mapping. In addition to its X-ray stopping power, the detector provided an impressive energy resolution of 152 eV at 5.9 keV at an operating count rate of 450 kcps, which, at the reported frame rate of 400 Hz, provided a powerful real-time 2D EDXRF camera. When operated in a single photon counting mode, the photon energy, position and time were recorded for each frame. The detector was also used in conjunction with a polycapillary optic for each pixel of the detector array, allowing the system to provide high spatial resolution, pseudo-colour EDXRF elemental images in real-time and with high energy resolution and count rate. The analytical performance of this full-field XRF camera was further described by Scharf and co-workers34 who used as an excitation source either a microfocus laboratory X-ray tube with a 30 μm spot size or SR at the BESSY II synchrotron facility in Berlin, Germany. The impressive set up included a pnCCD detector with an energy resolution of 152 eV at 5.9 keV that was described in detail and the associated acquisition system was reported to record simultaneously 69696 EDXRF spectra with a spatial resolution of 50 μm and a full frame imaging area of 12.7 × 12.7 mm2. Quantum efficiency of the pnCCD sensor was excellent over the energy range 3 to 40 keV, being limited only by the 50 μm beryllium entrance window at the low energy end and by the thickness, 450 μm of the silicon sensor material at the high energy end of the range. As with conventional SEM-based EDS, the full spectrum data cube comprising 264 by 264 spectra was saved for further off-line XRF data analysis. Such a system is undoubtedly impressive and offers a new dimension and level of performance in real-time high energy-resolution EDXRF imaging at medium spatial resolution. The performance characteristics of pnCCD detectors in the energy range 90 eV to 2 keV were reported by Kimmel and co-workers35 for use in free electron laser and other high energy physics experiments. The detectors were carefully characterised using 2 keV photons and with photon incidence rates of a few up to 100 photons per frame. The authors were particularly interested in optimising detector calibration protocols and in the effects that could arise from charge spreading between the pnCCD pixels themselves. Philipp et al.36 described a 194 by 185 pixel silicon pin diode sensor layer coupled to a custom ASIC readout system used in a high speed detector for free electron laser experiments. The detector was designed to deal with the instantaneous flux from each laser pulse of up to 1012 photons per s and a frame rate of 120 Hz or greater. The authors reported that a future device would be constructed with an impressive 1516 by 1516 sensor array. An interesting multi-detector module comprising up to 5 Medipix2 or Timepix readout modules was developed by a team at ESRF, Grenoble for operation on X-ray beam lines at that facility. The system was claimed to operate at frame rates of up to 1400 Hz, thereby generating Data Mountains of truly Alpine proportions! Although not yet fully developed, Miyoshi et al.37 described a pixellated detector module based upon silicon-on-insulator technology.In addition to the continuing developments using silicon-based pixellated detectors there was also continuing interest and developments in sensor materials with greater X-ray stopping power. CdTe or CdZnTe pixellated detectors continued to be favoured in this regard. A new small pixel, CdZnTe pixellated detector was described by Wilson et al.38 in which an array of 20 × 20 pixels on a 250 μm pitch was bonded directly to a custom-designed and built energy dispersive readout ASIC. The impressive real-time acquisition system could store up to 40![[thin space (1/6-em)]](https://www.rsc.org/images/entities/char_2009.gif)
000 frames per second. The use of CdZnTe gave a useful EDXRF energy range extending up to 150 keV and an energy resolution per pixel was achieved of between 1.09 and 1.50 keV at 59.54 keV making it attractive for a variety of EDXRF and other X-ray applications. A further development of this detector system was described by Seller et al.39 who increased the array dimensions to 80 × 80 pixels. The pixellated sensor layer was bump-bonded to the large area ASIC readout and used an extension of the custom data acquisition system that had been previously used successfully with a 20 × 20 array. An energy resolution was observed of <1 keV at 59.5 keV and the novel connection and readout systems developed by this team were expected to allow many such arrays to be placed closely together with negligible dead space. This set-up enabled large area energy dispersive detectors with very high stopping power to offer significant opportunities for applications using high speed EDXRF and other X-ray mapping in the 5 to 150 keV range. The characteristics of an impressive highly stackable 16 × 16 array of 1 × 1 × 2 cm3 CdTe detectors were described by Limousin et al.40 The design of the so-called Caliste256 detector array used custom ASIC readout devices that allowed stacking perpendicular to the detector surface and permitted each module to be butt-stacked on any of four sides to yield a very compact 3D detector array suitable for high energy X-ray applications and destined, in this case, for a hard X-ray space telescope. Each of the 256 pixels with their associated ED channel could be read out independently and the overall system delivered an impressive energy resolution of <1 keV at 59.5 keV. The advantages of CdTe sensors for high energy ED X-ray imaging were also described by Guni and colleagues,41 who used such sensors in a Medipix2 readout system for X-ray measurements of higher Z materials. A custom low-noise CMOS readout system was described42 for a CdTe X-ray detector array comprising 150 by 64 pixels although at the reported stage of development, the detector seemed not to have been used for ED purposes but only as a conventional total signal imaging detector. Although mainly used in a micro-CT medical X-ray application, the pixellated CdTe detector array described by Wang and coworkers43 had sufficient energy dispersing capability with its custom ASIC readout system to separate energy discrimination into six energy regions. Despite suffering from poor energy resolution, which smeared the detected X-ray absorption edges, along with significant charge sharing, the authors concluded that this multiple energy device had advantages over single energy μ-CT. The importance of starting with good detector grade CdZnTe was confirmed by Camarda and co-workers44 who investigated a single crystal of dimensions 15 × 15 × 7 mm3 and found it to contain distortions, low-angle and sub-grain boundaries and tellurium inclusions. When used in either a single or a pixellated detector, the authors found, unsurprisingly, problems from distorted electric fields and charge trapping that significantly degraded detector performance.
In the use of other detectors for EDXRF imaging applications, a detector based on a micro-hole and strip plate was employed in conjunction with a pinhole camera and conventional laboratory X-ray tube.45 The authors claimed the photon counting and 2D capability of the detector demonstrated it to be a promising device for EDXRF imaging despite the very poor energy resolution of the detector itself, which would severely limit the applicability; as will the uninspiring spatial resolution when compared to the pixellated semiconductor ED X-ray detectors that are increasingly available and offer much more attractive performance. Somewhat similarly, but adopting a more conventional approach to higher energy EDXRF imaging, Enomoto et al.46 used a single CdTe detector and a conventional medical X-ray tube with a 3 mm thick aluminium primary beam filter in a system where the sample was scanned in 25 μm steps (in x and y directions) and spectra were acquired for 0.5 seconds per step. Using this set-up, the authors were able to detect cancerous cells in mice when the cells were detected by means of Ce K and Gd K lines from marker molecules. The relatively long acquisition times and sequential nature of this system clearly demonstrated why there is so much more interest in developing direct reading 2D energy dispersive X-ray detector systems for medical, environmental and industrial applications. Finally, in the area of energy dispersive X-ray imaging, Lombi et al.47 reviewed how recent advances in XRF detection systems were being applied to rapid hard XRF imaging in a number of important applications such as environmental studies. The authors highlighted the benefits of fast, high count rate detectors for the direct measurement of hydrated samples, especially in very high energy SRXRF studies. In addition, the use of high-speed SRXRF detection was expected to lead to real breakthroughs in speciation of environmental samples. Sharma et al.48 modelled the transport of charge carriers in X-ray photoconductor detectors focusing on charge recombination effects. This type of detector is promising for imaging applications in the field of medical diagnostics. The authors compared two recombination approaches finding that results produced by both models correlated well but differed for individual clouds of charge carriers. In the authors' opinion, further optimisation of the models was required.
In addition to the wide variety of materials being used in pixellated detectors, it is interesting to note the continuing investigations into a number of diverse detector materials. In a comparison49 of mercuric iodide and CdZnTe detectors, primarily for hard X-ray and gamma ray detectors, it was shown that the charge collection efficiency was higher for CdZnTe, leading to improved peak shapes and lower spectrum background. The authors made careful measurements and simulations of charge carrier mobility and lifetime, further demonstrating the practical benefits of CdZnTe over mercuric iodide. A significant reduction in leakage current was predicted in careful modelling by Chang et al.50 for a CdZnTe detector on which HgTe/HgCdTe superlattice contacts were used. It remains to be seen if practical improvements in detector performance will result. It has long been known that the choice of metal electrode material is very important for many aspects of the performance of Si(Li) and other silicon-based detectors, no doubt leading Zheng and co-workers51 to perform a comparative study of the effect of 4 different metal contacts (gold, platinum, rhodium and ruthenium) on CdZnTe detector crystals. The authors used electroless deposition methods with mixed results but indicated, rather inconclusively, that the use of platinum resulted in the lowest leakage current. A study was reported52 of the growth of detector-grade CdZnTe in a vertical Bridgman furnace and it was found that better detector characteristics were obtained for crystals grown with a boron oxide encapsulation. A group at Northwestern University, Illinois reported the fabrication of X-ray and gamma rate detectors from various thallium chalcohalides.53,54 Devices made from either Tl6Se4 or TlGaSe2 single crystals were found to yield the best detector characteristics and were comparable in performance, particularly energy resolution, to commercially available CdZnTe detectors. Finally, Stankovic and co-workers55 proposed silicon carbide as potentially the best detector material for energy dispersive X-ray spectroscopy when faced with hazardous radiation environments such as those found in nuclear safeguards and space science applications. Work reported in this paper focused on Monte Carlo modelling of the characteristics of the proposed detectors and practical confirmation of the models remains to be completed.
Somewhat disappointingly, there was only one publication available for review on the topic of high resolution cryogenic detectors, that seemed to dominate the ED news less than a decade ago. In that paper,56 a conventional Ti/Au microcalorimeter operated at 140 mK was developed specifically for the complex L series spectroscopy of the transuranic elements. A layer of gold 5 μm thin was deposited on the titanium/gold bilayer to increase quantum efficiency into the range 35 to 80% for the 6 to 25 keV energy range of interest. As expected, an impressive energy resolution of 80 eV at 17.75 keV was achieved although one wonders, given the very low count rate of such detectors, how much worse the resulting spectroscopic data might be from a modern SDD with an energy resolution of 120 eV at 5.9 keV and an effective area and count rate several orders of magnitude higher than that of the microcalorimeter.
The solitary paper57 available for review on gas proportional detectors, described a so-called gas electroluminescence X-ray detector. Various gas fill compositions of neon and xenon were investigated and the authors reported the best spectroscopic results were obtained when using a gas fill of 80% Ar + 20% Xe pressurised to 3 atm. A useful energy resolution was obtained of 7.25% at 5.9 keV, prompting the authors to use the detector in an X-ray diffractometer thereby enabling spectroscopic separation of Kα from Kβ lines of the widely used copper target X-ray tube.
2.3 Spectrum analysis, matrix correction and calibration procedures
A significant number of contributions published in the reviewed period were devoted to improvements in analytical techniques and data processing algorithms for the applications of X-ray imaging and spectrometric methods in medical diagnostics. Russo and Mettivier58 proposed a new procedure to measure the focal spot dimensions of medical X-ray tubes by using a so-called coded aperture mask. The coded aperture consisted of a large number of smaller apertures arranged in an array. The advantage of the proposed method over single pinhole or slit camera measurements lay in the combination of very good brightness of the focal spot image, simultaneous characterisation of the focal spot in two dimensions, and robustness of the aperture mask alignment. When combined with a digital area detector, the method allowed a fast and accurate characterisation of the focal spot dimensions of medical X-ray tubes operated at low loadings. In a report by Brown et al.59 a Monte-Carlo approach was presented for back-calculating X-ray tube emission spectra based on the spectra measured in a direct pinhole geometry with Si PIN detector. The method was applied to X-ray sources used in orthovoltage radiation therapy with an X-ray generator operated at 150–300 kVp. In other research targeted towards medical applications, Aviles et al.60 developed a novel hybrid algorithm for incoherent scatter CT by combining an analytic-iterative procedure for correcting the attenuation of photons and filtered back-projection algorithm for image reconstruction. The tests showed that the algorithm reconstructed the images qualitatively in a few iterations even in the presence of a multiple scatter. The method had promising features for in vivo applications in medical imaging. In a more biologically oriented application, Vaz et al.61 thoroughly examined the influence of various scan parameters and spectrometer configuration on the quality of μ-CT analysis of porosity and pore-size distribution in Oxisol samples. The μ-CT scans were performed with a commercial laboratory-scale μ-CT instrument. The best quality reconstructions were achieved with an Al/Cu filter, however even at the best applied resolution of 3.7 μm, the CT-estimated porosities vastly underestimated the physically measured porosity values. Yang et al.62 carried out research that may speed up X-ray CT imaging, an improvement that is always welcomed especially in medical diagnostics and in real-time applications. The method, called adaptive region-of-interest (ARO), detected sample boundaries in the sinogram data, so vastly reducing the amount of data to be processed by the CT reconstruction algorithm. In the experiment performed by the authors, the procedure reduced the overall processing time by a factor of 5, without degrading the quality of the reconstructed data. Gherase and Fleming63 proposed a novel approach for the depth-dependent analysis of element concentrations. The method relied on a specific layered calibration procedure. The advantage of the new approach over the usual multiple-angle or confocal XRF scanning measurements was single-angle XRF measurements. Such an approach was much more suitable for in vivo determination of e.g. As and Se in skin as it significantly reduced the radiation exposure.The number of reports published during the past year confirmed a strong interest within the scientific community in further updating data on the so-called fundamental parameters as well as in the verification and advancement of the fundamental parameter algorithms and related methods. A number of reports including one review paper appeared in this area covering a variety of possible application fields. Horakeri et al.64 determined the K-shell fluorescence yields of Ba and La applying a simple experimental set up comprising a 57Co radioisotope excitation source and NaI(Tl) counter. The results obtained agreed well with the data published by Hubbell et al. (1994). Yilmaz et al.65 determined experimentally Coster–Kronig L-subshell transition factors for thulium using a 241Am radioisotope source excitation. The determined factors were systematically smaller when compared with existing literature data. In another report by Yilmaz et al.,66 results of the experimental determination of Coster–Kronig L-subshell transition factors for Nd and Pm were published. In this research, the authors found that with increasing excitation energy, the values of Coster–Kronig enhancement factors also increased. Gonzales et al.67 examined possible anisotropy in the emission of Au-Lα characteristic X-rays upon excitation by a 241Am radioisotope source and did not find any, contrary to the theory developed earlier by Flugge et al. (Flugge et al., Phys. Rev. Lett., 1972, 29, 7–9). However, the effect may be very subtle and therefore difficult to observe experimentally. The experimental results were in agreement with the results of Monte Carlo simulations using the PENELOPE code. Kalinin et al.68 studied the propagation of instrumental uncertainties in anode voltage, incidence and exit angles, thickness of the anode coatings, and purity of the exciting spectrum on the precision of element determinations by XRF technique when utilising the fundamental parameter approach. They demonstrated an overall 0.5% to 1% relative contribution on the final concentration estimate. Such magnitudes of uncertainty can be regarded as significant in the high-precision analysis of main sample constituents. Galchenko et al.69 used a Monte Carlo simulation code to investigate the relations between the intensity of primary radiation and XRF versus the X-ray scattering peaks. They used the X-ray scattering peak for normalisation of XRF signals for the determination of Pb and Zn in a bioassay with an accuracy of better than 3%. A comparison of experimental and theoretical results for fundamental data was given by Bonzi et al.,70 where the L shell fluorescence cross-sections of the elements in the range 45 < Z < 50 were determined at 8 keV using Synchrotron radiation. The individual L X-ray photons, Ll, Lα, Lß1, Lß2 Lγ1 and Lγ2 produced in the target were measured with a high resolution Si(Li) detector. The experimental set-up provided a low background by using a linearly polarised monoenergetic photon beam, thereby improving the signal-to-noise ratio. The experimental cross-sections obtained in this work closely agreed with the theoretical values calculated using Scofield and Krause data, except for the case of Lγ, where values measured were slighter higher. Bochek et al.71 tested the performance of an in-house developed X-ray interaction simulation computer code GEANT4, observing good agreement between simulated and measured X-ray spectra originating from 241Am radioisotope sources scattered from various targets and X-ray fluorescence emitters. Parviainen et al.72 investigated the influence of particle size effects on XRF signals in the energy range 1 keV to 10 keV by using the Monte Carlo simulation code. They found a strong influence of the mean particle radius on the intensity of emitted characteristic X-rays, especially noticeable when the radius was comparable with the mean free path of X-rays. Their research confirmed that the standard fundamental parameter models, when applied to samples with strong particle size effects, could lead to large errors in the determined concentrations of elements. In a rather controversial report, Mittal and Gupta73 cast doubts on the reliability of X-ray production cross-sections determined and published so far by other authors due to the confusion arising from the use of barns (1 barn = 10−24 cm2) and cm2 g−1 units. However, in the opinion of this review their report completely missed the point of merit and no evidence whatsoever was presented to support the authors' statement. In another critical article, Molchanova et al.74 disputed the results published in an earlier report by Rousseau (R. Rousseau, Spectrochim. Acta B, 2006, 61, 759), pointing out several inaccuracies in the XRF models presented. These critical findings were supported by experimental results. Building on his long experience in the field of X-ray spectrometry and knowledge of the topic, Markowicz75 published a review that focused on factors influencing the accuracy of EDXRF analysis taking into account physical and chemical matrix effects, sample types (so-called thin, intermediate thickness, and thick samples), various methodologies for correcting matrix effects, as well as quality control protocols. The general conclusion was that the interpretation and quantification of EDXRF data is a complex process requiring care and a good background knowledge in X-ray physics, especially when dealing with in situ measurements.
A few articles dealt with general effects and phenomena related to X-ray spectrometry and the interactions of X-rays with matter. Hodoroaba et al.76 investigated the phenomenon of X-ray scattering by applying an energy-tuneable synchrotron source to develop a physical model for the background in X-ray fluorescence spectra. The model took into account single Rayleigh and Compton scattering, the effect of bound electrons, Compton broadening, and the degree of polarisation of scattered radiation. The quality of this model was also verified with Monte-Carlo simulations. Harding and Olesinski77 elaborated a Compton profile fitting procedure in which the theoretical 1s, 2s, and 2p orbital profiles of C, N, and O were parameterised versus the atomic number and approximated by Gaussian functions. By least-square fitting of the parameterised profiles to the measured Doppler broadened W-Kα Compton profiles obtained by scattering the radiation on water and ethanol samples, the effective atomic numbers of both substances were discriminated with satisfactory accuracy. This method seemed to have significant potential in medical and security screening applications. Korun and Modec78 studied the effect of coincidence summing of X-rays and conversion electrons emitted in the decay of the first excited state of 137Ba. They demonstrated that the probability of the detection of a conversion electron decreases exponentially with absorbent thickness and that the probability of detecting a conversion electron emitted towards the detector was about 60% when no material was present on its path from the source.
A few articles and one review paper were devoted to the improvements of X-ray analytical methods related to structural research with such techniques as XRD, EXAFS, RIXS (resonant inelastic X-ray scattering) and structure oriented X-ray scattering. Soper and Barney79 developed a general method and implemented it with a computer code for processing raw white-beam X-ray total scattering data, which included diffraction and X-ray fluorescence, to determine the differential scattering cross-section and pair distribution function. The pair distribution function represented the local noncrystalline order of the material, which can be glass or liquid. The detailed model included corrections for XRF, Bremsstrahlung, polarisation, attenuation, and multiple scattering and was applicable to X-ray tube and synchrotron radiation sources. Further development of the methodology was envisaged to optimise the choice of specific correction parameters. Medling and Bridges80 proposed a simple background removal procedure for correcting EXAFS data acquired in emission mode at the Cu–K edge in ZnS:Cu samples. The need for background correction arose due to the low copper concentration. Additionally, the EXAFS data were partially disturbed by the low-energy tail of Zn-Kα peak and a contribution from the Zn X-ray Raman peak. Ament et al.81 reviewed developments over the last decade in RIXS, focusing on investigations of low-energy charge, spin, orbital, and lattice excitations in solids. Both experimental and theoretical model developments were discussed as well as emerging prospects for the use of RIXS with the advent of X-ray laser sources.
Two reports were largely devoted to algorithms for the deconvolution of XRF spectra. Gardner and Li82 presented an improved computer code based on a least-squares approximation of the analysed X-ray spectrum with a Monte Carlo generated library spectra for estimating the elemental composition of analysed samples. Its application to the μ-EDXRF analysis of metal alloys and rock samples was demonstrated. The code used a variance reduction technique in which the statistical variance of the elemental libraries was equalised to the variance observed in the analysed spectrum. The code greatly increased the accuracy of XRF analysis. Arzhantsev et al.83 employed the wavelet transform filtering technique, well-known in the field of signal-processing, to detect the presence of metals in pharmaceutical materials. The method was fast and robust and did not require any a priori assumptions about the shape and background levels in the EDXRF spectra. It used the Mexican hat wavelet function to detect the presence of X-ray peaks. The method was applied to over 1200 measurements from five different hand-held XRF instruments by six laboratories across the United States with estimated detection limits for As, Cr, Hg, and Pb equal to 8, 150, 20, and 14 μg g−1, respectively.
2.4 X-ray optics and micro-fluorescence
The development, optimisation, and testing of focusing capillary X-rays optics was the topic of interest in two reports. Nakazawa et al.84 evaluated the performance of Au-coated glass monocapillaries when coupled to a Mo-anode μ-focus X-ray spectrometer and applied for XRF analysis. Two capillaries with 400 μm and 700 μm diameters were tested. The results showed an intensity enhancement factor of 1.5, as compared to uncoated glass capillaries. Ozkan et al.85 carried out an experimental study of a polycapillary parallel collimator with the aim of tailoring the further design of such optics to the specific requirements of low-angle X-ray scattering imaging. The determined response function of the optics enabled the modelling of photon transport customised to applications at specific synchrotron setups.The shrinking of the X-ray beams in synchrotron beamlines has reached the sub-micrometre and nano-beam level. Wang et al.86 demonstrated the feasibility of a sub-μm X-ray beam for the characterisation of nanomaterials. They utilised nano-beam XRF/XRD techniques (beam FWHM = 250 nm) at the 2 ID-D beamline, Advanced Photon Source, USA and characterised the morphology, registered diffraction patterns from single crystalline NbSe3 nanobelts with a thickness less than 50 nm. The measurements were performed in a diamond anvil cell at a pressure of 20 GPa. Chu et al.87 successfully applied a synchrotron nano-beam XRF technique for examining the spatial variation of Co and Zn in single cobalt-implanted ZnO nanowires. The exceptional brilliance of the synchrotron beam also allowed the detection of residual impurities such as Fe and Sn. The results confirmed the overall uniformity in the distribution of Zn and Co along the wire, with some Co localisation within thicker irregularities. Bertoni et al.88 characterised nanoscale defects in large area solar cells by utilizing the synchrotron nano-probe XRF technique. The nanoscale defects significantly affected the efficiency of solar cells. With 80 nm spatial resolution and a hierarchical approach to the characterisation of defects, they could distinguish between the different types of dislocations. The elaborated methodology was applicable to the nano-scale characterisation of other nano-defect-limited energy systems. Using a μ-beam approach, Mino et al.89 applied a combination of synchrotron techniques including μ-EXAFS, μ-XRF, μ-XRD, and photo luminescence (PL) to characterise, with micrometre resolution, a multi-quantum-well electro-absorption modulated laser via the selective area growth method. This complex and specialised device was used in high-speed (10 Gb s−1) telecommunication applications. The EXAFS and XRF data showed good qualitative agreement with the μ-XRD/PL results, however further technical improvements should be implemented to make the μ-EXAFS analyses fully quantitative.
Sadly, even nowadays not all material scientists are aware of the complementarity of the laboratory-based μ-XRF technique and the ED-SEM. Davis et al.90 rediscovered this link in an examination of the heterogeneity of concrete samples. They considered non-destructive μ-XRF imaging to be complementary to and, to some extent, more convenient when compared with ED-SEM, with better detection limits, the possibility of working at atmospheric pressure, and at mid-sized spatial resolution which is of importance when large samples are to be characterised.
In a report strictly devoted to methods for quantitative μ-XRF analysis, Czyzycki et al.91 described an inverse Monte Carlo simulation code capable of modelling X-ray characteristic peak intensities and estimating the elemental composition of stratified multicomponent samples by processing the data from confocal μ-XRF measurements. The results obtained by the Monte Carlo code and by using an analytical approach developed earlier by Malzer and Kanngiesser (W. Malzer and B. Kanngiesser, Spectrochim. Acta B, 2005, 60, 1334) were assessed against experimental values from measurements of layered reference samples. Both methods showed good agreement with experimental results and known data with slightly better performance reported for the Monte Carlo code in estimating the elemental depth profile layer thicknesses. Wolff et al.92 elaborated a fundamental parameter calibration procedure for μ-XRF analysis. In their method, using measurements on thin-film standard samples, the excitation spectrum originating from X-ray tube, being affected by the transmission of focusing X-ray optics, was calculated and then used in the analysis of unknown samples. The method validation with certified reference materials yielded accuracy in the order of 2%, 10%, and 25% for main, minor, and trace elements, respectively. Continuing the subject of quantitative μ-XRF analysis, Trojek93 developed an interesting procedure for correcting the effects of variations in surface topology during μ-XRF mapping of element distributions in otherwise flat metallic objects such as coins. The procedure added the incidence and exit angles to a set of unknown variables, the other being the concentration of the elements. By solving the set of fundamental parameter equations, both the local concentrations and incidence/exit angles were recovered. The map of incidence/exit angle distribution reproduced the topography of the sample surface. Additionally, more precise average object composition was obtained compared to the use of constant effective incidence and exit angles. The method was applicable to objects with 100% of the chemical composition assessable.
2.5 Synchrotron radiation
Other instrumental advances in SR beamlines included developments described by Pereira et al.98 to support X-ray transmission microtomography (CT) combined with X-ray fluorescence microtomography at the Brazilian Synchrotron Light Laboratory (LNLS), Campinas, Brazil. The main use of this facility was to determine elemental distributions in biological samples (breast, prostate and lung samples) to verify the concentration of elements that have a role in the pathology of each of these tissues observed by transmission CT. Fluorescence photons were collected with an energy dispersive HPGe detector placed at 90 degree to the incident beam, whilst transmitted photons were detected with a fast NaI(Tl) scintillation counter placed behind the sample with respect to the beam. In a paper by Mazuritskiy,99 soft SR X-rays transmitted through microchannel plates were studied. An analysis of monochromatic radiation transported through the microchannels allowed the author to understand how interactions of the channelling radiation with unoccupied electronic states in the microchannel plate led to the excitation and propagation of X-ray fluorescence in the microchannels. This result is an important contribution to the development of new wave guides for novel X-ray focusing devices.
A number of contributions described developments in the biological sciences. In a review article, Lombi et al.106 reported advanced in situ spectroscopic techniques and their applications in environmental biogeochemistry, summarising the challenges, and highlighting recent advances and scientific gaps. The use of synchrotron-based techniques and other methods were discussed in detail, as was the importance to integrate multiple analytical approaches to confirm results of complementary procedures. The authors argued that the future direction of research will be driven in part by the need to undertake risk assessments for new materials (e.g., nanotechnologies) and the realisation that biogeochemical processes need to be investigated in situ under environmentally relevant conditions. Shi et al.107 investigated copper uptake and its effect on the metal distribution in root growth zones of the Cu-tolerant plant Commelina communis revealed by AAS and SRXRF. The Cu distribution (as well as Fe, Mn, and Zn), following treatment with a 100 μmol L−1 solution of Cu was investigated by SRXRF. High levels of Cu were found in the root meristem, and higher Cu concentrations were observed in the vascular cylinder than in the endodermis. The influence of copper on the uptake of Fe, Mn and Zn was also considered in detail. Yan et al.108 described a μ-SRXRF imaging method incorporating fast on-the-fly scanning on the hard X-ray beamline at SSRF (Shanghai Synchrotron radiation Facility), China. The authors presented images of a standard nickel mask and the elemental distributions of Cu, Fe, K, Zn in a specimen of mouse spleen. Qiu et al.109 reported preliminary experimental results of internal elemental imaging by scanning XRF microtomography using the hard X-ray microprobe beamline at the same Shanghai Synchrotron Facility. An image was presented of the cross-sectional elemental distributions within a single human hair, and the validity of these results were confirmed by comparing the results with the elemental maps of a thin hair section obtained using the well-established μ-SRXRF mapping method. The authors reported the tomographic images of heavy elements like Cu, Fe and Zn were found to be in good agreement with the corresponding μ-SRXRF maps. Light elements, such as S, however, showed discrepancies in the image patterns due to non-negligible self-absorption within the sample, demonstrating the need for more sophisticated correction algorithms.
2.6 TXRF
Horntrich et al.111–113 presented in a set of results from detailed studies of the influence of dried sample morphology, excitation energy and elemental distribution of a sample on the silicon wafer surface. The authors showed that the thin film approximation, which was conventionally applied over a wide mass range, astonishingly was only valid in the low ng region, whereas deviations from the linear relation between intensity and mass were observed from 200 ng upwards depending on the excitation energy. The authors speculated that this might be caused by the sample morphology, due to inhomogeneities and different sample shapes. To study these effects, single and multielement samples were investigated by μ-SRXRF and optical microscopy. It was shown that the optical microscope images were correlated to the investigated elements, thus inhomogeneities were directly visualised. For multielement samples, it was shown that the elemental distribution was homogenous and thus the use of an internal standard was justified. However, in silicon wafer surface analysis the addition of an internal standard is forbidden and quantification is performed using external standards and the direct comparison of intensities. Consequently, theses deviations from linearity lead to systematic error in quantification. In the second contribution, nickel samples of different concentrations were measured with Mo-Kα as well as W-Lβ radiation and calibration curves established. The experimental results were compared to calculations performed with a self-developed simulation model taking into account absorption phenomena of primary radiation through the sample, plus fluorescence radiation to the detector. It was clearly verified that the lower excitation energy of W-Lβ led to improved Ni intensities and lower detection limits, the saturation effect appeared at lower sample mass when compared with excitation using the higher energy Mo-Kα line. In the third contribution, different theoretical sample shapes were calculated and several parameters varied (excitation energy, density, diameter/height ratio of the sample). Among all the investigated sample shapes, the ring structure best matched the ideal shape for TXRF spectrometry, leading to the highest fluorescence intensity and lowest saturation effects. Your reviewer anticipates experimental verification.
Regarding the development of instrumentation, a new colour X-ray camera was successfully tested and applied to the fast spatially resolved analysis of trace elements. Kuhn et al.114 reported that samples were prepared in the conventional way, on the reflector for TXRF spectrometry. A sample area of 10 × 10 mm2 was investigated within a spatial resolution of 50 × 50 μm2 in 30 seconds, which was approximately 350 times faster than conventional scanning systems for trace element distributions. The main components of the X-ray camera were a polycapillary optic and a pn-CCD chip with an active area of 13 × 13 mm2. This was divided into a 264 × 264 pixel array, each with a size of 48 × 48 μm2. A full spectrum with an energy resolution of 152 eV at 5.9 keV and a chip temperature of 246 K was recorded for each pixel with a read out rate of 400 Hz. Sartore et al.115 reported a quartz crystal microbalance (QCM) chemical sensor for monitoring heavy metal ions in aqueous solutions. This polymer grafted QCM sensor was able to selectively adsorb Cd, Cr, Cu or Pb from a wide concentration range (0.01 to 1000 μg g−1) by complexation with functional groups in the polymer. X-ray reflectivity and TXRF measurements were carried out to characterise the modified and unmodified metal ions.
2.7 Hand-held and mobile XRF and planetary exploration
Although recent developments in hand-held instrumentation have substantially improved the capabilities of this form of XRF, developments in instrumentation continue to be reported. One area of performance that can cause limitations is the sensitivity to low-Z elements, mainly resulting from the attenuation of low energy X-rays in the air gap between sample surface and instrument. Migliori and colleagues123 further developed the helium flush approach and reported analytical performance data for a custom-designed instrument incorporating two X-ray tubes of different anodes applied to the characterisation of artefacts in the field of cultural heritage. In recent years, there has been interest, especially in space applications of combining XRF and XRD capabilities into a single instrument and this trend in terrestrial applications has been continued by Cuevas and Gravie.124 Their instrument combined in situ XRF with XRD in reflection mode using a single low-power X-ray tube and energy dispersive detector to measure the XRD spectrum at a fixed angle. They demonstrated the instrument's capabilities by reporting XRD results for a jadeite-jade mineral, bone samples of archaeological interest and paintings. Although not normally covered by this review, it is relevant to note the work of Hansford,125 who described a novel XRD technique that facilitates the development of a lightweight instrument suitable for field-portable or hand-held XRD combined with XRF analysis. This XRD approach was based on back reflection geometry with 2 theta similar or equal to 180 degrees, and offering almost complete insensitivity to the morphology of and distance to the sample. The author emphasised potential applications in geology and the planetary sciences. A further example of an in situ X-ray analytical study using a portable X-ray diffractometer incorporating XRF was described by Suzumura et al.126 who reported the laboratory and field analysis of iron oxides on the running surface of railway lines. They reported that different types of rust were generated under different environmental conditions and provided some important suggestions about understanding the effect of surface substances on the rolling interaction between wheel and rail.Portable XRF provides unique opportunities for the characterisation of extreme environments of which planetary surfaces is a prime example. In support of such investigations, Foing and colleagues127 described the field demonstration of astrobiological instrumentation and research methods conducted in and from the Mars Desert Research Station, Utah, USA as a Moon-Mars analogue environment. Of particular interest was the authors' discussion of the link between in situ and orbital remote sensing data, noting the contemporary use of portable XRF in both contexts. The authors focussed on a planetary exploration strategy involving a number of instrumental approaches, including XRF and XRD in a contribution designed to support the preparation of future space missions, especially to Mars. Nittler et al.128 reviewed XRF spectral data obtained from the Messenger spacecraft orbiting Mercury and reported that the planet's surface differed in composition from that of other terrestrial planets with relatively high Mg/Si and low Al/Si and Ca/Si ratios being incompatible with a feldspar-rich crust, as found on the Moon. These observations, together with high S and low surface Fe led the authors to suggest that Mercury formed from highly reduced precursor materials, perhaps related to enstatite chondrite meteors or anhydrous cometary dust particles. Remote XRF data was also recorded during the Chandrayaan-1 mission whilst orbiting the Moon during episodes of solar flares, as reported by Narendranath et al.129 The authors described analytical techniques including the derivation of X-ray line fluxes and their conversion to elemental abundances, and presented Al, Ca, Fe, Mg and Si data for the highland region on the southern nearside of the Moon. Their results were consistent with a composition rich in plagioclase with a slight enhancement in mafic minerals and a Ca/Al ratio that was lower than that in the Lunar return samples.
Space research can also be conducted on samples found on the surface of the Earth specifically by the analysis of meteorites as demonstrated by Zurfluh et al.,130 who applied hand-held instrumentation to well analysed meteorite powders, pressed pellets and hand specimens in the laboratory and tested instrumentation in the deserts of Oman, whilst searching for new samples. The main application of XRF instrumentation was for the identification and classification of meteorites, the quantification of terrestrial contamination (Ba and Sr) and for the detection of Mn-rich desert varnish. Schroder et al.131 described the miniaturisation of X-ray detectors (SDDs) that have enabled devices to be incorporated into instruments such as a field portable Mossbauer spectrometer. This was for the identification of iron phases on the Moon, Mars and beyond in which the SDD provides an additional capability for the determination of elemental compositions by XRF. Prinsloo et al.132 proposed that Marion Island in the South Indian Ocean was a possible terrestrial analogue for the geology on Mars. Their main interest was in the use of Raman spectroscopy to analyse igneous rocks and volcanic ash to identify the various iron-bearing phases, but XRF was used to evaluate the basic elemental content of three lavas. McHenry et al.133 considered that jarosite in a saline-alkaline paleolacustrine deposit of Pleistocene age in the Olduvai Gorge, Tanzania could have implications for the processes that led to the formation of this mineral on Mars. The authors used XRF as one of the techniques to analyse these samples and considered that this terrestrial occurrence had formed recently, perhaps due to the interaction of modern ground and meteoric water with paleolacustrine pyrite, causing its oxidation and the creation of temporary acidic conditions suitable for the formation of jarosite. Papike et al.134 used SRXRF and EPMA techniques to determine the Co, Cu, Ni and Se content of Martian and Lunar basalts and found that Co and Ni were higher in Martian sulfides than Lunar sulfides and in Martian olivine-bearing lithologies than olivine-free varieties. Results were interpreted as distinguishing different parent bodies for Lunar and Martian sulfides.
There are a number of innovative applications of hand-held XRF to report in this review. Apparently, Sr can be used as a marker for “corrosive drywall”, a phenomenon reported in North America whereby gases emitted as a result of the corrosion processes cause the corrosion of copper components within a building. Steiner135 described anon-site testing method for Sr that indicated populations of non-corrosive drywall with Sr contents both lower than and greater than that of an affected drywall. Additional research on this topic is described in section 3.8 Industrial applications. In another building-related application, Balasubramanian and colleagues136 used hand-held XRF to measure the Pb concentrations on various surfaces in pre-1950 built homes. XRF results from walls, floors and window sills, etc. were compared with results obtained from wipe samples and empirical relationships were developed to describe the migration of Pb from inner layers of surfaces with and without visible defects to provide assistance to surveyors in predicting lead migration to the surface from leaded paint. The use of portable X-ray equipment in addressing a threat of a different kind was reported by Iovea et al.137—that of the detection of explosives for bomb squad interventions. Instrumentation was capable of measuring in situ digital radiography images using a 2D dual-energy X-ray detector and portable X-ray source. By collecting X-ray intensities at two different energies, the mean atomic number of the material could be computed and compared with reference values from an explosives database. In the challenging underwater environment, Breen et al.138 reported the use of a miniaturised portable XRF instrument fitted to an autonomous underwater vehicle (AUV) and designed for the underwater mapping of the surface of sediments, providing information for the control system of the AUV to decide on future sampling locations.
There has been growing interest in the use of portable XRF systems to measure coating thickness, as exemplified by the work of Carapelle et al.,139 who emphasised the value of modern computers to control instrument functions and undertake processor intensive calculations and Gherase and Fleming63 who used a commercial portable X-ray spectrometer to verify the calculation of depth-dependent elemental concentrations using a layered calibration model. Measurements were made of four-layer stacks of polyester resin doped with different concentrations of As and was aimed at providing in vivo measurements of the As and Se concentration in human skin. Bonizzoni et al.140 reported the potential and limitations of portable XRF in the determination of pigment thickness exemplified by cold painted terracotta and wooden sculptures based on measurement of K and L line intensities.
2.8 On-line XRF
The under-reporting of on-line applications has been commented on in previous reviews, with limited work available again this year on which to comment. However, it is a delight to be able to report on the work of Hasan et al.141,142 on the on-line sorting of recovered wood waste using automated XRF technology to remove recycled wood products contaminated with wood treatment preservatives including chromated copper arsenate and alkaline copper quat. Their experimental instrumentation comprised an XRF detection chamber mounted on top of a conveyor with a side-way diverter which sorted wood into presumed treated and presumed untreated. Impressive figures were reported for the sorting efficiency of this device which achieved values of 75–92% by weight for treated wood and 68–96% by weight for untreated wood. Corresponding mass recoveries of As, Cr and Cu ranged from 75 to 99% and overall, the system achieved a recyclable portion that met residential soil quality levels for Florida, USA, that restricted an in-feed to 5% of treated wood.3. Applications
3.1 Sample preparation and preconcentration techniques
The fused bead technique has been used by many analysts over the years as an effective way to present approximately 1 g aliquots of sample to a spectrometer. Nakayama et al.143 described a fusion method for much smaller amounts of sample. They fused 11 mg of sample with 300 times the weight of Li2B4O7 to offer a calibration for the determination of major oxides (Al2O3, CaO, Fe2O3, K2O, MgO, MnO, Na2O, P2O5, SiO2 and TiO2) for archaeology and geochemistry studies where small samples are the norm. The calibration was prepared using chemical reagents (Al2O3, CaCO3, Fe2O3, K2CO3, MgO, MnO2, Na2CO3, Na4P2O7, SiO2 and TiO2) and offered acceptable lower limits of detection such as 0.3% m/m for Na2O, 0.5% m/m for MgO and 0.01% m/m for MnO. Wang et al.144 revisited the problem of dealing with samples that show a gain on ignition during fused bead preparation. They realised that the simple approach used by many analysts for some time of treating the gain as a negative loss on ignition in the calculation of theoretical influence coefficients works well. Verma et al.145 compared fused bead and pressed powder pellet preparation methods for the determination of Cr and Ni in geological samples using igneous and sedimentary reference materials. As expected, both preparation techniques gave consistent results at concentrations >50 μg g−1 with greater differences for lower concentration levels after assessment by both ordinary and weighted least squares linear regression models. Zivanovic146 reported the effect from mineralogical matrix differences on the quantitative XRF measurements of Al, Ca, K, Mg, Mn and Si in ferro-manganese slag. Whilst pulverised and fused-prepared slag showed a significant difference in microstructure, heterogeneity and mineralogy the author found little difference in the accuracy and reproducibility of the reported measurements. Other analytical techniques such as ICP-OES and classical gravimetric and titrimetric approaches were also used for checking the accuracy of the XRF calibration.Preparation methods for other sample types reported during this review period included Wang et al.147 who offered a method for the analysis of Fe, Mn, Ni and V in oil-based samples using emulsification technology for a water-in-oil calibration using a biodegradable surfactant, span80, as the emulsifier. Matrix corrections were applied by theoretical α-influence factors or use of an internal standard. Accuracy of the method was reported to be consistent with standard methods for the analysis of crude and fuel oil samples. James et al.148 compared preparation methods for the SRXRF analysis of brain tissue where quantitative imaging of trace metals with a high spatial resolution is increasingly used by biological researchers. The authors described the manufacture and characterisation of multi-element thin-film reference foils used in this method for two-dimensional mapping of trace metals in rat hippocampus. Workers in Brazil149 described a comparison between conventional EDXRF and SR-TXRF for the determination of Co in ruminal fluid from Holstein cattle as this element is used as a marker in animal nutritional studies. For the EDXRF analysis, 200 μl of sample were dried on 6.35 μm Mylar film at 60 °C. For the SR-TXRF, 10 μl of sample were pipetted on a Lecite carrier and also dried at 60 °C. Both techniques used gallium as an internal standard and a 200 s measurement time. The trueness of both techniques was evaluated by the standard addition method with recoveries reported for SR-TXRF and EDXRF as 76 and 99% and limit of detection, 13 and 240 μg L−1, respectively. Worley et al.150 addressed concerns common to many laboratory managers, namely, the reduction of both waste and costs and an improvement in process safety. Their method was related to the quantification of Ga in plutonium by WDXRF. The changes included reducing sample size, reducing ion-exchange process volumes, using cheaper reagent grade acids, eliminating the use of HF and using a more robust sample support film. Relative precision and accuracy achieved by analysing multiple aliquots from a single parent sample were approximately 0.2 and 0.1%, respectively. The same precision was reported by analysing a total of four parent samples and the average relative accuracy from all samples was 0.4%, which was within the protocol uncertainty requirements. Wang et al.151 described a method for the analysis of iron concentrates by gel sample preparation. The solution, digested by aqua regia was mixed with agarose, then dissolved in the boiling solution to form a quasi-solid gel at ambient temperature. The method was tested with iron concentrate CRMs and a relative standard deviation was reported of less than 0.3%.
A rapid and simple method was offered by Inui et al.152 for the determination of Crlll and CrVl in water using WDXRF after preconcentration with an ion-exchange resin disk. A 100 ml water sample was first adjusted to pH 3 with nitric acid and then passed through an anion-exchange resin disk placed on top of a cation-exchange resin disk at a flow rate of 1 ml per minute to separate Crlll and CrVl. Anionic CrVl was preconcentrated on the upper anionic disk whereas Crlll was preconcentrated on the lower cation disk. Each disk was then dried at 100 °C for 30 minutes in a laboratory oven and coated with a commercially available laminate film. Calibrations for both Cr species showed good linearity in the range 1–10 μg. The detection limits corresponding to three times the standard deviation of blank values were 0.17 μg for Crlll and 0.16 μg for CrVl. A spike test for 50 μg L−1 for both Cr species in tap water and river water showed quantitative recoveries of 94 to 114%. For mineral water, a correction was required for the overlap of V Kβ with Cr Kα to show a recovery of 115%. Zawisza and Sitko153 offered a method for the determination of Li (yes Li) in mineral water by XRF. As readers will appreciate, the direct determination of lithium by XRF is not possible due to its extremely low fluorescent yield and long wavelength radiation. However, a method was described for the determination of Li via iron after preconcentration with stoichiometric potassium lithium periodatoferrate(III) complex. The solution obtained after dissolving the complex was pipetted onto Mylar film for subsequent XRF analysis. As little as 1 μg Li might be determined by this method as the prepared samples were thin, rendering errors from self-absorption or matrix effects to be negligible. In recent years, liquid-phase micro-extraction has become one of the most valuable techniques for the preconcentration and separation of elements at trace and ultra-trace levels. This sample preparation method154 was combined with XRF since the incident X-ray beam may be focused on the small spot produced from 2–30 μL of sample deposited onto a membrane filter or Mylar film. Detection limits of 1.6, 2.8, 1.7, 4.1, 2.1 and 2.5 ng mL−1 were reported for Co, Fe, Ga, Pb, Se and Zn, respectively in water. Temerdashev et al.155 offered an XRF method using a thin-layer cellulose adsorbent bearing chemically immobilised thiosemicarbaside for the preconcentration of Cdll, Coll and Hgll in the concentrate.
3.2 Geological
Ten years or so ago, the XRF analysis of geological samples would have been dominated by classical geochemical studies. Now, however, a large proportion of such studies focus on evidence for climate and environmental change over geological time periods, with XRF usually contributing to a multi-technique approach and with XRF core scanning often the favoured approach. Typical of such investigations is the work of Tian et al.,156 who used non-destructive XRF core scanning to present a high resolution K/Al and Ti/Al record at Ocean Drilling Project site 1143 in the South China Sea over the past 5 Ma. Together with oxygen isotope data, their results demonstrated changes in weathering patterns associated with the East Asian summer monsoon over the late Pliocene and Pleistocene periods. Lauterbach et al.157 undertook a study of sediment from Lake Mondsee (northeastern Alps) using a new field sampling approach that offered resolutions at the decade to sub-annual level. Multi-technique data by μ-XRF scanning, carbon geochemistry, stable isotope measurements on ostracods (fossilised marine crustaceans), pollen analysis and microfacies analysis on large-scale thin sections provided the authors with data to demonstrate the environmental response to late glacial climate fluctuations. Lowemark and colleagues158 drew attention to discrepancies that can occur in XRF core scanning data from lake sediments due to variations in the organic content (which can range from a few to 50%). They proposed that Al could be used effectively to normalise XRF elemental data to avoid the problem that variations in elemental abundance would simply reflect variations in the organic content. Balascio et al.159 combined scanning XRF with magnetic susceptibility and data on the properties of bulk organic matter, molecular biomarkers and diatom assemblages to assess salinity and water column changes over the last 7800 years based on an analysis of sediments from Lake Heimerdalsvatnet in the Lofoten Islands, northern Norway and interpreted results in terms of changes in sea level. Vegetation was of interest to Olsen et al.160 with XRF and stable isotope measurements on three lake sediments on the Faroe islands elucidating the deglaciation history of the islands over the Holocene period. Sea surface conditions during the Late Holocene in two bay areas off the coast of Newfoundland were the subject of a study by Solignac et al.161 using core-scanning XRF. Results were related to movements of sea ice associated with the Labrador Current. Intensities from Ba, Ti and V in marine sediments by core scanning XRF, together with the oxygen isotope measurements in planktonic foraminifera and carbonate and organic carbon contents were used by Zhao et al.162 to reconstruct changes in discharges from the River Nile over the last 1.75 Ma. The authors concluded that oxidation of organic material played an important role in determining the organic carbon content of sapropels (dark-coloured sediments that are rich in organic matter) and that the carbonate content and normalised Ti and V values in bulk sediments reflected changes in Nile discharges (linked to the capability of the Nile to transport suspended matter) and variations in the African monsoon. XRF measurements giving a high resolution of 0.5 cm were combined with oxygen isotope and assemblage analysis to evaluate paleoceanographic conditions from 11 m of sediment retrieved off the Cape Verde islands in the Atlantic Ocean by Matsuzaki et al.163 Their results were used to interpret changes in sea surface temperatures over the last 220 ka along the north-western African margin. The focus of Aarnes et al.164 was on plant microfossils and pollen analysis, which together with scanning XRF was used to evaluate changes in vegetation in response to climate change during the last deglaciation period (13500–8000 years ago) in southwest Andoya, arctic Norway. The development of polar desert vegetation during this period was linked to the extent of sea ice. Ice cores from the Antarctic were analysed using XRF and Fe- and Ti-K edge XAS by Marcelli et al.165 to evaluate the mineral phase composition of dust trapped inside with a particular interest in evaluating the oxidation and coordination states of these elements. Giralt et al.166 presented a case study to reconstruct quantitatively the climate, based on meterological and limnological data and XRF core scanning data from Lake Sanabria, Northwest Spain. In contrast to many other similar studies, their work used very recent records since 1986 to evaluate relationships between climate, hydrology and lake dynamics as recorded in lake sediments. They concluded that the chemical composition of lake sediment was mainly controlled by sediment and nutrient delivered by input from the River Tera, that lake sediments act as a low band-pass filter, smoothing variations in the climate signal, but that it is possible to undertake accurate climate reconstructions from non-laminated sediments.
Other climate change studies that made use of XRF data include a novel approach by Vasskog et al.167 who used Rb/Sr ratios to show the impact of snow avalanches and flooding over the last 7300 years during the Holocene period based on an analysis of lacustrine sediments in Oldevatnet, western Norway. Their data suggested that the record was dominated by snow avalanches with the largest activity occurring during the ‘little Ice Age’. Van der Land and colleagues168 combined magnetic susceptibility with XRF data (specifically for Fe and Ti) for three piston core samples from the summits of coral-topped carbonate mounds in the margin of the Southwest Rockall Trough to show that sediments had undergone significant post-depositional modification that had affected both the geochemical signal and the mineralogical composition. Specifically, a lithification sequence was identified, involving dissolution of aragonite and the precipitation of low-magnesium calcite, and the dissolution of magnetite with the enrichment of iron and manganese. A combination of SRXRF together with XRD, IR and SEM were the techniques of choice of Moroz et al.169 to characterise the major and minor element composition of nontornites (high iron minerals of the smectite group) found in the sea of Okhotsk, Siberia. Post-volcanic sediments could be distinguished on the basis of the Fe/(Fe + Al + Mg) ratio and Cu, Ni, Pb, Rb, Sb, Sn and Y contents. The clastic sediments of the Mugnano Cave in the Siena district of the Northern Apennines, Italy, were studied by Martini170 using XRF and XRD. Results were interpreted to hypothesise on the processes that led to the formation of the cave, involving the local disintegration of the bedrock, production and deposition of the sediments in a subterranean lake and the removal of these sediments by erosion. XRF and XRD were used by Guo et al.171 to show that black shales of the Lower Silurian Longmaxi formation, Southeast of Chongqing, China, were deposited primarily in deep water and variations in composition were linked to changes in sea level during this period. Mineral analysis indicated that the deposit was similar to the US Ohio shale, indicating a significant potential for shale gas production.
XRF continues to be used in a large number of more conventional geochemical studies. The papers selected for review here demonstrate innovations in the development or application of technique rather than reflect the full scale of the more routine use of the technique. Likely to be of interest to all workers in this field is a simple software tool developed by Buttner172 that computes bulk rock compositions from the mixing or unmixing of rocks of minerals to describe processes such as magma mixing, fractional crystallisation, assimilation, residual melt extraction or the formation of solid solutions – all geological processes to which a contribution can be made from XRF data. In terms of developing techniques for geochemical studies, Kon et al.173 at the Geological Survey of Japan (GSJ), applied the femtosecond LA-ICP technique to the analysis of GSJ reference materials prepared as XRF glass discs and claimed improved reliability in the determination of a comprehensive list of major and trace elements. The innovations reported by the authors included the use of a femtosecond laser to minimise element fractionation during ablation, new software to control laser/stage movement and the timing of the acquisition of data, and a new design of sample cell to enhance transport efficiency of ablated material to the plasma. For an analysis time of 100 s, precisions in the range 10 to 30% were reported for the major elements and a comprehensive range of trace elements. X-ray micro-computer tomography can be used to visualise interior detail, for example of a granite, that is inaccessible by other techniques, as demonstrated by Boone et al.174 The authors were able to combine density information obtained by μ-CT with μ-SRXRF and μ-SRXRD measurements to construct 3D phase images of a heterogeneous Precambrian granite as confirmed by using more traditional thin section petrography. Wang et al.175 undertook an evaluation of uncertainty in the determination of Rb, Sr, Y and Zr by polarised EDXRF in geological samples prepared as polyethylene-backed pellets. Fan and Gerson176 applied more specialised X-ray techniques to elucidate the nickel geochemistry of laterite ores from the Philippines in which nickel was heterogeneously distributed on a micrometre scale. Thus, in addition to bulk determinations by SRXRF, a range of other μ-X-ray techniques (μ-SRXRF, μ-EXAFS, μ-XANES and μ-XRD) were used to elucidate the Ni mineral associations. The biogeochemistry of manganese in a ferruginous lake, Lake Matano in Indonesia, was described by Jones et al.177 using SRXRF and X-ray spectroscopy in which the product of biologically catalysed Mn oxidation was birnessite. Analysis of extractions from sinking particles and modelling of transport reactions indicated that the kinetics of Mn reduction in the lake's reducing waters were sufficiently rapid to preclude the deposition of Mn oxides from the water column into sediments underlying the ferruginous lake water. This observation had direct relevance to an understanding of Mn geochemistry in the sedimentary record. Garcon et al.178 used μ-XRF mapping to analyse beach placer deposits that concentrate detrital heavy minerals, which result from erosion over a large area of continental crust and where the Nd and Hf isotopic ratios may represent the average composition of a large continental area. The authors studied both bulk and mineral separate samples from the Camargue, France and showed that monazite controls the Nd isotopic composition and zircon the Hf isotopes, despite these mineral representing only 3.5 and 10% respectively of the heavy mineral assemblage. The geological implications of these results were presented in terms of the events that created the Alps and the Massif Central which resulted in extended areas of the crust drained by the river Rhône. The origin of high Zn contents of the Jurassic limestone of the Jura Mountains and the Burgundy (western Europe) was reported by Jacquat et al.179 Using μ-SRXRF and XANES the authors identified sphalerite and Zn-substituted goethite and a minor fraction of Zn-bearing carbonates in limestones of Bajocian age and Zn-substituted calcite and hydrozincite in Oxfordian samples. They considered these results indicated a hydrothermal origin for Zn with differences related to rock permeability and/or hydrothermal events. The μ-XRF technique was used by Genna et al.180 for the in situ determination of the major elements on a 1.7 × 1.3 mm2 window in thin sections from a massive sulfide deposit related to hydrothermal alteration in the Cap d'Ours section of the Glenwood rhyolite, Rouyn-Noranda, Quebec, Canada. Two styles of alteration zoning were identified related to either sea-water at the lava-water interface at temperatures above 400 °C and lower temperature (<300 °C) hydrothermal mineralisation. Weathering indices could be used to quantify the condition of fresh volcanic ash and evaluate its fertility, to provide a better understanding of element mobility during weathering and to predict the source of soil nutrients. Fiantis et al.181 measured these parameters and the trace element content using wet chemical and XRF methods for new volcanic ash deposits from Mt Talang, West Sumatra, Indonesia originating from an eruption in April 2005. Geochemical studies of silicate rocks based on a microanalytical approach depend on the availability of well characterised microanalysis reference materials. XRF was one of a number of techniques contributing to the characterisation of four ‘Chinese Geological Standard Glasses’, as described by Hu et al.,182 who reported preliminary reference and information values for 55 elements. Grafe et al.183 described quantitative evaluation of mineralogy by scanning electron microscopy coupled with μ-XRD, μ-XRF, and μ-XANES spectroscopy to determine mineralogical associations and chemical speciation of trace metals. The authors sought to define the mineralogical environment of a bauxite residue core segment with the more specific aim of determining the speciation of trace metals (e.g., Cr, Mn, Ti, and V) within the mineral matrix.
During the current review period, XRF made a number of contributions to the mining and mineral exploration industries. One example involved the use of hand-held XRF by Gazley et al.184 to illustrate the geochemical stratigraphy of individual lava flows at Plutonic Gold Mine, Western Australia, which consisted of gold-mineralised metabasalts of Archaean age. When combined with Au assay data, the XRF results showed that gold was deposited along basalt flow boundaries. This observation was not readily apparent at the macroscopic level and has clear relevance to an understanding of the stratigraphic controls on other types of deposit worldwide. Reith et al.185 reported the distribution and speciation of gold in biogenic and abiogenic calcium carbonates in the Barns gold prospect, South Australia. The distribution of Au, Ca, Zn and other metals was mapped using μ-SRXRF in calcium carbonate samples precipitated by active bacterial cultures. The μ-XANES technique was used to show that metallic Au hotspots in calcium carbonate were surrounded by ionic Au, resembling those found in natural calcrete, which was not the case when precipitation occurred in the presence of dead bacteria or by raising the pH or pCO2 of solutions. The authors concluded that microbial processes that combine biogenic calcium carbonatogenesis with gold precipitation were likely to cause the formation of gold-anomalous calcrete. Figueroa-Cisterna et al.186 used multivariate statistical methods based on ‘ex situ’ portable XRF data to classify rock types in the Boris Angelo area of Central Chile in support of a drill hole survey undertaken to evaluate the economic potential of a copper deposit. Effective studies of mining and mineral deposit samples depend on the availability of well-characterised reference materials and Wang et al.187 described two cobalt-rich seamount crust platinum group element (PGE) reference materials (MCPt-1 and MCPt-2) produced by the Institute of Geophysical and Geochemical Exploration, Langfang, China. One feature of these samples was the use of a milling technique that produced an ultra-fine particle size distribution to eliminate or minimise the well-known nugget effect. Both XRF and EPMA were used in an assessment of homogeneity and certified/reference/information values were reported following analysis by ICP-MS, ICP-AES and XRF. Haavisto and Hyotyniemi188 described the design and performance of a prototype measuring device for the monitoring and control of mineral flotation. The device was used to monitor chalcopyrite and sphalerite slurries and was based on low cost visible and near IR imaging spectrography combined with traditional XRF analysis to reduce significantly the sampling interval for elemental analysis.
The environmental contamination from mining and natural sources was the subject of a range of studies over the current review period. Arsenic is a serious contaminant in the world-class borate deposits in Turkey and California, adversely effecting local water supplies and commercial boron products. Lin et al.189 used ICP-MS and μ-SRXRF to reveal that colemanite contained up to 125 μg g−1 As and μ-EXAFS demonstrated the substitution of both As5+ and As3+ in the crystal lattice with the authors concluding that colemanite was the main source of As contamination in both boron products and aquifers associated with boron deposits. Safe aquifers in areas of high arsenic is a well-known problem in Bangladesh and Tauhid-Ur-Rahman and colleagues190 used a range of spectroscopic techniques (SEM, TEM, XRD, XRF) to investigate the sorption and mobility of arsenic at the sediment-ground water interface in the Holocene deposits of south western Bangladesh. Their results indicated that the upper shallow aquifer (18 m depth) was composed mainly of fine, grey, reduced sand and produced highly enriched As levels in ground water, whereas deeper sediments, composed partially of oxidised, brownish, medium sand containing natural absorbents such as iron and aluminium oxides imparted low arsenic concentrations to the water. An analysis and modelling of results by the authors indicated that arsenic could be immobilised and prevented from reaching the deeper aquifer by a natural filter of oxidising sand and absorbent iron and aluminium oxides producing an adequate supply of sustainable safe water in the deeper aquifer. Further examples of arsenic speciation can be found in the environment forensics section of this review. High fluoride in groundwater is a problem of the Unnao district of Uttar Pradesh, India and a detailed analysis of alluvial sediments was undertaken by Kumar and Saxena191 using XRF to determine the major elements and 24 trace elements. The authors suggested that elevated levels of fluorine in ground water were associated with the effect of weathering causing the dissociation/alteration of mica minerals, especially biotite. Mitsunobu et al.192 reported that soil near tailings from an antimony mine contained micro-grains coated with an antimony-rich layer, which was characterised using μ-EXAFS, μ-XRD, TEM and EPMA. Their analysis indicated the presence of nanocrystalline tripuhyite (ferric antimonate), the first such report in natural soil to date. Synchrotron-based techniques (μ-XRF, μ-XRD, μ-XAS) were used by Carbone et al.193 to study iron-rich hardpans within a waste rock dump at the Libiola mine, eastern Liguria, Italy. The heterogeneous assemblages of iron-bearing precipitates that had formed as a result of an iron-copper oxidation processes in the dump were found to contain significant amounts of hazardous elements such as As, Cu, Mo, Se, Zn. Goethite-rich assemblages showing a particular affinity for Cu and Zn, whereas hematite-rich material selectively concentrated As, Cu, Mo, Se, Zn. Odumo et al.194 used EDXRF to assess the environmental impact of heavy metals from gold mining activities in the Migori gold belt of south western Nyanza, Kenya, and reported that the average concentration of As, Pb, Ti and Zn exceeded the WHO limits of 50 mg kg−1. Boes and colleagues195 noted that when investigating lake sediments for their history of heavy metal pollution, it had become normal to calculate enrichment factors by normalising elemental distributions against a reference lithogenic element. However, their studies by XRF of the elemental composition of commonly used reference elements (Al, Rb, Ti, Zr) in frozen cores collected from Lake Nylandssjon in northern Sweden led them to recommend the use of multiple reference elements as this gave a more reliable interpretation of the impact of anthropogenic as opposed to geogenic inputs. Wildman et al.196 were interested in the effect of drought on chemical changes in sediments at Lake Powell, USA using laser diffractometry, XRF and XRD to characterise the sediment from the input region and some shore locations. They found that solid phase iron, rather than particle size or organic carbon content was the best predictor of variations in the element and mineral concentrations of sediments. An interesting 2 part study published by Baines et al.197,198 dealt with the causes and biogeochemical implications of regional differences in silicification of marine diatoms exposed to additions of silicic acid and iron. Using a cell-specific technique of SRXRF microscopy, the authors showed that diatom cells in the cold, high-silicic-acid waters of the Antarctic zone of the Southern Ocean had 6 times more silicon per volume than those inhabiting the warm, low-silicic-acid waters of the eastern equatorial Pacific. The difference between the excess densities of diatoms and non-diatoms was 15-fold greater in the Antarctic waters than in the eastern equatorial Pacific. The authors suggested that ecological processes might cause much larger systematic regional and temporal differences in cellular stoichiometry than is currently accommodated by ecosystem models. This study revealed how the cellular Fe, P, Si and S contents of natural diatoms respond to additions of Fe and Si in the eastern equatorial Pacific, a major natural source of CO2 to the atmosphere.
As society seeks to exploit more marginal deposits of fossil fuels, pollution and the fate of contaminants continues to be a topical issue. Thus, Binner et al.199 investigated the effect of drying on the behaviour of inorganic species during the pyrolysis and combustion of brown coal from Victoria, Australia, using XRF, XPS and SEM to analyse char and ashes from both wet and dry coal. Char contained Cl, Mg and Na and low concentrations of excluded minerals and small differences were noted depending on combustion temperature, although the rate of pyrolysis was found to be similar for wet and dry coal. Neutron activation analysis was used with XRF by Arbuzov et al.200 to characterise the geochemistry of Th and U in coal and peat from Siberia, the Russian Far East, Kazakhstan and Mongolia and the highest concentrations were reported to be in coal associated with blocks of rock within basins, or coal formed during a period of volcanism. The interest of Yang et al.201 was in the REE geochemistry and depositional environment of a silver–vanadium deposit hosted in a black shale, using ICP-MS and XRF to provide data that was interpreted as demonstrating formation during a period of hot water sedimentation, mostly involving terrigenous material. Oil shale contains a proportionally large amount of kerogen which can be converted to oil by thermal degradation of the compacted rock leaving semicoke as a by-product. Datangel and Goldfarb202 investigated the environmental impact following the disposal of this waste by-product to land fill and used XRF to determine the heavy metal content of samples resulting from the pyrolysis of oil shale at 500 and 1000 °C. They found that the main hazard arose from the As content of semicoke with other elements (Ba, Cu, Fe, Mn, Pb) being well below the US EPA regional screening limits. Doyle et al.203 developed EDXRF for the determination of Cl in crude oil to a lower level than was approved by the relevant ASTM standard using a simple calibration strategy based on diluting an aqueous solution of sodium chloride with glycerine. They claimed their method gave a linear response over the range 8 to at least 100 μg g−1 Cl. An interesting study was undertaken by Goncalves et al.204 who used EPR (electron paramagnetic resonance), XRF and NMR to investigate the recent claim that magnetic fields can reduce the crystallisation of paraffin and the viscosity of some types of oil. They found that one of six Brazilian crude oil samples showed a reduction in viscosity when exposed to a large magnetic field but the others did not. Based on data obtained from the cited techniques, the authors considered that the affected sample was distinguished by the presence of the paramagnetic Mn2+ ion, the highest aromatic/aliphatic molecular ratio and the highest water content indicating that the effect of magnetic fields on rheological properties was not as universal as some authors had claimed. Shimobayashi et al.205 used XRD, SEM, XRF and CHN analysis to report the first occurrence of four ammonium sulfate minerals in Japan (Mikasa City, Hokkaido). These unusual minerals (boussingaultite, godovikovite, sfremovite and tschermigite) were associated with a coal gas escape fracture.
3.3 Industrial minerals
Many of this year's contributions on industrial minerals cover the properties and uses of clay minerals, often with XRF as part of a multi-technique approach. However, a WDXRF-focussed contribution was made by Gazulla et al.,206 who reported a method for the direct control of the chemical composition of clay slurries used to prepare the bodies of ceramic floor and wall tiles. Their method was designed to avoid the need to prepare fused disc or pellet samples by the analysis of slurry samples in specially designed plastic holders and they reported that slurry viscosity and suspension solid content did not appreciably affect the WDXRF results, although the type of tile body composition did. Persistent environmental contamination from 137Cs is a well-known problem associated with nuclear accidents and Bayulken et al.207 used EDXRF to analyse the major and minor elements in various clays from Turkey to investigate the absorption properties required for an effective barrier material. They concluded that Cs absorption occurred essentially by ion exchange and partly by specific absorption mechanisms and that bentonite and zeolite were the most effective of the clays tested in hindering the expansion of a Cs radioisotope contamination plume. Orosco et al.208 used a range of techniques, including XRF to study the effect of chlorine on different refractory clays within a wide temperature range, and the XRF analyses of residues after treatment indicated that iron might be entirely removed by chlorination above 900 °C. A number of techniques (XRF, XRD, FTIR and specific surface analysis) were used by Arus et al.209 to characterise anionic clays, with a particular emphasis on optimising the Mg/Al ratio, for use as kinetic modifiers in lactic fermentation. Kaolin from the Capim River Region, Brazil, was analysed by dos Santos et al.210 using XRF and brightness measurements to demonstrate that samples from this deposit are characterised by low iron and high brightness and these and other measurements were used to optimise the benefaction of this mineral for industrial use. Tehrani-Bagha et al.211 studied the sorption of cationic dyes onto kaolin with a particular interest in the removal of basic yellow, methylene blue and malachite green onto Persian kaolin, using a multi-technique approach that included XRF. They concluded that dye absorption onto kaolin is a spontaneous, endothermic and physical process. The interest of Caglayan and Otman212 was to optimise the activation conditions for locally available clays (from Ordu, Turkey) for the bleaching of cotton seed oil using XRF and a number of other techniques. Acid activation, cation treatment and thermal activation were investigated with sulfuric acid activation being more effective than hydrochloric. XRF and XRD were used by Bondar et al.213 to evaluate the effect of heat treatment on the reactivity of natural pozzolans, activated and condensed with sodium silicate in an alkaline environment. Their results showed that pozzolans containing sodium zeolite clinoptilolite could be used to prepare a moderate-to-high strength binder by heat treatment and that calcination could cause the formation of disordered hornblende as a constituent of pozzalan with no amorphous phase, to prepare a binder of moderate strength. XRF and XRD were also the techniques chosen by Meseguer et al.214 to investigate the ceramic behaviour of four kaolin deposits from the Cauquenes Province of Chile, whilst Ngun et al.215 undertook a similar study of clays from central Cambodia. The first study demonstrated the adaptability for a dry pressing ceramic process whilst in the second, for the production of structural ceramics. Casting the net wider than just clay materials, Halim et al.216 used XRF, XRD and SEM to analyse ore and reduced samples of manganese ores to investigate the increase in efficiency in the ferromanganese industry that resulted from the pre-reduction of manganese ores using solid carbon. They concluded that at the optimum reduction temperature (1000 °C), solid state diffusion plays a significant role in the reduction of MnO2 to MnO. A similar range of techniques (with the addition of optical microscopy and EPMA) was used by de Oliveira et al.217 to demonstrate the mineralogical, micromorphological and geochemical transformations that occur during the bauxitisation of anorthosite from the Barro Alto Stratiform Complex in Central Brazil. The authors provided a detailed description of the mineral changes that occurred as this weathering process progressed.Polarised EDXRF was used by Yamasaki et al.218 to determine an extended range of trace elements in soils and sediments using the pressed powder sample preparation technique, calibration using 26 reference materials and the Compton scatter matrix correction procedure. Extensive comparisons were made with conventional wet chemical methods and favourable agreement was obtained for Ba, Ce, Cs, Cu, La, Nb, Nd, Ni, Rb, Sr and Zn. Poor agreement for the elements Cr, Sn and Zr was attributed to incomplete dissolution and/or volatile losses during those wet chemical procedures that involved acid attack (and indicating that the XRF method was superior). EDXRF discrepancies in the determination of Co were caused by Fe Kβ line overlap and although EDXRF comparisons of Pr, Th, V and Y with wet chemical data were not as good, measurements were still considered to be of practical use. Vott et al.219 were interested in characterising multiple tsunami events during the Holocene period in the Bay of Palairos-Pogonia, Akarnania, Northwest Greece. Evidence was acquired by drilling cores and by the use of geophysical and geochemical methods, including the determination of Ca/Fe ratios by XRF to trace the impact of the tsunami inland. The authors were able to date strong tsunami events and concluded that on a regional scale, these events reoccurred at a time interval of 500–1000 years.
3.4 Environmental
Advanced X-ray techniques such as μ-SRXRF, μ-XANES and μ-PIXE offer chemical imaging to researchers interested in spatial distribution and speciation of elements within plants. Roschzttardtz et al.220 investigated the dynamics of Fe distribution in subcellular locations within pea (Pisum sativum). Elemental mapping with μ-PIXE revealed the unexpected presence of Fe in the nucleus and μ-SRXRF measurements on cryo-sectioned samples confirmed the Fe concentration in the nucleus to be higher than the expected Fe-rich plastids and vacuoles. Furthermore, the iron was found to accumulate in a sub-compartment identified as the nucleolus as it was shown to transiently disassemble during cell division. This work introduced a novel cellular function for iron related to actively dividing plant tissue. Regvar et al.221 also recognised that high spatial resolution offered by synchrotron imaging techniques was valuable in gaining new insights into the complexity of biochemical composition, morphology and the structural characteristics in protein storage vacuoles in the wheat aleurone. They reported subcellular distributions of Al, Fe, Mg, Na, P, Si and Zn from direct imaging methods that revealed the importance of globoids with phytic acid mineral salts and walls as preferential storage structures. The Si distribution was atypical, being contained in the aleurone apoplast and symplast, supporting a physiological role for Si in addition to its structural function. Frommer et al.222 reported spatial distribution and speciation of As, Fe and Mn around rice roots grown in an As-affected paddy field in Bangladesh. The authors used μ-SRXRF on soil thin sections to show that roots influenced soil As, Fe and Mn distribution up to 1 mm away from the root–soil interface. Thick roots, with a diameter ∼500 μm, showed Mn enrichment close to the root surface without associated As whereas concentric Fe accumulations formed further away were closely correlated to As. In contrast, thin roots (diameter <100 μm) showed As and Fe enrichment next to the root surface and no Mn enrichment. XAFS suggested that the distinct enrichment patterns were related to oxygen release from the primary and lateral rice roots and the kinetics of As, Fe and Mn redox transformations. Strategies to reduce As in rice grain, below concentrations that represent a threat to human health, require an understanding of As accumulation within the grain. Carey et al.223 studied phloem transport of As species from flag leaf to grain using μ-SRXRF. Dimethylarsinic acid (DMA) and monomethylarsonic acid (MMA) were found to be efficiently transported from flag leaves to rice grain; arsenate was poorly translocated and found to be rapidly reduced to arsenite within flag leaves whilst arsenite displayed no movement. Within grains, DMA was found to rapidly disperse while MMA and inorganic As remained close to the entry point. Johnson et al.224 recognised that the commonly consumed polished grain rice contains insufficient levels of key micronutrients, Fe, Zn and vitamin A to meet advised daily dietary requirements. Many breeding programmes have failed to achieve the recommended 14.5 μg g−1 Fe in the endosperm for those consuming a rice-based diet. The authors used SRXRF to investigate three populations of rice generated to constructively over-express the “OsNAS” gene family to show potential for Fe and Zn bio-fortification of rice endosperm that could provide a sustainable and genetically simple solution to Fe and Zn deficiency disorders affecting many people. Kopittke et al.225 reported in situ distribution and speciation of Cu, Ni and Zn in hydrated roots of cowpea (Vigna unguiculata) exposed to the analytes of interest for 1–24 h. After 24 h exposure, μ-SRXRF and XAFS confirmed that Cu was bound to polygalacturonic acid of the rhizodermis and outer cortex. When exposed to Zn, cortial concentrations remained comparatively low with much of the Zn accumulated in the meristematic region and moving into the stele. Approximately 60% to 85% of total Zn was stored as zinc phytate within 3 h of exposure. Nickel concentrations were reported to be high in the cortex and meristem whereas concentrations in the stele were comparatively low. Yu et al.226 also used μ-SRXRF to map the influence of mycorrhizal inoculation on the accumulation and speciation of Se in maize grown in selenite (SelV) and selenate (SeVl) spiked soils. The fungi were found to inhibit the translocation of Se from the surface of inner roots when SelV was added to the soil. Similarly, Yamaguchi et al.227 studied root-to-shoot translocation of Cd, Fe and Zn in Solanum melongena, Tian et al.228 reported cellular sequestration of Cd in the hyperaccumulator plant species Sedum alfredii and Carrasco-Gil et al.229 followed Hg transport within alfalfa, barley and maize. These studies have shown that 3D μ-SRXRF imaging is a powerful technique to assist in the understanding of potential transport mechanisms within plant tissues. Nakai et al.230 used 2D SRXRF imaging to assess Cs accumulated in vegetables affected by the nuclear accident in Fukushima, Japan.The impact of nano-particles on biological systems, especially plants is still not fully understood. Hernandez-Viezcas et al.231 reported the effects of ZnO nano-particles on a desert plant, velvet mesquite. Mesquite seedlings were grown for 15 days in hydroponics with 10 nm ZnO particles at concentrations varying from 500 to 4000 mg L−1. Zinc concentrations in roots, stems and leaves were determined by ICP-OES with biotransformation of ZnO and Zn distribution in tissues determined by XANES and μ-XRF respectively. The XANES spectra showed that ZnO nano-particles were not present in mesquite tissue, while Zn was found as Znll, resembling the spectra of Zn(NO3)2. The μ-XRF analysis confirmed the presence of Zn in the vascular system of roots and leaves in treated plants. Dumlupinar et al.232 reported the effects of mammalian sex hormones (progesterone, β-estradiol and androsterone) on changes in the inorganic elemental content of barley leaves. Solutions with hormone concentrations from 10−4 to 10−15 mol L−1 were sprayed on 7 day old plants that were harvested after 18 days. Conventional WDXRF was used to show increased concentrations of Al, Ca, Cl, Cu, Fe, K, Mg, Mn, P, S and Zn and a decrease in Na in the barley leaves with maximum changes obtained at 10−9 mol L−1 for plant leaves treated with progesterone, and 10−6 mol L−1 for those treated with β-estradiol and androsterone.
In Turkey, two studies were conducted using WDXRF to compare elemental concentration of a number of elements in hazelnuts233 and figs234 grown under organic and conventional farming regimes. Data from the hazelnuts was assessed using a statistical package for social sciences to show higher concentrations of Br, Ca, Cl, F, Fe, K, Na, Mg, Mn, P, Rb, Se and Zn in samples grown organically. Samples grown under conventional farming principles were reported to contain higher levels of potentially harmful metals Al, Cr and Ni. Similarly, the second study revealed that organic figs were likely to contain higher nutritional minerals. A group in Hungary235 investigated cucumber plants grown in hydroponics containing different chelated iron supplies, FelllEDTA and Felll citrate containing 10 μmol L−1 Cdll, Nill and Pbll. The extent of Cd, Ni and Pb accumulation and distribution were determined by TXRF. The accumulation of Ni and Pb was reported to be higher by about 20% and 100% respectively, if the iron supply was Felll citrate whereas Cd was similar in plants grown by both regimes. The amounts of Fe transported from root towards the shoot of the control and heavy-metal-treated plants were independent of the Felll feed. Matasin et al.236 reported Cr, Cu, Fe, Mn, Pb and Zn levels in different organs (liver, kidney, intestine spleen, skin and muscle) of grass carp and bighead carp reared on a fish farm in the Republic of Croatia. Similarly, Aich et al.237 studied the same analytes in Indian major carp species from waste-water fish ponds in East Calcutta wetlands. Sabatini et al.238 used TXRF to measure Cu in filter-feeding freshwater mussel as an indicator of oxidative stress effects and histological alterations during a 6 week regime of feeding on green algae that had been previously exposed to copper. A maximum Cu accumulation of 0.49 μg g−1 was measured in the mussel at week 6.
During this review period, two papers reported the assessment of willow as a bio-accumulator. Zimmer et al.239 sampled willow roots during a phyto-remediation trial in the contaminated flood-plane of the river Elbe in Germany. After freeze-drying; cross-sections were mapped for the distribution of As, Ca, Cu, Fe, K, Mn, Ni, S and Zn by SRXRF. The elements Ca, Cu, Ni, S and Zn were reported to be concentrated in the aerenchymatic tissue, and not associated with As, Fe and Mn found in plaque that covered the surface of the roots. The results suggest that willows are especially suited for the stabilisation of As and Cu thereby offering short rotation coppicing of willows as a practical approach for the mitigation of adverse flood-plain soil contamination. A Japanese group240 also recognised the high biomass of willow as an efficient heavy metal accumulator. Two-dimensional metal distribution maps from segments of young stems were obtained by μ-SRXRF with an approximately 2 μm2 X-ray beam to show the location of Cd in the apoplastic region. Following μ-XANES analysis, this apoplastic detoxification was thought to depend on cadmium–oxygen rather than cadmium–sulfur interaction. Metal concentration in the leaves of the willow was compared with that in the soil and enrichment factors were calculated for Cd, Cu, Pb and Zn. Stewart et al.241 identified specific organs within termites that host elevated metals and therefore play an important role in the regulation and transfer of contaminants back into the environment. High resolution PIXE mapping of whole termites and ED-SEM spot analysis showed localised accumulations of Mn and Zn in the mandible tips that were associated with increased hardness whereas Ca, K, Mg, P and Zn were accumulated in Malpighian tubules. Wannaz et al.242 reported the accumulation ability of the aerophyte Tillandsia capillaris. Leaves of the aerophyte were exposed to different metallic solutions of Cu2+, Ni2+, Pb2+ and Zn2+ cations. The cations of interest were measured using SR-TXRF to correlate their different toxic effects even in the most dilute solutions used in this study.
Studies of contamination in soils continue to feature in the literature reflecting the range of X-ray techniques available. Weindorf et al.243 used a portable XRF with global positioning technology to evaluate the environmental quality of sugarcane fields near to two industrial complexes in Louisiana, USA. With on-site measurements made in a matter of minutes, heavy metal contamination was reported proving the hand-held instrument to be an effective tool. Takeda et al.244 collected soil samples for analysis back in the laboratory. Pressed pellets of powdered soils were analysed by polarised EDXRF, calibrated with reference samples previously analysed by ICP-MS after pyrohydrolysis preparation. Calibration curves for Br and I K spectra were obtained in the concentration ranges 3.8–223 mg kg−1 and 0.91–54 mg kg−1, respectively. Repeated analyses within 1 day and after 1.5 years showed good reproducibility of the measured data. The lower limit of detection for Br and I were 0.14 mg kg−1 and 0.34 mg kg−1, respectively. The method was also suitable for the routine analysis of other elements such as Ba, Cd, Cs, Nb, Rb, Sb, Sn, Sr, Pb, Y and Zr measured under similar protocols. Sampling in a more challenging environment, Guerra et al.245 reported heavy metal contamination in century-old anthropogenic soils (technosols) from Hope Bay in the Antarctic peninsula. A former penguin rookery had been subjected to human disturbance following local explorations since 1903. Concentrations of Cd, Cu, Pb and Zn were reported to reach 47, 2082, 19381 and 5225 mg kg−1, respectively. Enrichment factors were calculated using Zr as reference element qualifying the site as extremely polluted. Shimamoto et al.246 reported speciation of iodine in a soil/water system in Chiba, Japan. Iodine speciation was determined by K-edge XANES in the soil at depths of 0–12 cm whilst HPLC-ICP-MS investigated the pore water collected at depths 0–6 cm. The water contained 50–60% m/v organic iodine bound to dissolved organic matter with the remainder reported as I−. In contrast, the XANES data showed the iodine in soils existed as organic iodine. Mapping of soil grains by XRF also indicated that the iodine was bound to organic matter. The enzyme laccase, which has the ability to oxidise I− to I2 was reported to be high at the surface of the soil water layer, suggesting that iodine oxidising enzymes may promote iodine transformation from inorganic to the organic state. Degryse et al.247 used Zn K-edge XAFS to assess soils that had been contaminated by runoff water from 17–74 year-old galvanised power-line towers. The zinc was identified as precipitates in the forms of phyllosilicates, zinc-layered double hydroxide or zinc in hydroxyl-interlayered minerals which contradicted the concept of precipitation control by a single phase. Other speciation studies included μ-SRXRF maps248 of arsenic in soil adjacent to chromated copper arsenate-treated fence posts and cadmium XAFS spectra249 from alkaline paddy soil under various flooding and drainage conditions.
Bromine was historically termed a cyclic salt in terrestrial freshwater environments due to its perceived conservative cycling between the oceans and the continents. This assumption was challenged by Gilfedder et al.250 with evidence that Br is involved in dynamic chemical cycles in soils and freshwaters. Water samples from all major and some minor inflows and outflows of Lake Constance, Germany collected over one year were analysed by ICP-MS and IC-ICP-MS. Sediment traps were deployed at two locations for two years for subsequent measurement by μ-XRF. Some 190 t per year of total dissolved bromine is fed into the lake via 14 rivers and precipitation with the rivers Alpenrhein and Schussen providing the largest sources from soils and rocks. Most of the bromine in the sediment traps was found to be bound to organic matter and showed a clear seasonal pattern in concentrations with a maximum in winter and minimum in summer. Gerke et al.251 used μ-SRXRF mapping and μ-XANES for the speciation and distribution of V in drinking water iron pipe corrosion by-products. Concentrations of V by bulk XRF analysis ranged from 35 to 899 mg kg−1 whereas the synchrotron data showed discrete grains of vanadium present as Pb5 (V5O4)3Cl embedded in the surface regions of iron corrosion by-products. The authors calculated that even in corroded iron pipes with a low V concentration of 100 mg kg−1, as little as 0.0027% of the 0.1 cm thick by 100 cm long corroded section would need to be disturbed to increase V concentrations in the drinking water at the tap to levels above the 15 μg L−1 notification for the State of California and thereby impact human health. It is thought that there is potential for V contamination from the network of unlined cast iron mains and service branches in American water distribution systems.
3.5 Aerosols and particles
The μ-SRXRF theme continues in this section of the review as more analysts recognise the technique's ability to provide information on particles at the micrometre and submicrometre scale coupled with its non-destructive nature and the benefit of little or no sample pre-treatment. Cozzi et al.252 used the ID-21 beamline at ESRF (Grenoble, France) to examine PM10 samples collected at two sites in the Province of Trieste, Italy. In addition to the determination of Ca, Cl, Cr, Fe, K, Mn, S, Ti and V, the authors were interested in the granulometry of the collected particles. The imaging facilities at the beamline revealed that some elements (Ca, Fe and S) were more amenable to this type of analysis than others. The spatial homogeneity of a PM2.5 certified reference material, NIST SRM-2783, was also investigated by analysing four adjacent areas from the total 1 mm2 reference sample. The CRM showed a relative standard deviation of less than 7% for Al, Ca, Cl, Cr, Fe, K, P, S, Si and V and close to 17% for Mn and Ti. Fischer et al.253 reported optical and size-resolved chemical properties of aerosols transported to Mount Bachelor, Oregon, USA during Spring 2010. Samples collected using a rotating drum impactor were analysed by SRXRF to show sulfur had formed CaSO4 on surfaces of both the fine and coarse aerosols. In Argentina, Lopez et al.254 collected 24 h samples of PM2.5 and PM10 at urban and semi-urban sites in Cordoba City. The SRXRF data showed different elemental compositions in the two size fractions. Elements reflecting a crustal origin were reduced in the PM2.5 particles and anthropogenic elements were higher than those in the coarser particles. Positive matrix factorisation software was used to resolve the components and assign physical meaning to the chemical compositions. In Siberia, Artamonova255 reported elemental compositions of aerosols accumulated in winter snow and in summer, the top 0–5 cm layer of soil and birch leaves in the vicinity of the Novosibirsk tin smelter and power stations. The elemental indicators for the smelter were As, Cd, Sn, Tl and Pb whereas Ga, I, Mn and V were associated with the power plants. The author found that birch leaves nearer to the industrial sources of pollution were lower in Mn than leaves sampled from cleaner areas. The SRXRF data collected from seasonal snow cover and vegetation was reported to be a reliable seasonal environmental assessment of the urban area. Windblown and vehicle-raised dust from un-vegetated arsenic-rich mine tailings in Nova Scotia, Canada were characterised by Corriveau et al.256 from seven particle size fractions (0.5 to16 μm) collected by a cascade impactor. All three of the sampling sites were used for recreational activities with off-road vehicles racing on two of the tailing fields. Total arsenic concentrations in the <8 μm fraction varied from 65–1040 ng m3 of air measured by particle-induced X-ray emission (PIXE) analysis. The same samples were analysed by μ-SRXRF-XANES and μ-XRD showing the presence of multiple As-bearing mineral species including Fe–As weathering products. The vehicle traffic is thought to contribute to the production of fine-grained As-rich particles in the airborne dust with potential human health risks. Godelitsas et al.257 also used As K-edge XANES to analyse particulate matter collected in Athens, Greece. The spectra showed both Aslll and AsV to be present in the respirable PM2.5 fraction previously sampled for electron microscopy studies.Studies on samples collected from the domestic environment continue to assist in the understanding of human health risk assessment. MacLean et al.258 used XAFS, μ-SRXRF and μ-XRD to determine the speciation of house dust samples from four Canadian homes known to contain elevated Pb concentrations <1000 mg kg−1. The inorganic species of Pb identified were linked to metal, carbonate, hydroxyl carbonate, oxide and Pb adsorbed onto iron oxyhydroxides. Lead citrate and Pb bound to humate were the organic species reported. Related work by Waker et al.259 used the same techniques to identify paint pigments including white lead (hydrocerussite) and lithopone (wurtzite and barite) as the primary source of Ba, Pb and Zn in bedroom dust. A lower level of lead in the living room dust showed a relationship with garden soil but no evidence of Pb and Zn from the bedroom paint pigments. The techniques were also successful in confirming the presence of chromated copper arsenate treated wood as a source of As brought into the living room. Asbury and Shannon260 reported a method for the quantitative evaluation of carpet cleaning technology. Five different test compounds were incorporated into artificial soil that was then applied to a test carpet. XRF analysis then showed the relative differences in removal efficacies of various cleaning processes including vacuuming and wet extraction.
The literature continues to report routine dust surveys that provide a comprehensive and temporal data base of air quality around the globe. Staying in Athens, Remoundaki et al.261 demonstrated the influence of Saharan dust on air quality that became a priority for southern European cities during the last decade. This study used conventional EDXRF to measure 12 elements that proved to exceed the EU regulatory limit of 50 μg m−3 several times during the sampling period when Saharan dust was transported over Athens. Sulfur and heavy metals in the fine particulates (<1 μm) were also detected and were thought to be associated with local emissions. The distribution of heavy metals in road dust along an urban-rural gradient in Massachusetts, USA, was reported by Apeagyei et al.262 and showed links to motor vehicle brakes and tyre wear. Hamza et al.263 compared 2009 XRF and XRD data with earlier measurements on samples collected during dust storms over the Arabian Gulf to show a shift in characteristics that may constitute a sensitive indicator of climate change affecting the region. Increasing productivity and liberation of iron from sediments is thought to lead to an increase in dimethyl sulfide in the atmosphere, which by oxidation will scatter solar radiation effectively with a consequent decrease in global temperature.
With so many papers now reflecting the increased use of synchrotron beam lines, Lucarelli et al.264 posed the question “is PIXE still a useful technique for the analysis of atmospheric aerosols?”. In Italy, the 3-MV Tandetron accelerator in Firenze has an external beam facility that is fully dedicated to PIXE and particle-induced gamma-ray emission (PIGE) measurements of atmospheric aerosol elemental composition. All elements with Z > 10 were simultaneously detected by PIXE in a few minutes and an automatic system for the positioning, changing and scanning of samples offered the opportunity for the analysis of aerosols collected by different sampling devices. With a capability of detecting crustal elements, PIXE-PIGE analyses were thought by the authors to be unrivalled for studies on mineral dusts. The detectable elements also include markers of anthropogenic sources thereby offering effective source apportionment studies of polluted urban environments. Hence, the authors answered their question with a resounding “yes”. Bernardoni et al.265 were interested in the analysis of samples collected by two different deposit impactors that were known to collect the aerosol in an inhomogeneous geometry. They calibrated an EDXRF spectrometer for this purpose and compared the results with PIXE data to report good agreement between the two techniques. The advantage of the cheaper EDXRF approach is that it is easier to use and more widely available than PIXE to meet the needs of many analysts.
Other work of interest to readers of this section of the review included standardless quantification of particle-like surface contaminations by grazing incidence XRF analysis.266 This approach required particles to be deposited on a flat substrate. If the particles exhibited surface areas parallel to the substrate surface, total reflection of the incident X-rays might arise preventing X-rays from penetrating and exciting the particles. To further understand these effects for nano-scaled objects examined by GIXRF, the authors prepared artificial nano-structures of known size, shape and composition on flat silicon wafer surfaces. A reference-free quantification of the deposited mass was carried out using a simple model for X-ray standing waves (XSW) through the sample material. Good agreement between nominal masses and measured values depended on the quality of the manufactured surfaces with only moderate agreement reported for samples that were more difficult to manufacture. GIXRF measurements offered information on the physical dimensions of the structures that agreed with those obtained by an EDXRF column attachment on an SEM. The authors offered their quantification model based on XSW software for the assessment of nano-particles sampled from an aerosol phase. Sun et al.267 used a laboratory confocal μ-XRF spectrometer based on an incident polycapillary focusing lens and a polycapillary parallel X-ray detecting lens for size-resolved source apportionment of aerosol particles. The detection optics increased the collecting angle of the detector and improved the signal-to-noise ratio of the X-ray spectra. The authors established a size-resolved fingerprint data base for the air pollution sources of interest to establish a method based on quantitative XRF data for single particles as part of a study of aerosols generated on hazy-foggy days in Beijing, China. Jones and Flynn268 reported results on particles captured from the comet 81P/Wild2 in gradient density silica aerogel that returned to earth in 2006. Analyses of these Stardust mission particles revealed several new insights into the formation of the solar system. However, since the aerogel used as the capture media was silica, the subsequent analysis of the silica-rich particles was complicated by the mixing of silicon from the particles and the aerogel. Consequently, future missions will use non-silica aerogels such as alumina, zirconia or resorcinol/formaldehyde which the authors tested using fragments analysed by XRF. The study showed that resorcinol/formaldehyde aerogel proved to be the best capture material in that the XRF could analyse particles that were less than 10 μm in size.
3.6 Consequences of industrial activity
Literature during this review period reflected interesting work to find new uses for material previously considered as waste, with XRF being amongst the techniques used for characterisation. Whilst the analysis may be considered routine, the range of applications serve as an example of the ways in which industrial waste products are being re-used rather than consigned to land fill. Eliche-Quesada et al.269 studied various industrial wastes such as urban sewage sludge, bagasse (fibrous matter that remains after sugarcane is crushed to extract juice), sludge from the brewing industry, olive mill waste-water and coffee ground residue. These materials were blended with clay to produce ceramic bricks with a 19% improvement in thermal conductivity when compared to bricks made without the waste materials. Felipe-Sese et al.270 also used industrial waste products to manufacture bricks that satisfied regulatory requirements for use as low-temperature structural insulation ceramics. Chen et al.271 investigated the potential use of recycled fine aggregate powder as a filler in asphalt mixes and Liu and Xu272 evaluated asbestos tailings for the same purpose. Esteves et al.273 used biomass fly ash to mitigate an alkali–silicate reaction in cement mortars responsible for the degradation of some older concrete structures.Donner et al.274 used μ-SRXRF to investigate the speciation of Cu and Zn in biosolids (waste-water residuals). High resolution mapping was reported to reveal heterogeneity in elemental associations and a combination of both organic and inorganic binding environments. Linear combination fitting of K-edge X-ray absorption spectra indicated consistent differences in metal speciation between freshly produced and stockpiled biosolids. Sulfide minerals were found to play a dominant role in metal binding in freshly dewatered biosolids whereas they were not as effective in stockpiled material with consequences for the long-term stability of metals and their eventual fate following land application. Fawcett and Jamieson275 used μ-XRF, μ-XRD and μ-XANES to distinguish between As, Sb and roaster-derived iron oxide transformations in mine waste and sediment at a Canadian gold mine. In the cyanide roaster dust, the 3+ phase was the dominant oxidation state for both As and Sb whereas 5+ was identified in the bulk calcined material with consequences for predicting their eventual fate in the environment.
Routine XRF investigations continue to feature in studies of fly ash. Shao et al.276 analysed ash deposition in a co-firing three-fuel blend system using woody biomass (white pine), peat and lignite. The authors compared ash from the three-fuel system with two-fuel blends of lignite and pine or peat with individual fuel collected with an air-cooled probe sampler installed in the freeboard zone of the reactor. The chemical composition of deposits from the three-fuel blends were shown to be enriched with Al and Si and depleted in K, P and S. Gonzalez-Fernandez et al.277 reported the distribution and mobility of As, Cu, Pb and Zn in the non-saturated zone of the alluvial plain of a mining wadi in SE Spain. Elemental chemistry of soils, sediment and different plant species was reported using XRF and XRD techniques to show that values for As, Pb and Zn exceeded the limits established by the European Union for leachates. Although activity at the Idrija mine in Slovenia ceased in 1995, large quantities of mining waste containing high concentrations of mercury remain in the area. Tomiyasu et al.278 measured total mercury and methyl-mercury by XRF in the tailings and fluvial terrace and forest floor soils to show pollution some 20 km downstream from the mine. In Japan279 ceramic waste from electrical insulators was investigated for use in cement mortars as a possible effective way to improve resistance to chloride ion penetration.
Readers interested in a more comprehensive review of all atomic spectrometry techniques for environmental analysis should refer to our companion review.3
3.7 Archaeological and cultural heritage
As a contribution to the development of instrumentation and technique, portable instrumentation for the XRF and XRD analysis of artwork was described by Eveno et al..280 Their instrument incorporated a copper anode air-cooled X-ray tube, polycapillary optics and an advanced 2D detector with Debye-Scherrer XRD measurements being made in reflection mode and a capability for XRF analysis at the same point. The authors provided a number of examples of the application of this instrument, including distinguishing different lead pigments and identifying lapis lazuli, a mineral that is difficult to recognise from XRF data alone. Deneckere and colleagues281 explored the feasibility of the application of μ-Raman imaging to complement μ-XRF imaging, especially to overcome the limitations of the conventional approach of Raman measurements at a few spots, which is inferior to imaging when characterising heterogeneous samples. Kanngiesser et al.282 reviewed the opportunities for 3D spatial imaging in cultural heritage samples offered by confocal μ-X-ray spectroscopy, in particular overcoming the limited penetration depth of both the EPMA and PIXE techniques. Their review covered developments in SR beamlines, particle accelerators and desktop spectrometers and included the opportunity to undertake speciation depth profiling using confocal XANES spectrometry. Bertrand et al.283 reviewed the application of synchrotron spectroscopy and imaging to the present field of application emphasizing the breadth of applications and the potential offered by third generation synchrotron systems.The use of X-ray fluorescence to analyse coins of historic and archaeological interest is regularly featured in this section. In an imaginatively titled paper (Making sense and cents…), Shilstein and Shalev284 used a simple XRF instrument to analyse Euro coins of 10, 20 and 50 cents minted in five European countries (Belgium, France, Germany, Italy and Luxemburg) to identify the extent of local and temporal variations in composition as a proxy for archaeological material that is typically less controlled and therefore difficult to cluster. The Sn/Cu and Zn/Cu ratio was measured with a relative precision of about 5% and the average ratios for coins from each country was determined from 20 to 39 coins. A range of Sn/Cu mass ratios from 0.0101 to 0.0111 (9%) was detected and one coin from Luxemburg showed differences of up to a factor of 1.5 over its surface showing that even modern metal artifacts display differences in composition that can be correlated with their production and place of use, an observation that is relevant to variations found in archaeometallurgical studies. Rarely is it possible to make cross sectional measurements on coins of archaeological interest, but Rodrigues et al.285 did so using μ-XRF and μ-SRXRF to check the fineness of the alloy used to manufacture silver denarius coins of the Trajan period (98–117 AD) and to see if the presence of impurities would allow identification of ore sources. Additional measurements were undertaken by ED-SEM and the authors found that the Ag content was enriched in the 100 to 200 μm surface region due to the effects of corrosion, an observation that was made in a further contribution from this group286 and attributed to the depletion of copper in surface layers to form a typical green surface patina. This latter study used the same techniques as well as PIXE to characterise silver coins from the Hoard of Becin from the Ottoman Empire (16th to 17th centuries). The average silver content was found to be 90 to 95% m/m, a result that was contrary to historic interpretations that predicted a debasement of approximately 44% in the silver content of coins during the period studied. The fineness of ancient silver coins was also of interest to Kantarelou et al.287 who proposed a set of three complementary XRF analytical methodologies in an assessment of a collection of 82 silver coins that originated from different mints in the reigns of the first five Ptolemaic kings (321–180 BC) comprising the Ioannes Demetriou collection. The tests were designed to provide reliable bulk compositional data despite the possible presence of a silver enrichment layer on the surface and comprised (i) a comparison of micro-spot XRF data on original and cleaned surfaces, (ii) an evaluation of the Ag K/L ratio, and (iii) a comparison of measured and theoretical intensity of the Rayleigh peak of the tube anode scattered off the sample. When comparing XRF and ED-SEM results in a study of official and imitation bronze Roman nummi of the 5th century AD, Canovaro et al.288 observed differences which they attributed to the migration of Pb to the surface layers such that the XRF results represented (perhaps not unexpectedly) the surface but not the true bulk composition. Further studies of corrosion processes in archaeological bronzes were undertaken by Alberghina et al.289 using laboratory made binary, ternary and quaternary alloys typical of the Roman period and an integrated range of techniques, including XRF.
XRF was also used to analyse a wide range of other metallic artifacts as exemplified by the work of Leroy et al.,290 who used confocal μ-SRXRF and LA-ICP-MS to characterise slag inclusions trapped in the metallic iron matrix of medieval armour. Their work was aimed at elucidating the origin of the armour, which had been attributed to Lombardy by art historians. Cattaneo et al.291 were interested in bronze artifacts from a pre-Roman Ligurian settlement (Guardamonte-Monte Vallassa, Pavia, Italy), combining XRF for the surface analysis of objects covered by corrosion and concretion layers with time-of-flight neutron diffraction, which allows access to depths of a few cm to the interior of metallic objects. In some cases, their data gave indications of the method of production, for example casting or hammering. Portable XRF and TOF neutron diffraction were also used by Gliozzo et al.292 to characterise Roman bronze artifacts from the 1st to 3rd century AD archaeological site of Thamusida (Morocco). The 26 objects studied were classified into alloy types and results were interpreted as either anticipating the important change in the Roman use of copper alloys (generally referred to as the ‘zinc decline’) or more likely, the fact that brass never entered the local metal-working activities of this military site. Galli et al.293 used both portable EDXRF and a capillary collimated spectrometer to characterise grave goods from the Royal Tomb 14 (Sipan, Peru) comprising thin copper sheets or tumbaga (a natural alloy of copper, silver and gold) from the clothing of a warrior priest. EDXRF was reported to be particularly useful in the analysis of fragile material that could not be polished to remove corrosion products with a fundamental parameter method used to quantify results, taking account of the surface patina and inhomogeneous composition. Figueiredo et al.294 used μ-EDXRF and ED-SEM to study inclusions and the composition of Bronze age copper-based artifacts from Portugal, concluding that in the Copper Age and Early Bronze Age, copper and arsenical copper were in use with tin bronze only taking over by the Late Bronze Age leading to a general decrease in the average tin content of bronzes in the Early Iron Age. The origins of gilding with mercury was the subject for study by Martinon-Torres and Ladra295 who used portable XRF to characterise two torcs (neck rings made of strands of metal twisted together) that revealed the earliest use of this technique in the northwest of the Iberian Peninsula, and speculated on the transmission of this technology from the Atlantic Coast of Europe. Sandu et al.296 reviewed the wide range of techniques (including XRF, TXRF and XPS) for the investigation of a range of ancient gilded objects from European cultural heritage, recommending an integrated, complementary interdisciplinary approach, but with an emphasis on the effectiveness of microscopy. Before leaving this subject, mention should be made of an investigation by Abe et al.297 of the gold ground of a pair of folding screens by Ogata Korin ‘Red and White Plum Blossoms’, a Japanese national treasure. In a detailed study using portable XRF and XRD instrumentation, the authors concluded that the gold ground of the screen could be produced by gold leaf, rather than gold paint as had been reported in an earlier study.
Glass regularly features in this section, no less this year as illustrated by the work of Liu et al.298 who used portable XRF to analyse and classify ancient glass samples excavated from Xinjiang, Guangxi and Jiangsu provinces, China. As part of this study, the authors investigated the effect on quantification of the distance between sample and reference plane of the instrument and the effect of the curved shape of the sample surface; aspects that are of relevance to many real world applications of this technique. In a further contribution from this group,299 samples from the Xinjiang Province were classified into three types and the authors speculated on exchange and trade networks in the Han (202 BC to 220 AD) and Yuan (1271–1368 AD) Dynasties. Dark coloured manganese-rich stains can be found in the alteration layer of ancient glass artefacts and is an issue for the restoration and conservation treatment of the glass as highlighted by Cagno et al.300 These workers used μ-XANES and μ-XRF and μ-absorption CT to examine fragments of 14th century glass from Sydney Sussex College, Cambridge, UK. The authors concluded that treatment with hydroxylamine hydrochloride was effective in removing manganese browning from the glass, but that it suffered from a number of side effects that needed to be minimised. Delgado et al.301 used XRF and UV-VIS spectroscopy to support a μ-PIXE study of medieval yellow silver stained glass from the Convento de Cristo, Tomar, Portugal. Results showed that yellow staining was produced from a mixture of silver and copper, the 14th century process being investigated by experiments on glass synthesised in the laboratory. Work continued in the characterisation of glass beads from the Mycenaean Palace of Nestor at Pylos, Peloponnesus, Greece by Polikreti et al.302 using portable XRF to compare compositions with Late Bronze Age glasses from Egypt, Mesopotamia and mainland Greece, with a particular interest in Ti and Zr contents. The authors concluded that results supported the hypothesis that glass beads found at this Palace were made of foreign-produced glass introduced via internal Greek trade routes. Vaggelli and Cossio303 evaluated the μ-XRF technique for the non-destructive study of Islamic cultural heritage glass finds of Sasanian production (3rd–7th century BC) on the basis that this technique offered superior detection limit performance to EPMA but inferior to ICP-MS. The authors reported an accuracy within 5% for the major elements in the glass and for Cr, Mn, Sr and Zr when present at >100 μg g−1.
The provenancing of pottery remains a popular XRF application, often using a multi-technique approach involving XRD, SEM and/or thermogravimetric analysis. However, Speakman et al.304 used portable XRF and INAA to analyse 75 archaeological pottery shards from the American Southwest using data to separate samples into compositional groups. When comparing analytical data from the two techniques, the authors concluded that the unambiguous separation into compositional groups was challenging by portable XRF because of the limited number of key discriminating elements that could be measured compared to INAA and the relative precision and accuracy of the XRF data. The uncritical application of portable XRF in this field was the subject of a paper by Forster et al.,305 who undertook an evaluation of the parameters and constraints that affect this technique in the analysis of archaeological ceramics. The parameters investigated were surface methodology, organic surface coatings, grain size and mineralogy and when applying these parameters to the portable XRF analysis of heterogeneous handmade ceramics from Central Turkey, the authors concluded that the technique provided a high level of precision and accuracy in the geochemical discrimination of archaeological ceramics. An alternative approach in the WDXRF analysis of ceramic samples of small mass was reported by De Vleeschouwer et al.,306 who compared determinations on 300 mg of powder with 2 g test portions. Because elemental intensities varied with the mass of the test portion, the authors considered that calibrations for the two approaches were comparable, with the small mass method showing great potential for ceramic studies. Micro-focus XRF elemental mapping and XANES were used by Sciau et al.307 to investigate the different firing methods used in the manufacture of ancient ceramics from southern Gaul and Italy in a study aimed at discriminating differences in clay composition and conditioning and kiln firing. Li et al.308 used EDXRF line scanning technology to study the thin layer between glaze and body of porcelain from the Jin and Yuan dynasties in China, showing that this layer, which was found to have a higher K2O content than glaze or body, was formed by reactions that occurred during firing. Sicilian ceramic fragments dating back to the 12th and 13th centuries were of interest to Bardelli et al.309 who used portable XRF to provide elemental and spatially resolved data on the major and minor constituents of the decorated coating (especially attributing Fe and Mn to the colouring agent) and XAS to discriminate between samples, identifying umber (comprising a mixture of hydrated iron and manganese oxides) as the pigmenting agent.
Once again, the analysis of painting and murals features strongly in the publications that appeared during the current review period with XRF often coupled with Raman and other techniques for the identification of pigments. In the measurement of elemental distribution maps in the study of historical paintings, Alfeld et al.310 described three self-built macro-XRF instruments and included a discussion of the use of polycapillary optics and pinhole collimators as beam defining devices. The imaging capabilities of these instruments were exemplified by measurements of paintings from the 15th to the 19th centuries with a direct comparison being made with μ-SRXRF in the case of van Gogh's ‘Patch of Grass’. Zemlicka et al.311 described the application of a highly sensitive hybrid semiconductor pixelated detector (Timepix) in novel table-top scale instruments designed to undertake measurements by X-ray transmission radiography and by X-ray induced fluorescence imaging. These instruments were evaluated on samples comprising several layers prepared in a restoration laboratory and designed to represent real historic paintings from the 19th century. A study of quantitative EDXRF methodology for measuring the areal distribution of pigments and to characterise painting methods of ‘oil on copper’ works of art was undertaken by Pitarch et al.312 with the intention of applying layer thickness measurements used for quality control in the coatings industry. XRD was used for supplementary measurements on two paintings from the 16th and 18th centuries. As well as identifying the copper or brass supporting material, two superimposed layers were identified. One layer comprised a mainly white lead preparation layer and the other the pictorial layer comprising a range of pigments. The main scope of the work of Thoury et al.313 was to study the luminescence properties of cadmium pigments for the in situ mapping of pigments in paintings (e.g., Edward Streichen's 1920 study for ‘Le Tournesor’) with XRF as one of the techniques used to corroborate results. Confocal μ-SRXRF, μ-XRD, optical microscopy and SEM were all used by Valadas et al.314 to identify pigments and study the stratigraphy and degradation of paint layers in the murals of the 17th century frescoes at the Misericordia Church of Odemira, Southwest Portugal. Following in situ examination, micro-fragments of paint layers were analysed by SEM and the SR techniques indicating that the pigments were essentially yellow, brown and red ochres, smalt blue, copper green and black earths, probably from local sources. Donais et al.315 used portable XRF and portable Raman spectrometers to study pigments in frescos at the Coriglia, Castel Viscardo excavation site near Orvieto, Italy, identifying pigments and discussing analytical approaches and data analysis.
XRF, especially portable XRF is extensively used to provenance lithic archaeological artefacts. To some extent the success of such studies depends on the absence of, or alternatively the characterisation of surface weathering, if the non-destructive characteristics of this technique are to be maintained. Gauthier and Burke316 investigated this phenomenon using polarised EDXRF to study a set of Ossipee archaeological hornfels flakes from New Hampshire, USA, comparing results from weathered and mechanically ground surfaces. The authors used specific variation diagrams to portray the weathering trend. Yoshida et al.317 included XRF in a range of techniques used to determine the formation process and elemental mass balance associated with the formation of weathering rinds on Mesozoic sandstone and basalt cobbles buried in terrace deposits for up to 300 ka in the western part of Fukui prefecture, central Japan. Results showed that the Fe content of the weathering rind on the basalt cobbles decreased slightly from the surface to the unweathered core, whereas there was an Fe-rich layer some distance below the surface of the sandstone. In both cases, the weathering of Fe was associated with the precipitation of iron oxyhydroxide minerals. Millhauser et al.318 tested the accuracy of portable XRF data in a study of obsidian artefacts from Xaltocan in Central Mexico. The authors reported that their ability to assign artefacts to sources was not compromised by the length of read time, the presence of surface residue or incomplete coverage of the detector due to the small size of the sample. However, the analysis of concave surfaces did reduce the accuracy of measurements due to the increase in distance between artefact and detector. Sun et al.319 found that portable XRF and PIXE data were comparable in the characterisation of jadeite jade. Of the significant number of other provenencing studies, the work of Burley et al.320 is of interest in demonstrating portable XRF measurements of volcanic glass specimens from 12 archaeological sites in the Kingdom of Tonga, that inter-island voyaging and trading existed over a distance of 600 km along the Tonga island chain from 2900 BC and throughout later prehistory. XRF and INAA were used by Glascock et al.321 to provenance high quality volcanic glass found at archaeological complexes in the River Amur basin, of the Russian Far East. Analysis of results showed that transport of obsidian extended for 50 to 750 km for sources found within the river basin during the Neolithic and Early Iron Age periods and from 550 to 850 km in relation to sources located outside the Amur River valley. XRF data for obsidian from three Paleo-indian assemblages in Northwest Nevada, USA were used by Smith and Kielhofer322 to contribute to an understanding of the residential versus mobility of these peoples and the locations in the landscape that attracted them.
The analysis and provenancing of archaeological building materials is one of the developing areas to which XRF analysis contributes with applications published during the current review period including building stone, bricks, mortar and plaster. The development of lightweight concrete was one of the major technical achievements of the Romans and the geochemical analysis of scoria and pumice used in the concrete from which vaults were constructed in ancient Rome was the subject of a study by Lancaster et al.323 Geochemical signatures indicated that the dark scoria originated from Vesuvian lavas (36–18 ka) (not more recent events on which Pompeii was built) and the light coloured pumices from Campi Flegrei (not the Sabatini volcanic system, as had been previously thought). The authors extended this approach to light-weight stones used in vaulting by the Romans in modern-day Turkey and Tunisia.324 The provenancing and manufacturing of bricks and tiles was of interest to Gliozzo et al.325 who used XRF, XRD, SEM and optical microscopy to provenance samples from Thamusida (Rabat, Morocco) analysing samples that spanned the Roman occupation to the Islamic period. Similar techniques were used by De Francesco et al.326 to demonstrate local production of bricks and some amphorae of Roman Imperial age from Muricelle, close to Cosenza (Calabria, Italy). Archaeological mortars from Pompeii were characterised by a range of techniques, including XRF by Miriello et al.,327 who led a similar study in the characterisation and provenancing of lime plasters from the Templo Mayor, the main pyramid of Tenochtitlan (Mexico). A multi-technique approach was used to characterise plasters from the Ptolemaic Baths, near the Karnak Temple Complex, Upper Egypt by Mahmoud et al.328In toto, these reports demonstrate the growing interest in applying the XRF technique to archaeological building and construction materials. A slightly different aspect was reported by Sanjurjo-Sanchez et al.329 who compared coatings on natural rock outcrops with those on the surface of stone buildings in Northwest Spain. One aspect of interest was that some coatings had a protective effect against erosion and the authors used XRF and XRD to analyse the underlying rocks and XRD and ED-SEM to characterise the coatings. Their results showed that natural outcrops were widely covered by biological coatings or coatings that originated from weathering of the rock, whereas the micro-environment influenced coatings on building stone to a much greater extent with air pollution, other building materials, and organic droppings all having an effect.
Wood and paper are not the most obvious artefacts for XRF study, however, Smith et al.330 applied the portable XRF and SR-XAS techniques to a Bronze Age wooden shovel found in the copper mines at Alderley Edge, Cheshire, UK to discover the reason for its remarkable state of preservation compared to other wooden artefacts found in the mine. Results indicated that preservation was caused by As and Cu along with significant amounts of Pb that entered the wood of the shovel during its use in working mineral-rich deposits, rather than through the burial environment. Fors et al.331 reviewed the use of various X-ray spectroscopies in the analysis of waterlogged wood relevant to conservation methods applied to historical shipwrecks. The partly degraded parchment of some Dead Sea Scroll samples were analysed by 3D μ-XRF and μ-XRF by Mantouvalou et al.332 to identify reliable marker elements that could be used for classification and provenancing studies – bromine was considered to be diagnostic in screening a large number of samples, even on site, using portable μ-XRF. In a further contribution333 the Cl/Br ratio, corresponding to that of water from the Dead Sea, was considered to make it possible to distinguish parchment and leather fragments whose origin lay within the Dead Sea region from those produced in other regions using μ-XRF. Not the easiest of materials to analyse, leather found on a 6th century Chinese bronze sword was the subject of a Raman, FTIR and XRF study by Luo et al.334 applied on discoveries from the 6th century BC at an excavation site in Yun county, Hubei Province, China. Castro et al.335 used portable XRF and specialised spectroscopic techniques including NMR and Raman to characterise the ageing processes that affect paper and papyrus with light and chemical oxidation being found to cause the most aggressive effects. Although techniques such as SEM and XRF have been used to study the small brown rusty stains (foxing) often found on paper documents of historic interest, Zotti et al.336 demonstrated the value of FTIR to identify residual microfungal agents and the by-products of their activity on paper substrates.
Conservation is a hugely important issue in the preservation of items of cultural heritage, and Van Grieken and Worobiec337 highlighted the important role of X-ray spectrometry, in its many forms, as one of the most relevant techniques in preventative conservation with a particular emphasis on identifying particle types and their sources as well as gaseous pollutants in indoor environments, including museums, that impact on conservation. The authors provided examples of their work, including the recommendations to remove deteriorating plaster wall renderings that were releasing particles that threatened classic paintings, the threat from automotive diesel soot particles entering a museum through drafty gaps in windows and doors in addition to problems from street de-icing salts and coal burning particles brought into a museum by visitors, mainly in winter. Van Grieken was co-author of a further contribution338 using a multitechnique approach to investigate the effect of atmospheric pollutants on the construction materials and artworks in the San Jernimo Monastery, Granada, Spain. High abundances of soil dust particles, salt aerosols and nitrogen and sulfur oxides were detected together with surprisingly high abundances of amorphous black carbon particles. Interestingly, some of the degradation problems were attributed to the resuspension of particles due to the cleaning practices (dusting) in the monastery. A multi-technique approach (including XRF) was used by Kigawa et al.339 to investigate the effects of fumigants on museum objects that contain protein (e.g., muscle, animal glue and silk). XRF data revealed residual Br and I in muscle that had been fumigated with either methyl bromide or methyl iodide and the report provided the first detailed evidence for the chemical alteration of a protein material by fumigants under common conditions used in museums. Alberghina et al.289 used XRF as one of a group of techniques to study corrosion processes in archaeological bronzes with an emphasis on the chemical composition of the patina and migration phenomena between bulk and alloy surface. XRF was one of the techniques used by Zammit et al.340 to demonstrate the biodeterioration of artworks in Maltese catacombs by the formation of metastable minerals by microbially mediated processes. The interest of Fiorucci et al.341 was in the use of a laser to clean graffiti from ornamental granite (Rosa Porrino), using XRF as one of the techniques used to characterise the substrate. It was found that the laser caused mineralogical damage to the stone with biotite being the most susceptible mineral. By contrast, Saeed et al.342 were interested in the conservation of large historic vehicles in museum environments with XRF used to provide information on material composition and ultrasonic methods to obtain a material loss profile. As might be expected, corrosion was the main cause of material loss.
The final subject for consideration in this section is the XRF analysis of fossil bones, exemplified by the work of Janos et al.343 who examined human bones from two 10th century AD cemeteries in Northeast Hungary. Diagenetic alteration was postulated to have affected many of the elements determined, but the Br, Sr and Zn contents appeared to have accumulated during life. Thomas and Chinsamy344 undertook a chemometric analysis of hand-held XRF data from fossil bone and tooth data from two Pleistocene localities in the Western Cape of South Africa. One set of bones was distinguished by elevated Ca and the other by Fe and Sr and the authors speculated on the influence of ground water percolating through the sedimentary matrices of each locality. And finally, Piga et al.345 adopted a multi-technique approach (XRD, XRF and FTIR) to characterise the diagenesis of dinosaur bones from Spain of Upper Jurassic/Lower Cretaceous age. In addition to Ca and P, the XRF data showed the presence of Fe and Sr at significant levels, both incorporated into the mineral fluorapatite and at higher levels associated with the presence of goethite (FeOOH) and celestite (SrSO4).
3.8 Forensic
XRF continues to play a selective role in the characterisation of samples for forensic analysis and to support such activities, Nakano et al.346 described the use of a table-top confocal X-ray microscope instrument for ‘criminalistic’ purposes. The instrument, which incorporated a poly-capillary lens, was applied to multilayer paint fragments and leather samples and results were in approximate agreement with cross sectional analyses undertaken by conventional μ-XRF. XRF, Raman and IR/VIS spectrometry were used by Zieba-Palus and Trzcinska347 to examine 50 and 200 PLN court tax marks suspected of being forgeries although comparison with ink and glue supplied by the manufacturer only showed discrepancies that were thought to be caused by physical handling of the documents. Li et al.348 were concerned with the overharvesting of a Chinese delicacy, nostoc flagelliforme (an edible blue-green algae) and the consequent provision of counterfeit supplies on the retail market. They evaluated the use of EDXRF and FTIR to authenticate samples in place of more conventional techniques that involved the destruction of samples that were valuable (if genuine). The integrity of chemical weapons dumped in the Bornholm Basin was investigated by Khalikov and Savin349 by the XRF and voltammetric analysis of As sediments. Enhanced As values were found to be local in character and not at present considered to be a hazard to the local environment. Bong et al.350 claimed a first in the use of high energy (116 keV) SRXRF for the quantitative analysis of trace elements in geological samples and proposed the use of this technique for forensic investigations of trace amounts of high atomic number elements in soil. Forensic anthropological examinations were performed by Christensen et al.,351 who conducted XRF analysis on a variety of tissues and materials in unaltered and altered (damaged) states. Characteristic levels of Ca and P allowed the researchers to identify the “unknown” material as osseous or dental in origin.3.9 Industrial
The maturity of the XRF technique for the chemical characterisation of materials is once again confirmed in this review period. A wealth of contributions were published in which XRF combined with other analytical tools was routinely applied to characterise various types of catalysts, modified clay minerals and zeolites, ceramics, slags and other novel materials. As most of these papers involved the industrial process rather than describing the XRF measurements, they are not considered in this review but interested readers should consult our companion review on Industrial analysis: metals, chemical and advanced materials.2Investigations regarding the presence/absence of toxic components in plastic materials are of importance in the estimation of associated health concerns. The presence of Cu, Fe, S and Sb in PET bottles was studied by Shimamoto et al.,352 who used XRF to verify if Sb, a common catalyst applied in the synthesis of PET, was present in the final products. Concentrations of Sb varied between 2.5 and 11 mg kg−1 in the 20 samples analysed. Chemometric treatment of the XRF data enabled the classification of PET samples between bottle-grade PET/recycled PET blends by the Fe content. The identification of flame retardants in polyurethane foam, collected from 101 baby products, was performed by Stapleton et al.353 Portable XRF was used to estimate the Br and Cl content of the foam to verify whether XRF was a useful method for predicting the presence of halogenated flame retardant additives in these products. A significant correlation was observed only for bromine. Matsuyama et al.354 also determined Br concentrations using XRF as a tracer for decabrominated diphenyl ether (DBDE), performed in a homogeneity study of a newly developed certified reference material (CRM) consisting of polystyrene resin. The concentration of DBDE in the CRM was certified as 312 mg kg−1 with an expanded uncertainty (k = 2) of 16 mg kg−1. The homogeneity assessment of reference materials consisting of epoxy moulding compounds and spiked with Cd and Pb at two different concentration levels, was performed by Lee et al.355 Measurement results obtained by ICP-AES, LA-ICP-MS and XRF techniques showed a variation in homogeneity related to both the instrumental technique used and the CRMs investigated.
The use of XRF for the determination of the elemental composition in building materials remains a recurrent issue. In two contributions by Hejzlar, XRF was used to assess corrosive problems related to imported Chinese drywalls. In the first,356 the context included sulfur-based attack on copper in domestic residences. In this study, small segments of copper were exposed to 45 different samples of drywall. The XRF results showed that the method could detect sulfur impact on copper due to emissions from drywall and also distinguished between corrosive and non-corrosive drywalls. In the latter contribution,357 the applicability of portable XRF was investigated by determing Sr levels in certified gypsum reference materials and various corrosive and non-corrosive drywalls. Although Sr levels were typically higher in corrosive drywalls, there were a number of non-corrosive drywalls that had levels above the regulatory value of 1200 mg kg−1. Moreover, some corrosive drywalls showed Sr levels below 600 mg kg−1. These results indicated that both false positives and false negatives could be readily reported, thus potentially reducing the reliability of the portable XRF results. A similar application is included in Section 2.7 of this review concerning hand-held and mobile XRF publications. Gredmaier et al.358 used μ-XRF to visualise the Ca and S distribution in fired clay brick in the presence of a black reduction core. The elements Ca and S appeared to combine to form a compound, most probably calcium sulfate, around a so-called reduction core, caused by magnetite (Fe3O4) in the centre of the brick body. Bouchard et al.359 examined all the XRF analysis conditions for the calibration of raw materials using a robust fusion sample preparation methodology as well as the numerous reference materials used for this analytical application. The authors demonstrated that the fast automated fusion of non-ignited samples, combined with WDXRF spectrometry, complied with both cement standard methods of analysis ASTM C114 and ISO/DIS 29581-2.
Research on environmentally friendly, healthy and efficient alternative pigments in anticorrosive paints was conducted by Ahmed et al., who used XRF to elucidate the concentration of different elements in the prepared pigments. In a first contribution,360 the use of cation-exchanged zeolites in alkyd-based paints was evaluated. The results revealed that paint films containing Na-zeolite offered the least protection, while films including Ca, Mg and Zn-zeolites were better in their corrosion protection performance. Corrosion protection was also reported as Zn-zeolite > Ca-zeolite > Mg-zeolite. The second contribution361 showed the performance of innovative titanium dioxide kaolin mixed pigments in anticorrosive paints.
The characterisation of materials from power plants using XRF in combination with other analytical techniques was frequently implemented in research projects. Alonso-Hernandez et al.362 reported levels of As, Cr, Cu, Hg, Mn, Ni, Pb, Ti, V and Zn in bottom ashes from a thermal plant and an oil refinery in Cuba using polarised EDXRF. High contents of Cr, Ni, Pb, Ti, V and Zn were found in these ashes, resulting in their classification as hazardous wastes as specified in the Cuban regulations. XRF in combination with XRD, spectrometric and metallographic analysis, was used by Dorri and Harandizadeh363 to conduct a “failure analysis” of perforation in the salty water-wall tubes of a power plant. The obtained results suggested that significant amounts of Cu entered into the water circulation line and caused higher corrosion rates. Austrian researchers364 investigated bed material changes in a dual fluidised bed, steam gasification plant in Austria using ED-SEM, XRD and XRF. Using forestry residues as fuel and olivine as bed material, the analyses showed the building of two Ca-rich layers around the bed particles. Analysis of the crystal structure of the used bed material revealed the formation of calcium silicates that were not detected in the fresh bed material. This might have consequences for the performance of the plant related to the catalytic activity of the bed material and the tendency for fouling in the plant. Meng et al.365 studied the pyrolysis of biomass fuels and their residual char gasification using a broad range of analytical techniques. Circulating fluidised bed chars, sampled from Agrol, willow, and dried distiller's grains with solubles (DDGS) gasification, were characterised by XRF. These results showed that the inorganic elements of the Agrol char comprised Ca, Fe, K, Mg, and Si. The willow char was mainly composed of Ca and K, with minor amounts of Fe, Mg, P, and Si. However, DDGS char was mainly dominated by K and P, with a lesser amount of Ca, Mg, and Na.
Readers of this section will recognise the wide use of XRF in industrial applications. An interesting application was presented by Hurst et al.,366 who evaluated the performance of the fundamental software package UniQuant® versus a normal calibration for the determination of elements in welding fumes. Samples obtained from the HSL Workplace Analysis Scheme for Proficiency (WASP) programme were analysed by both methods for Cr, Fe, Mn and Ni. For the normal calibration, average recovery results for the WASP samples were between 92 and 103% of the target value with relative standard deviations of 3 to 7%, whilst for the UniQuant calibration, average recovery results were between 97 and 112% of the target value with relative standard deviations of 3 to 10% being obtained. In concluding this section; Gamaletsos et al.367 investigated typical red-brown (Fe-rich) and high-quality white-grey (Fe-depleted) bauxite samples from active mines of the Parnassos-Ghiona area, central Greece. According to XRF and ICP-MS analyses, their actinide content, and particularly of Th, was relatively increased. The authors used μ-XRF and μ-XAFS at the SUL-X beamline of the ANKA Synchrotron facility (KIT, Germany) to show the presence of Th in diaspore and in Ti-containing phases, with distinct pisoliths of Fe-depleted bauxite. The XAFS spectra of Th salts and Th-containing reference materials were also obtained. Accordingly it was revealed, for the first time in the literature, that Ti-phases, and particularly anatase, hosted significant amounts of Th.
3.10 Clinical
In this year's review it is remarkable how extensively the SR based X-ray fluorescence microscopy (XFM) technique is applied in clinical research, especially to gain more insights into element contributions in cells and tissues in order to elucidate specific disease patterns. High resolution synchrotron XFM was used by Malinouski et al.,368 to map the Se distribution in mouse liver and kidney with submicrometre resolution. The authors identified a highly localised pool of this trace element at the basement membrane of kidneys that was associated with glutathione peroxidase 3. Kasaikina et al.369 performed tissue imaging of Se by XFM and direct analyses of trace elements in naked mole rats' liver and kidney. They observed that mole rats were characterised by the reduced utilisation of Se due to a specific defect in the expression of glutathione peroxidase 1. Selenite metabolites in human lung cancer cells were studied by Weekley et al.370 using X-ray absorption and fluorescence spectroscopy. X-ray fluorescence microscopy of single cells treated with selenite for 24 h revealed a punctate distribution of Se in the cytoplasm. The accumulation of Se was associated with a greater than 2-fold increase in Cu, which was co-localised with Se. Selenium K-edge EXAFS spectroscopy revealed Se–Se and Se–S bonding, but not Se–Cu bonding, despite the spatial association of Se and Cu. Microprobe-XANES showed that the highly localised Se species were mostly elemental Se. Carpentier et al.371 used μ-XRD and μ-XRF analyses in their research on metabolic defects related to kidney stone diseases. The presence of a mineral deposit at the surface of Randall's plaque, which is made of calcium phosphate, carbapatite and serves as a nucleus for kidney stone formation, has recently been underlined. The process by which apatite nanocrystals nucleate and form Randall's plaque still remained unclear. This contribution dealt with the possible relationship between trace elements, especially Zn, and the formation of this mineral. Liu et al.372 recognised the strength of XFM in their investigation of the content, distribution and demand for Zn2+ in gastric mucosa under baseline conditions and its regulation during secretory stimulation. Their findings offered the novel interpretation, that Ca2+ integrated the basolateral demand for Zn2+ with stimulation of secretion of HCl into the lumen of the gastric gland. Grasso et al.373 investigated the alteration of the endocytic vesicle membrane permeability barrier to toxins such as inorganic arsenic present in drinking water. Micro-SRXRF showed that the retention of As in the urinary bladder of rats, exposed to ingestion of As poisoned water, was lower than the kidney accumulation of As and was accompanied by altered concentrations of Ca, Cu, Fe, K and Zn, all ions related to cellular metabolism. Polish researchers374 applied μ-SRXRF for the elemental mapping of neoplastic tissues in cases of various types of brain tumours. Using multiple discriminant analysis to construct a diagnostic classifier for brain tumours, it was found that Br, Cl, Cu, Fe, K, S and Zn were the most significant elements in the general discrimination of tumour type. Popescu and Nichol375 also performed mappings of brain metals, but to examine the effect of chelators on the distribution and amount of metals in the brain, as metal chelators might improve the clinical outcome of several neurodegenerative diseases. Pereira et al.376 collected 3D elemental distribution images in biological samples (breast, prostate and lung samples) by X-ray transmission CT and XRF μ-CT, in order to verify the concentration of some elements correlated with characteristics and pathology of each tissue observed by transmission CT. The experiments were performed at the X-ray fluorescence beamline (D09B-XRF) of the BSLL, Campinas, Brazil. Results from the 3D visualisation showed that the distribution of Cu, Fe and Zn was different and heterogeneous from the analysed samples. Dodani et al.377 used μ-SRXRF in conjunction with a “Coppersensor-3”—a bright small-molecule fluorescent probe that offered the unique capability to image labile Cu pools in living cells at endogenous, basal levels—to discover that neuronal cells moved significant pools of Cu from their cell bodies to peripheral processes upon their activation. Moreover, these Cu redistributions were dependent on calcium release. Jensen et al.378 used small-angle X-ray scattering, receptor binding assays and μ-SRXRF to find that rat adrenal gland (PC12) cells could acquire Pu in vitro through an iron-dependent and transferrin-mediated cellular uptake pathway. The same research group379 also studied the cellular response to molecular and polymeric forms of Pu using rat PC12 cells. They observed that molecular Pu was taken up by PC12 cells and mostly co-localised with Fe, while aged polymeric Pu was not internalised by the cells. Leoni et al.380 used for the first time XFM to both visualise and quantify Mn under glucose-stimulated conditions in pancreatic beta-cells at cellular and subcellular levels. The obtained data confirmed that Mn could be used as a functional imaging reporter of pancreatic beta-cell activation and could also provide a basis for understanding how subcellular localisation of Mn will impact magnetic resonance imaging contrast. Zaichick and Zaichick381 continued their research on specimens of human prostate using radionuclide-excited 109Cd EDXRF, to determine Br, Fe, Rb, Sr and Zn contents in intact and morphological normal prostate tissues of 64 men who had died suddenly. A strongly pronounced tendency of an age-related exponential increase in Zn mass fraction as well as an increase in the Zn/Fe, Zn/Rb, and Zn/Sr ratios in prostate was observed. Polgari et al.121 used XANES analysis in combination with SR-TXRF acquisition, to determine the oxidation state of Fe in human cancer cells and simultaneously their elemental composition by applying a simple sample preparation procedure consisting of pipetting the cell suspension onto the quartz reflectors. Polgari et al.382 used TXRF and GF-AAS for the determination of Cu, Fe and Zn in colorectal cancer cells. The main advantage of the proposed methods was the execution of all sample preparation steps following incubation and prior to the elemental analysis in the same Eppendorf tubes. Sample preparation was performed at microscale (115 μL sample volume) with 65% v/v nitric acid and 30% v/v hydrogen peroxide.An ongoing investigation related to the determination of Ca, Cu, Fe and Zn content in the foetal and maternal portions of the placentas of teenage and adult women using SR-TXRF was presented by de Moraes et al.383 Significant differences in the Ca and Cu concentrations of the placenta's maternal portion were observed when compared to the foetal portion, for both teenagers and adults. For Fe and Zn concentrations differences were only detected when comparing the maternal portion of placenta with the foetal portion of the adults. These results suggested important differences in mineral content based on the placental portion, whereby the mineral concentration of the foetal portion of the placenta is influenced by the mother's age. In order to study the daily Pb absorption in the foetus and to monitor the main Pb sources in prenatal foetus, Tong et al.384 investigated two cases of Pb distribution along the longitudinal axis of foetal hair. By analysing the Pb distribution curves in the foetal hair and relating it to the living habits of their mothers, the study revealed that the main sources of Pb might be coming from the polluted fluid surrounding the foetus.
The constraints of in vivo applications of X-ray fluorescence in human subjects were presented by David Chettle,385 together with a more detailed description of the well-established Pb in bone measurements and the less widespread Sr in bone measurements. Lodwick et al.386 performed mathematical simulations and benchmark measurements to assess the impact that normal variations in human calcium content had on in vivo K X-ray fluorescence measurements of Pb in bone. Simulations identified a 4.5% negative bias in measured Pb values for each 1% increase in Ca weight percent in the bone matrix as compared to the calibration matrix. Behinaein et al.387 evaluated the bone lead survey, conducted by McMaster University in 2008, and in which a total of 497 smelter employees from New Brunswick participated, to examine the efficiency of Pb exposure control programmes and a four-element ‘clover-leaf’ geometry detector system. Nearly 42% of the subjects had participated in both the previous surveys performed in 1994 and 1999. The method detection limit of the clover-leaf geometry system was improved on average for tibia and calcaneus by a factor of 3.1 compared with the 1999 and 1994 surveys in which a conventional system (one detector) was used. Furthermore, by comparing the results of the three mentioned surveys, the 2008 results were found to represent the highest precision. Several research contributions are published to gain insights into the consequences of cumulative Pb exposure.388–392 Fleming et al.393 used a miniature X-ray tube and a silicon PIN diode detector to measure Pb in bone phantoms using L-XRF spectra. Besides experiments on bone phantoms made from plaster of Paris and dosed with varying quantities of Pb, a more realistic in vivo scenario with soft tissue overlying bone was simulated, using a resin material placed between the experimental system and the bone phantom. For the square cross-section bone phantoms, a layer of resin with a thickness of 1.2 mm was used and a minimum detection limit of 17 ± 3 μg g−1 of Pb was determined. For the circular cross-section phantoms, a layer of resin with an average thickness of 2.7 mm was used. From these, a more realistic minimum detection limit for in vivo applications of 43 ± 7 μg g−1 of Pb was determined. Finally, Guimaraes et al.394 studied the aging effect of Pb accumulation in bones of Wistar rats by EDXRF. Two groups were studied: a control group (n = 20), not exposed to Pb and a contaminated group (n = 30), exposed to Pb from birth, first indirectly through mother's milk, and then directly through a diet containing lead acetate in drinking water (0.2%). Rat's age ranged from 1 to 11 months, with approximately one month intervals and each of the collections had three contaminated rats and two control rats. Iliac, femur, tibia-fibula and skull were analysed by EDXRF. The Spearman correlation test applied to mean Pb concentrations showed strong and very strong positive correlations between all different types of bones. This test also showed that mean Pb concentrations in bones were negatively correlated with the age of the animals.
An evaluation of LED therapy at 945 nm to accelerate bone repair was performed by Diamantino et al.,395 who assessed qualitative and quantitative Ca and P contents by μ-XRF and the morphological structure using SEM. The results demonstrated the efficiency of infrared LED therapy, because the amount of mineral components analysed by μ-XRF and the morphological features of cortical and trabecular bones, demonstrated by the SEM images, showed enhanced bone repair in the irradiated groups when compared with their corresponding control groups at all stages. Lange et al.396 studied the Ca content in foetal and postnatal mouse bone tissue and in hydroxyapatite (HA) using synchrotron small-angle X-ray scattering (SAXS) combined with wide-angle X-ray diffraction and XRF. The study revealed strong differences in size and orientation of the mineral particles between foetal and postnatal bone, with bulkier, randomly oriented particles at the foetal stage, and highly aligned, much longer particles after birth. Moreover, a part of the Ca seemed to be present in a form other than HA at all stages of development. The bone mineral content in bone samples with nanohydroxyapatite and HA spheres were also investigated by Gasperini et al.397 using μ-SRXRF. Their findings suggested that HA-based biomaterials were biocompatible, promoted osteoconduction and favoured bone repair. Iranian researchers398 evaluated the subcutaneous connective tissue reaction of rats to three bioactive glass nanopowders, which were reported to be promising bone substitutes and tissue regeneration matrices. Characterisation techniques such as TEM, XRD and XRF were utilised to carry out the phase analysis and to study the structure, particle size and composition of the synthesized bioactive glasses. The obtained results indicated that biocompatible 58S and 63S bioactive glass nanopowders with antibacterial activities could be synthesized for the treatment of osseous defects. Finally, Stanimirova et al.399 assessed the effects of anticancer treatment with cyclophosphamide and cytarabine during pregnancy on the mineralisation of mandible bones in 7-, 14- and 28-day-old rats. The mineral composition of each bone sample was determined using XRF spectrometry. Using the ANOVA-simultaneous component analysis methodology adapted for unbalanced data, the results showed that treatment with cyclophosphamide and cytarabine during pregnancy induced a decrease in the K and Zn levels in the mandible bones of newborns. This suppressed the development of mandible bones in rats in the early stages (up to 14 days) of formation. An interesting observation was that the levels of essential minerals like Ca, K, Mg and Na varied considerably in the different regions of the mandible bones.
Strontium ranelate has been approved in several countries for the treatment of postmenopausal osteoporosis. Pemmer et al.400 studied how Sr uptake was influenced by dietary Ca deficiency as well as by the formula of Sr administration. Vertebral bone tissue of ovariectomised calcium-deficient rats treated with strontium ranelate or strontium chloride was analysed using confocal SRXRF and backscattered electron imaging. The study clearly showed that inadequate nutritional Ca intake significantly increased uptake of Sr in serum as well as in trabecular bone matrix. The distribution of selected elements in atherosclerotic plaques of apoE/LDLR-double knockout mice subjected to dietary and subsequent pharmacological treatments with perindopril was investigated by Gajda et al.401 using μ-SRXRF. In animals fed an egg-rich diet, significantly higher concentrations of Ca and significantly lower contents of Cl, Cu, Fe, S, Se and Zn in atheromas were seen in comparison with chow diet-fed animals. Perindopril showed its potency to reduce atherosclerosis, as estimated by the size of the atheroma and content of pro- and anti-atherogenic elements.
Lead deposition on enamels while dental caries was developing, was studied by Molina et al.402 using μ-SRXRF. The Pb distribution was evaluated in bovine enamel slabs, after adding lead acetate salt and submitted to a pH-cycling regime simulating the dental caries process. After the pH cycling, 100 μm sections of the slabs were analysed by polarising microscopy, to observe the extent of caries-like lesions, and these sections were used for Pb estimation by μ-SRXRF. Caries lesions were observed along all superficial enamel surfaces to an extent of 120 μm. A Pb concentration gradient was observed in enamel, which decreased towards the dentine. This study suggested that if Pb is present in the oral environment, it might deposit in enamel during the caries process. Soares et al.403 investigated the effects of heating by steam autoclaving and Er:YAG laser etching on dentin components. The dentin was exposed on bovine incisors and subsequently autoclaved or treated with thymol. The surface of the dentin, divided in four areas, was etched with either phosphoric acid or irradiated with an Er:YAG laser (subgroups: I-80 mJ, II-120 mJ and III-180 mJ). Elemental distribution maps of Ca and P were performed by μ-EDXRF, reflecting the most homogeneous distribution of both Ca and P for the thymol/phosphoric acid treatment, whilst Er:YAG laser irradiation produced a heterogeneous Ca and P distribution throughout the dentin surface with areas of increased Ca concentration. Stock et al.404 investigated the spatial distribution of carbonated apatite mineral and elemental Ca (and other cations including Zn) around dentin tubules using simultaneous diffraction and fluorescence mapping with a 250 nm, 10.1 keV synchrotron X-ray beam. The authors were convinced that an extension of X-ray mapping from near 1 pm resolution to the 250 nm level, performed for dentin and its tubules, would provide a new understanding of other mineralised tissues.
A remarkable study dealing with the possible role of Ti in the genesis of the yellow nail syndrome was examined by Berglund and Carlmark.405 Performing EDXRF analyses of nail clippings, Ti was regularly found in finger nails of patients but not in control subjects. The Ti ions were derived from titanium implants in teeth or elsewhere in the body and/or from titanium dioxide in drugs and confectionary. These findings showed that the yellow nail syndrome was associated with the presence of titanium. A calibration method for XRF measurements of As and Se in human nail clippings was demonstrated by Gherase and Fleming.406 Using a portable X-ray tube and a detector unit, experimental X-ray spectra were acquired from phantom nail clippings containing equal concentrations of As and Se ranging from 0 to 20 μg g−1 in increments of 5 μg g−1. A semi-empirical relationship between the mass of the nail phantoms and the slope of the calibration line was determined separately for As and Se to estimate elemental concentrations and their uncertainties from the XRF spectra of human nail clippings.
The concentration of Gd was determined by means of TXRF in urine and blood plasma samples, taken from magnetic resonance imaging (MRI) patients during a period of up to 20 hours after the administration of Gd-based MRI contrast agents.407 A limit of detection of 100 μg L−1 in urine and 80 μg L−1 in blood plasma was obtained. The strength of the TXRF technique was once again proven, underlined by the simplicity of the method and the ability for fast monitoring Gd in human body fluids on a daily routine in clinical laboratories. Ray et al.408 studied the elemental profile in blood samples from 60 patients with leukoplakia and oral submucous fibrosis using EDXRF. Of the 16 detected elements, alteration in element profile was observed for Br, Co, Fe, Mn and Zn. While Br, Fe and Zn reflected similar changes by showing gross depletion in both the diseased groups, Co and Mn depicted an inverse pattern of alterations in their concentrations in the two types of precancerous disorders when compared with the control subjects. Brazilian researchers409 performed analyses of whole blood samples of Crioula breed horses, used for antivenom production and therefore of great importance in the public health programme. From the EDXRF results, and compared with NAA results, reference interval values were determined for the elements Na (1955–2013 mg kg−1), Mg (51–75 mg kg−1), Ca (202–213 mg kg−1), Cl (2388–2574 mg kg−1), Cu (4.1–4.5 mg kg−1), K (1649–1852 mg kg−1), P (523–555 mg kg−1), S (1628–1730 mg kg−1) and Zn (2.4–2.8 mg kg−1).
Another interesting application dealing with the determination of Cu, Se and Zn in seminal plasma of men with variocele was conducted by Camejo et al.410 TXRF measurements of seminal fluids of patients with variocele showed only a decrease of the Se concentration which could be associated with detriment of seminal parameters (e.g. spermatozoa concentrations, mobility and morphology). No difference was observed for both Cu and Zn.
3.11 Drugs
The production of counterfeited drugs is a criminal problem that worldwide carries serious risks to public health. In Brazil, Viagra® and Cialis® are the most counterfeit medicines, being used to treat problems related to erectile dysfunction. Ortiz et al.411 showed that XRF was an excellent analytical technique for the semi-quantitative determination of active ingredients (in case of sildenafil citrate, which presents S in its structure) and excipients such as calcium phosphate, titanium oxide and iron oxide (Ca, Fe, P and Ti). From 41 commercial samples and 56 counterfeit samples, the chemical fingerprinting was estimated from the XRF data and the matrix data were allied to chemometric methods (Principal Component Analysis and Hierarchical Cluster Analysis) to successfully classify the tablets investigated into authentic and counterfeit groups. Romao et al.412 worked out a methodology using various techniques to distinguish meta-chlorophenylpiperazine (m-CPP) tablets, a new illicit drug that has been sold as ecstasy tablets, from tablets containing amphetamines (mainly 3,4-methylenedioxymethamphetamine (MDMA)). XRF measurements identified Ca, Cl, Cu, Fe and K as inorganic ingredients present in the m-CPP tablets. In contrast, higher Cl concentrations and a more diverse set of elements (Ca, Cu, Cl, Fe, Hf, Ti, P, Pt, V, Zn and Zr) were found in MDMA tablets. Principal component analysis applied to XRF data divided samples into three groups: m-CPP tablets (four samples), MDMA tablets (twenty three samples), and tablets with no active ingredients (three samples). The use of confocal μ-XRF as a new tool for the non-destructive study of the elemental distributions in pharmaceutical tablets, was evaluated by Mazel et al.413 Based on two different examples, it was shown that the distribution of several inorganic elements (Cu, Fe, Mn, Ti, Zn) from the surface to a depth of several hundred micrometres under the surface could be measured. An original method to correct for absorption effects, to measure accurately the true elemental distribution, was proposed. Moreover, by using the presence of titanium dioxide in a pharmaceutical coating, the authors proved that this technique was also suited to the non-destructive measurement of coating thickness.Finally, a comprehensive review of the current state of the art in analytical methods to detect heavy metals in herbal medicines, including XRF spectrometry, was given by Yuan et al.414 A detailed description was provided of the different techniques together with some application examples.
3.12 Biological
Imaging of elements and molecules in biological tissues and cells in the low-micrometre and nanometre range is of particular interest in the life science. A review by Wu and Becker415 underlined the fact that analytical techniques supporting chemical imaging are under intensive development with respect to higher spatial resolution and higher sensitivity and accuracy. The state of the art of both advanced mass spectrometric techniques and non-mass spectrometric techniques, such as XRF, were highlighted. An overview of the metallometabolomic methodology for metal-based drug metabolism was presented by Ge et al.416 This review discussed the concept of this methodology with a focus on analytical techniques and methods, including XRF.Several contributions elucidated element distributions in animal samples using SR. Rao et al.417 presented the results obtained with a new hard X-ray microspectroscopy beamline facility, X27A, available at NSLS, BNL, USA, for elemental mapping. With a primary beam spot size of 10 μm and a high flux throughput, the elements Cr, Cu, Fe, Mn, Ti and Zn were measured using a liquid-nitrogen-cooled 13-element energy-dispersive high-purity germanium detector. The sample was scanned in a ‘step-and-repeat’ mode for fast elemental mapping measurements and generated elemental maps at 8, 10 and 12 keV, from a small animal shell (snail). The accumulated trace elements, from these biological samples, in small areas have been identified. Biologic rhythms derived from Siberian mammoths' hair were compared with those of modern human hair by Spilde et al.418 Electron microprobe analysis, confocal microscopy and scanning electron microscopy gave information about the mineral content of mammoths' hair and the preservation of the cuticle. Moreover, μ-XRF and XRF μ-CT analyses allowed evaluation of the metal distribution and a visualisation of hollow tubes in mammoths' hairs. Seasonal variations in the Cu and Fe content combined with spectral analyses gave insights into variations in food intake of the animals. Nakazawa et al.419 investigated the Ag speciation in the livers of five species of marine mammals using XAFS and XRF. These results revealed the formation of Ag2Se or Ag2S which might depend on the Hg levels in the liver. In liver samples with relatively high Ag/Hg ratio Ag2Se was observed, whereas liver samples with low Ag/Hg ratio contained Ag2S. In a second contribution420 the presence of mercury selenide in various tissues of the striped dolphin was studied using μ-XRD, μ-XRF and XAFS techniques. Analysis by XAFS confirmed the presence of HgSe in all the tissues examined, suggesting that Se would be involved in the detoxification process of Hg in various tissues other than the liver. The contribution of HgSe seemed to be large especially in the liver and spleen but relatively small in the kidney, pancreas and brain, because the proportion of insoluble fraction containing HgSe was lower in these tissues (25 to 46%).
In situ imaging of metal distributions at physiologically relevant concentrations in highly hydrated biological systems is technically challenging, as samples suffer both radiation damage and dehydration during lengthy analysis. The heightened potential of SRXRF μ-CT using a new generation of fast fluorescence detectors coupled with powerful data acquisition approaches, was proven by Lombi et al.421 by measuring the distribution of Ni and Zn in hydrated plant roots. Although 3D tomography was still impeded by radiation damage, 2D tomograms of hydrated plant roots exposed to environmentally relevant metal concentrations for short periods of time, were successfully collected. Turkish researchers422 investigated the changes in inorganic constituents of plants (chickpea leaves) exposed to mammalian sex hormones using WDXRF. In all of the concentrations tested, the treated samples reflected a significant increase in the content of Ca, Cu, Fe, K, Mg, Na, Ni, P, S and Zn, while only Cl and Mn contents decreased.
To conclude this biological review section, a few interesting biological applications are highlighted. Evens et al.423 investigated the hypothesis that dietary Zn toxicity was the result of selective accumulation in tissues that were involved in reproduction. Tissue-specific Zn distribution of the freshwater invertebrate Daphnia magna, exposed to various concentrations of Zn, was quantified by confocal SRXRF. Their findings emphasized that the effects of dietary Zn exposure were interactive with waterborne Zn exposure. Moreover, the XRF technique enabled the researchers to provide possible links between the tissue-specific bioaccumulation and reproductive effects of Zn. Synchrotron X-ray fluorescence microscopy analysis was used by Lye et al.424 to detect changes in Cu levels of two different Drosophila tissues, the larval wing imaginal disc and sectioned adult fly heads, changes caused by targeted manipulation of known copper homeostasis genes. Krejci et al.425 performed research on the desmid green algae Closterium moniliferum, an organism that forms barite (BaSO4) or celestite (SrSO4) biominerals. The ability to sequester Sr in the presence of an excess of Ca is of considerable interest for the remediation of 90Sr from the environment and nuclear waste. The authors investigated how Ba, Ca and Sr were transported in C. moniliferum and how precipitation of (Ba,Sr)SO4 crystals occurred in the terminal vacuoles, using XRF and μ-XANES. The results obtained showed that engineering the sulfate concentration in the vacuole might be the most direct way to increase the Sr sequestered per cell, an important consideration in using desmids for phytoremediation of 90Sr. Portable XRF was used by Mascari et al.426 to evaluate the use of the trace element Rb as a long-lasting systemic biomarker for bloodfeeding females of the sand fly Phlebotomus papatasi Scopoli. Rubidium was detected in all sand flies that fed on Rb-treated hamsters for at least 14 days post-blood meal. These results underlined the potential that Rb marking could be used as a technique for evaluating rodent-targeted sand fly control methods and in ecological studies of sand flies. Readers searching for additional clinical and biological applications may take a look at our companion ASU review on Clinical and biological materials, foods and beverages.4
3.13 Thin films, coatings and nano-materials
Dendooven et al.427 reported in situ XRF measurements during nucleation and growth of TiO2 on planar substrates and in nanoporous films using SRXRF. The Ti uptake was monitored during deposition of TiO2 in nanoporous silica films. In mesoporous films, the Ti content varied quadratically with the number of cycles, a behaviour that was attributed to a decreasing surface area with progressing deposition. Mainz and Klenk428 investigated the in situ analysis of elemental depth distributions in CuInS2 thin films by combined evaluation of SRXRF and energy dispersive diffraction during the reactive annealing of the films in a sulfur atmosphere. The time evolution of phases in the films was determined from the observed diffraction signals. This phase information was then linked to the depth distributions of the elements in the films. For this latter step, the fluorescence intensities for a given set of depth distributions were numerically calculated. Influences of lateral non-uniformities of the films, as well as the accuracy limits of the method, were also investigated. Dill and Rössiger429 compared the performance of XRF instruments with different detector systems (proportional counter, positive intrinsic negative and Si drift detectors) for measuring thin Au and Pd coatings and investigated different ways of background treatment. The authors found that the well-established X-ray instrumentation for coating thickness measurement, with proportional counter detectors, was not suitable for measuring ∼100 nm coatings of gold and palladium due to the poor energy resolution of the proportional counters. Systems with semiconductor detectors achieved more reliable results with a significantly higher accuracy. A correct background treatment was found to be especially important for very thin coatings. The authors concluded if small measuring spots (e.g. 150 μm) have to be measured with semiconductor detector systems, special X-ray optics have to be used to obtain an intensity comparable to that offered by proportional counter devices. In the region below 100 nm, measurement uncertainties of less than 1 nm were achieved. Torres et al.430 used XANES and GIXRF to investigate the electronic structure of ZnFe2O4 thin films. XANES was used to determine the nonequilibrium cation site occupancy as a function of depth and oxygen pressure during deposition. It was found that low deposition pressures, below 10−3 mbar, cause iron super-occupation of tetrahedral sites without Zn2+ inversion, resulting in an ordered magnetic phase with high room-temperature magnetic moment. Devloo-Casier et al.431 studied the initial growth of HfO2 by means of SRXRF and grazing incidence small angle X-ray scattering (GISAXS). HfO2 was deposited by atomic layer deposition (ALD) using tetrakis(ethylmethylamino)hafnium and H2O on both oxidised and H-terminated Si and Ge surfaces. XRF quantified the amount of deposited material during each ALD cycle and showed an inhibition period on H-terminated substrates. No inhibition period was observed on oxidised substrates. The evolution of film roughness was monitored using GISAXS. A correlation was found between the inhibition period and the onset of surface roughness.A new method of elemental depth profiling was developed by Iida,432 by using a thin Mo wire and μ-XRF technique. In the proposed approach the thin wire was positioned close to the sample surface in the sample-detector radiation path with the incident microbeam and the sample-detector radiation paths at right angles. When a layered sample was scanned in a direction perpendicular to the sample surface, the wire shadowed the emitted XRF radiation at certain sample positions producing a depth profile of XRF emission. A similar depth profile was obtained without scanning the sample by replacing the standard XRF detector with and X-ray sensitive CCD camera. The minimum spatial resolution was obtained with a Mo wire of about 15 μm in diameter. Compared with a confocal depth-profiling method, wire depth-profile analysis was reported to be easy to implement, flexible, and has reasonable sensitivity.
Biofilms were analysed by several groups this year, thus Chen et al.433 studied the sorption and distribution of Cu in unsaturated Pseudomonas putida CZ1 biofilms by μ-SRXRF. The spatial and temporal distributions of metals were determined and it was found that Ca, Fe and Mn were mainly distributed near the air–biofilm interface of a film grown on 40 m mol L−1 citrate, while there were two Ca-, Fe- and Mn-rich layers within a biofilm grown on 10 m mol L−1 citrate. The sorption of Cu by biofilm grown in medium containing 10 m mol L−1 citrate was rapid, with Cu being found throughout the film after only 1 h exposure. Copper initially co-localised with Fe and Mn layers in the film and then precipitated in a 40 μm thick layer near the air–biofilm interface when exposed for 12 h. Cu K-edge XANES analysis revealed that Cu was primarily bound with citrate within the biofilm with a precipitate most similar to copper phosphate. Staining revealed that cells at the biofilm–membrane interface were mostly alive even when the copper concentration reached 80.5 mg copper per g biomass. Yang et al.434 reported the biotransformation of As and Se in multi-species biofilm. Arsenic and selenium are both elements of concern especially when released into the environment by anthropogenic activity. Biofilms, or communities of micro-organisms, can play important roles in bio-transforming elements to less toxic chemical forms. The authors studied novel tools to characterise the fate of oxyanions (selenate, selenite, arsenate or arsenite) in multi-species biofilms inoculated from a source receiving coal mining effluent. Confocal laser scanning microscopy (CLSM) demonstrated a distinct biofilm morphology at elevated oxyanion concentrations. Selenium and arsenic K near-edge XAS showed biofilm transformation of oxyanions. Micro-XRF imaging revealed highly localised reduced selenium species in the biofilm. Biofilms can both detoxify and sequester selenium and arsenic, playing a critical role in their fate in aquatic environments. Qu et al.435 evaluated the in vivo fate and physiological behaviour of quantum dots (QDs) in Caenorhabditis elegans by green fluorescent protein transfection, fluorescent imaging, synchrotron radiation based elemental imaging, and speciation techniques, including μ-XRF and μ-XANES. The in situ metabolism and degradation of QDs in the alimentary system and long-term toxicity on reproduction highlighted the use of the C. elegans model as a multi-flexible platform to allow non-invasive imaging and in vivo monitoring of the consequences of engineered nanomaterials.
Qu et al.436 critically reviewed SR and related nuclear analytical techniques for the study on biological effects of nanomaterials (NMs), especially toxicological or biological behaviours in biological systems, along with their advantages and limitations. The techniques included SRXRF (XAFS, XANES and EXAFS), SR circular dichroism spectroscopy, ICP-MS, NAA, and isotopic tracing. These novel techniques will help to lead a better understanding of the biological effects of NMs. Marmorato et al.437 determined the cellular distribution and degradation of CoFe2O4 nanoparticles in Balb/3T3 mouse fibroblasts by SRXRF. In cells exposed to low concentrations of CoFe2O4, the nanoparticles were found to preferentially segregate in the perinuclear region preserving their initial chemical content. At concentrations exceeding 500 μM the XRF spectra indicated the presence of Co and Fe also in the nuclear region, accompanied by changes in the cellular morphology. The increase of the Co/Fe ratio measured in the nuclear compartment indicated that above certain concentrations the CoFe2O4 NPs intracellular distribution could be accompanied by biodegradation resulting in Co accumulation in the nucleus. Morishita et al.438 reported the detection of titanium dioxide particles in frozen tissue sections using SRXRF. Recent studies of the in vivo absorption and biological influence of particulate matter, especially nanomaterials have raised worldwide concerns over their safety. However, it is often technically difficult to conduct these studies because NMs are too small to be observed by optical microscopy. The authors established a new method to visually detect NMs on the surface tissue samples. Titanium dioxide particles with a diameter of 5 μm frozen tissue sections have been analysed by SRXRF. Such particles are widely used by the cosmetic industry.
Research in nanolayer technology was reported by Unterumsberger et al.439 They performed complementary characterisation of buried nanolayers by quantitative XRS under conventional and grazing incidence conditions. A comparison of reference-free XRF under conventional and grazing incidence conditions offers complementary information with respect to quantification reliability, elemental sensitivity, and layer sequences. Buried boron-carbon layers with nominal thicknesses of 1, 3, and 5 nm were examined using monochromatised undulator radiation in the laboratory of the Physikalisch-Technische Bundesanstalt (PTB) at the synchrotron radiation Facility BESSY II, Germany. The results for the two beam geometries were compared and showed good agreement, thus encouraging the complementary use of both methodologies. Segura-Ruiz et al.440 investigated nano-XAS of single cobalt-implanted ZnO nanowires. The authors reported the local structure of single Co-implanted ZnO nanowires studied by using a hard X-ray nanoprobe. X-ray fluorescence maps showed uniform Zn and Co distributions along the wire within the length scale of the beam size. The XRF data allowed the estimation of the Co content within the nanowire. Polarisation-dependent XANES showed no structural disorder induced neither in the radial nor axial directions of the implanted nanowires after subsequent annealing. Co2+ ions occupied Zn sites into the wurtzite ZnO lattice. EXAFS data revealed high structural order in the host lattice without distortion in their interatomic distances, confirming the recovery of the radiation-damaged ZnO structure through thermal annealing.
3.14 Chemical state and speciation
Several authors used the intensity ratio of fluorescence line families for speciation. Durham et al.441 studied the Kβ/Kα intensity ratio of Cl for various salts with EDXRS and found that the ratio of the peak intensity was sensitive to the local chemical environment of the chlorine atoms and that a periodic trend for these salts could be observed. Sokaras et al.442 reported the investigation of the cascade L-shell X-ray emission as an incident polarised and unpolarised monochromatic radiation overpass the 1s ionization threshold for the metallic iron by means of moderate resolution, quantitative X-ray spectrometry. A full ab initio theoretical investigation of the L-shell X-ray emission processes was performed. The agreement obtained between experiments and the theory was discussed with respect to the accuracy of the advanced atomic models. Porikli and Kurucu443 compared an external magnetic field effect and chemical effect on X-ray Kβ/Kα intensity ratio and line-shape of some Cr compounds using EDXRS. The samples were located in an external magnetic field of 0.6 T and 1.2 T. The results showed that the Kβ/Kα intensity ratios, chemical shifts, could change when irradiation was conducted in a magnetic field. An interesting approach using satellite peaks for speciation of Cr was presented by Tsuyumoto and Maruyama.444 A Kβ satellite peak was observed in XRF spectra accompanying the pre-edge XANES peak. In the Kβ emission of CrVI compounds, a small satellite peak was observed in the region 5.983 to 5.988 keV together with the main peak at 5.947 keV, while CrIII compounds showed only the main peak at 5.947 keV. This corresponded to the fact that the pre-edge peak in XANES was observed only for the CrVI compounds. The electronic energy level linked to the satellite peak was almost at the same energy as the level causing the pre-edge peak. The authors claimed that their findings not only affected the interpretation of the origin of the pre-edge peaks but also led to a simple speciation method of Cr compounds using XRF.The combination of SRXRF and XAS for comprehensive characterisation of samples was reported by several authors. Silversmit et al.,445 described the 3D Fe speciation of an inclusion cloud within an ultra-deep diamond by confocal μ-XANES and found this was evidence of late stage thermal overprint. An assembly of 1 to 20 μm sized mineral inclusions located within an “ultra-deep” diamond from Rio Soriso (Juina area, Mato Grosso State, Brazil) had been studied with confocal μ-XANES at the Fe and Mn K-edges. This technique allowed a 3D nondestructive speciation of the Fe and Mn-containing minerals within the inclusion cloud. The observed Fe-rich inclusions were identified to be ferropericlase (Fe, Mg)O, hematite, and a mixture of these two minerals. Confocal μ-XRF further showed that Ca-rich inclusions were present as well, spatially separated or in close contact with the Fe-rich inclusions. The inclusions were found to be aligned on a plane, which most likely represented a primary growth zone. The 3D distribution indicated a likely fluid overprint along an open crack. The authors claimed that their results implied that an imposed negative diamond shape of an inclusion alone did not exclude epigenetic formation or intense late stage overprint. Micro-XAS/XRF and thermodynamic study of CeIII/IV speciation after long-term aqueous alteration of simulated nuclear waste glass was reported by Curti et al.446 The relevance for predicting Pu behaviour was discussed. In the study, the dissolution and mobilization of Ce, introduced in a simulated nuclear waste glass as a surrogate of Pu, was investigated after leaching in pure water at 90 °C and pH of about 9.6. The microscopic distribution and oxidation state of Ce in the altered glass were studied using μ-XRF mapping techniques and μ-XANES. Distribution maps of CeIII and CeIV were obtained by recording the Lα fluorescence emission at two different incident X-ray energies, coinciding with the maximum contrast between CeIII and CeIV fluorescence intensities. The μ-XRF maps revealed that Ce was dominantly present as oxidized species of CeIV in the original glass. After leaching from the glass matrix, CeIV was partly reduced and re-immobilized as CeIII at grain boundaries or in the interstitial spaces between the glass particles. The concentration of CeIII was found to correlate with the spatial distribution of secondary Mg-clay formed during the aqueous corrosion as the main glass alteration product. Micro-XANES spectra collected at locations representative to both altered and non-altered glass domains confirmed the findings obtained by the redox mapping. Because the redox-sensitive elements (Fe, Cr, Se) in the pristine simulated nuclear waste glass occur almost exclusively as oxidized species, reduction of CeIV was probably mediated by an external source of reductants. The authors concluded that Ce was not a good chemical analogue of Pu, in spite of its wide use as its surrogate in simulated radioactive waste. Mayhew et al.447 reported microscale imaging and Fe speciation during fluid–mineral reactions under highly reducing conditions. The oxidation state speciation and distribution of Fe are critical determinants of Fe reactivity in natural and engineered environments. Dynamic changes in Fe speciation in environmental systems during progressive fluid mineral interactions were observed. Two common geological and aquifer materials, basalt and FeIII oxides were incubated with saline fluids at 55 °C under highly reducing conditions maintained by the presence of Fe0. The authors tracked changes in Fe speciation after 48 h and 10 months using μ-SRXRF maps collected at multiple energies within the Fe K-edge. After 48 h, the major Fe-bearing components of the samples (FeIII oxides, basalt, and rare olivine) were successfully identified and mapped. After 10 months, the FeIII oxides remained stable in the presence of Fe0, whereas significant alteration of basalt to minnesotaite and chlinochlore occurred, providing new insights into heterogeneous Fe speciation in complex geological media under highly reducing conditions.
As the nitridation of SiO2/SiC interface has shown great promise as a means of achieving high quality gate oxides for SiC structures, therefore its characterisation is of critical importance. Hu et al.448 characterised SiO2/SiC interface after nitridation treatment. A SiO2/SiC structure was prepared by direct oxidation in nitrous oxide (N2O), followed by a nitric oxide (NO) post-annealing. Using XAS of Si L- and K-edges, recorded simultaneously in the surface sensitive total electron yield and the interface/bulk sensitive fluorescence yield modes, the authors investigated the SiO2/SiC interface of a series of samples after the nitridation treatment. The results showed that nitridation introduced nitrogen into the SiO2/SiC interface to form silicon nitride (Si N bonds). Oxygen was also possibly incorporated into SiO2/SiC interface in the oxynitride form. The great sensitivity of XAS in probing Si, SiC, SiO(2) and SiN(x) at different depths was also demonstrated. Kikuchi et al.449 applied μ-SRXRF/SR-XAFS to the speciation of Fe on a single stalk in bacteriogenic iron oxides (BIOS). Micro-XRF analysis of the stalk samples showed that Fe precipitated around the stalk. All the μ-XANES spectra at several Fe-rich parts showed similar spectra. The authors claimed that the combined use of μ-SRXRF/SR-XAFS was a powerful tool for chemical speciation of metals in single-cell metal-bearing bacteria. Tamenori et al.450 reported a 2D approach to fluorescence yield XANES measurement using a silicon drift detector. 2D-XANES measurements were achieved by using a silicon drift detector as an energy-dispersive fluorescence detector allowing the full survey of X-ray fluorescence data that are lost in conventional measurements. The availability of a map approach was demonstrated by applying it to XANES measurements in both the diluted (Mn-doped nano-diamond) and concentrated (MnO crystal) manganese samples. The 2D approach clearly distinguished between the spectra of Mn and O atoms, where absorption edges of both elements are close to each other.
In recent years, the relevance of physico-chemical heterogeneity patterns in soils at the micron and sub-micron scale for the regulation of biogeochemical processes has become increasingly evident. Prietzel et al.451 described microheterogeneity of element distribution and sulfur speciation in an organic surface horizon of a forested Histosol as revealed by μ-SRXRF. For an organic surface soil horizon from a forested Histosol in Germany, microspatial patterns of element distribution (Al, P, S and Si) and S speciation were investigated by μ-SRXRF. Microspatial patterns of Al, P, S, and Si contents in the organic topsoil were assessed in a sample region of 50 × 30 μm2 by spatially resolved μ-XRF. Sulfur speciation at four microsites was investigated by μ-XANES at the S K-edge. The results showed a heterogeneous distribution of the investigated elements at the sub-micrometre scale, allowing the identification of diatoms, aluminosilicate mineral particles and sulfide minerals in the organic soil matrix. Evaluation of the S K-edge μ-XANES spectra acquired at four different microsites by linear combination-fitting revealed a substantial microspatial heterogeneity of S speciation, characterised by the presence of distinct enrichment zones of inorganic sulfide and zones with dominant organic disulfide S within a few micrometers distance, and a coexistence of different S species (e.g., reduced inorganic and organic S compounds) at a spatial scale below the resolution of the instrument (60 × 60 nm2; X-ray penetration depth 30 μm). The first results for determination of the oxidation state of several iron samples by means of Raman scattering spectroscopy (RRS) were reported by Leani et al.452 The changes existing in the RRS structure between Fe and its oxides were clearly discriminated, suggesting chemical environment characterisation by RRS spectroscopy using an energy-dispersive system combined with synchrotron radiation.
4. Abbreviations
| 2D/3D | 2 dimensional/3 dimensional |
| AAS | Atomic absorption spectrometry |
| AD | Anno domini |
| ADC | Analog-to-digital converter |
| AFM | Atomic force microscopy |
| ALD | Atomic layer deposition |
| ANOVA | Analysis of variance |
| ApoE/LDLR | Apolipoprotein E/low density lipoprotein receptor |
| ARO | Adaptive region-of-interest |
| ASIC | Application-specific integrated circuit |
| ASTM | American Society for Testing and Materials |
| ASU | Atomic Spectrometry Updates |
| AUV | Autonomous underwater vehicle |
| BC | Before Christ |
| BIOS | Bacteriogenic iron oxides |
| CCD | Charge coupled detector |
| CFC | Chlorofluorocarbon |
| CLSM | Confocal laser scanning microscopy |
| CMOS | Complementary metal oxide semiconductor |
| CPP | Chlorophenylpiperazine |
| CRM | Certified reference material |
| CT | Computer tomography |
| DBDE | Decabrominated diphenyl ether |
| DDGS | Dried distiller's grains with solubles |
| DMA | Dimethylarsinic acid |
| ED | Energy dispersive |
| EDS | Energy dispersive X-ray spectrometry |
| ED-SEM | Energy dispersive scanning electron microscopy |
| EDTA | Ethylenediaminetetraacetic acid |
| ED-TEM | Energy dispersive transmission electron microscopy |
| EDXRF | Energy dispersive X-ray fluorescence |
| EDXRS | Energy dispersive X-ray spectrometry |
| EPA | Environmental protection agency |
| EPMA | Electron probe microanalysis |
| EPR | Electron paramagnetic resonance |
| ERL | Energy recovery linac |
| ESRF | European synchrotron radiation facility |
| EXAFS | Extended X-ray absorption fine structure |
| FTIR | Fourier transform infrared |
| FWHM | Full width at half maximum |
| GF-AAS | Graphite furnace atomic absorption spectrometry |
| GEXRF | Grazing exit X-ray fluorescence |
| GISAXS | Grazing incidence small angle X-ray scattering |
| GIXRF | Grazing incidence X-ray fluorescence |
| GSJ | Geological Survey of Japan |
| HA | Hydroxyapatite |
| HF | Hydrogen fluoride |
| HPLC | High performance liquid chromatography |
| HSL | Health and Safety Laboratory |
| IC-ICP-MS | Ion chromatography inductively coupled plasma mass spectrometry |
| ICP-AES | Inductively coupled plasma atomic emission spectrometry |
| ICP-MS | Inductively coupled plasma mass spectrometry |
| ICP-AES | Inductively coupled plasma atomic emission spectrometry |
| ICP-OES | Inductively coupled plasma optical emission spectrometry |
| INAA | Instrumental neutron activation analysis |
| IR | Infrared |
| IR/VIS | Infrared/visible spectrophotometry |
| ISO | International organization for standardisation |
| LA-ICP-MS | Laser ablation inductively coupled plasma mass spectrometry |
| LED | Light-emitting diode |
| MDMA | 3,4-Methylenedioxymethamphetamine |
| MMA | Monomethylarsonic acid |
| MOSFET | Metal-oxide-semiconductor field-effect transistor |
| MRI | Magnetic resonance imaging |
| NAA | Neutron activation analysis |
| NIST | National Institute of Standards and Technology |
| NMR | Nuclear magnetic resonance |
| NM | Nanomaterial |
| NP | Nanoparticle |
| PC | Personal computer |
| PET | Polyethyleneterephthalate |
| PGE | Platinum group element |
| PIGE | Particle-induced gamma ray emission |
| PIXE | Particle-induced X-ray emission |
| PL | Photo luminescence |
| PM | Particulate matter |
| QCM | Quartz crystal microbalance |
| QD | Quantum dot |
| REE | Rare earth elements |
| RIXS | Resonant inelastic X-ray scattering |
| RRS | Resonant Raman scattering spectroscopy |
| SDD | Silicon drift detector |
| SE | South east |
| SEM | Scanning electron microscopy |
| SIMS | Secondary ion mass spectrometry |
| SRM | Standard reference material |
| SR | Synchrotron radiation |
| SR-TXRF | Synchrotron radiation total reflection X-ray fluorescence |
| SR-XAFS | Synchrotron radiation X-ray absorption fine structure |
| SR-XANES | Synchrotron radiation X-ray absorption near edge structure |
| SR-XAS | Synchrotron radiation X-ray absorption spectroscopy |
| SRXRF | Synchrotron radiation X-ray fluorescence |
| TEM | Transmission electron microscopy |
| TOF | Time-of-flight |
| TOF-SIMS | Time-of-flight secondary ion mass spectrometry |
| TXM | Transmission X-ray microscopy |
| TXRF | Total reflection X-ray fluorescence |
| UK | United Kingdom |
| US | United States |
| USA | United States of America |
| UV | Ultraviolet |
| UV-VIS | Ultraviolet-visible spectrophotometry |
| WASP | Workplace analysis scheme for proficiency |
| WD-SEM | Wavelength dispersive scanning electron microscopy |
| WDXRF | Wavelength dispersive X-ray fluorescence |
| WHO | World Health Organisation |
| XAFS | X-ray absorption fine structure |
| XANES | X-ray absorption near edge structure |
| XAS | X-ray absorption spectroscopy |
| XFCT | X-ray fluorescence computer tomography |
| XFM | X-ray fluorescence microscopy |
| XPS | X-ray photoelectron spectroscopy |
| XRD | X-ray diffraction |
| XRF | X-ray fluorescence |
| XRR | X-ray reflectometry |
| XRS | X-ray spectrometry |
| XSW | X-ray standing waves |
| YAG | Yttrium aluminium garnet |
| Z | Atomic number |
References
- M. West, A. T. Ellis, P. J. Potts, C. Streli, C. Vanhoof, D. Wegrzynek and P. Wobrauschek, J. Anal. At. Spectrom., 2011, 26(10), 1919–1963 RSC
.
- S. Carter, A. S. Fisher, P. S. Goodall, M. W. Hinds, S. Lancaster and S. Shore, J. Anal. At. Spectrom., 2011, 26(12), 2319–2372 RSC
- O. T. Butler, W. R. L. Cairns, J. M. Cook and C. M. Davidson, J. Anal. At. Spectrom., 2012, 27(2), 187–221 RSC
- A. Taylor, S. Branch, M. P. Day, M. Patriarca and M. White, J. Anal. At. Spectrom., 2011, 26(4), 653–692 RSC
- E. H. Evans, J. A. Day, C. D. Palmer and C. M. M. Smith, J. Anal. At. Spectrom., 2011, 26(6), 1115–1141 RSC
- C. F. Harrington, R. Clough, L. R. Drennan-Harris, S. J. Hill and J. F. Tyson, J. Anal. At. Spectrom., 2011, 26(8), 1561–1595 RSC
- M. Cotte and J. Susini, Actual. Chim., 2011,(356–357), 113–115 CAS
- U. E. A. Fittschen and G. Falkenberg, Anal. Bioanal. Chem., 2011, 400(6), 1743–1750 CrossRef CAS
- J. Molloy and J. Sieber, X-Ray Spectrom., 2011, 40(4), 306–314 CrossRef CAS
- P. T. Palmer, J. Chem. Educ., 2011, 88(7), 868–872 CrossRef CAS
- A. Kuczumow and P. Wolski, Pramana, 2011, 76(2), 213–221 CrossRef
- M. Sudarshan, S. S. Ram, S. Majumdar, J. P. Maity, J. G. Ray and A. Chakraborty, Pramana, 2011, 76(2), 241–247 CrossRef
- G. Grindlay, J. Mora, L. Gras and M. T. C. de Loos-Vollebregt, Anal. Chim. Acta, 2011, 691(1–2), 18–32 CrossRef CAS
- A. G. Revenko, J. Anal. Chem., 2011, 66(11), 1059–1072 CrossRef CAS
- J. Kawai and S. Hayakawa, Adv. X-Ray Chem. Anal., Jpn., 2012, vol. 43, ISSN 0911–7806 Search PubMed.
- E. Sato, Y. Sato, S. Ehara, A. Abudurexiti, O. Hagiwara, H. Matsukiyo, A. Osawa, T. Enomoto, M. Watanabe, J. Nagao, S. Sato, A. Ogawa and J. Onagawa, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 638(1), 187–191 CrossRef CAS
- O. Hagiwara, M. Watanabe, E. Sato, H. Matsukiyo, A. Osawa, T. Enomoto, J. Nagao, S. Sato, A. Ogawa and J. Onagawa, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 640(1), 170–175 CrossRef CAS
- B. L. Jones and S. H. Cho, Phys. Med. Biol., 2011, 56(12), 3719–3730 CrossRef
- K. Fujisaki, H. Yokota, N. Furushiro, S. Komatani, S. Ohzawa, Y. Sato, D. Matsunaga, R. Himeno, T. Higuchi and A. Makinouchi, Microsc. Microanal., 2011, 17(2), 246–251 CrossRef CAS
- K. Tsuji, T. Ohmori and M. Yamaguchi, Anal. Chem., 2011, 83(16), 6389–6394 CrossRef CAS
- Y. Nakaye and J. Kawai, X-Ray Spectrom., 2011, 40(6), 446–448 CrossRef CAS
- P. Grochulski, M. N. Fodje, J. Gorin, S. L. Labiuk and R. Berg, J. Synchrotron Radiat., 2011, 18(4), 681–684 CrossRef CAS
- M. Cotte, J. Szlachetko, S. Lahlil, M. Salome, V. A. Sole, I. Biron and J. Susini, J. Anal. At. Spectrom., 2011, 26(5), 1051–1059 RSC
- E. Kleymenov, J. A. van Bokhoven, C. David, P. Glatzel, M. Janousch, R. Alonso-Mori, M. Studer, M. Willimann, A. Bergamaschi, B. Henrich and M. Nachtegaal, Rev. Sci. Instrum., 2011, 82(6), 065107 CrossRef
- N. G. Kujala, C. Karanfil and R. A. Barrea, Rev. Sci. Instrum., 2011, 82(6), 063106–063107 CrossRef CAS
- B. A. Deng, Q. Yang, H. L. Xie, G. H. Du and T. Q. Xiao, Chin. Phys. C, 2011, 35(4), 402–404 CrossRef CAS
- B. Bozzini, A. Gianoncelli, B. Kaulich, M. Kiskinova, C. Mele and M. Prasciolu, Phys. Chem. Chem. Phys., 2011, 13(17), 7968–7974 RSC
- W. X. Cong, H. O. Shen and G. Wang, J. Biomed. Opt., 2011, 16(6), 7 CrossRef
- C. Fauquet, M. Dehlinger, F. Jandard, S. Ferrero, D. Pailharey, S. Larcheri, R. Graziola, J. Purans, A. Bjeoumikhov, A. Erko, I. Zizak, B. Dahmani and D. Tonneau, Nanoscale Res. Lett., 2011, 6, 308 CrossRef
- S. Lagomarsino, S. Iotti, G. Farruggia, A. Cedola, V. Trapani, M. Fratini, I. Bukreeva, A. Notargiacomo, L. Mastrototaro, C. Marraccini, A. Sorrentino, I. McNulty, S. Vogt, D. Legnini, S. Kim, A. Gianoncelli, J. A. M. Maier and F. I. Wolfe, Spectrochim. Acta, Part B, 2011, 66(11–12), 834–840 CrossRef CAS
- B. R. Maddox, H. S. Park, B. A. Remington, C. Chen, S. Chen, S. T. Prisbrey, A. Comley, C. A. Back, C. Szabo, J. F. Seely, U. Feldman, L. T. Hudson, S. Seltzer, M. J. Haugh and Z. Ali, Phys. Plasmas, 2011, 18(5), 6 CrossRef
- P. H. H. Oakley, R. L. McEntaffer and W. Cash, Exp. Astron., 2011, 31(1), 23–44 CrossRef
- I. Ordavo, S. Ihle, V. Arkadiev, O. Scharf, H. Soltau, A. Bjeoumikhov, S. Bjeoumikhova, G. Buzanich, R. Gubzhokov, A. Gunther, R. Hartmann, P. Holl, N. Kimmel, M. Kuhbacher, M. Lang, N. Langhoff, A. Liebel, M. Radtke, U. Reinholz, H. Riesemeier, G. Schaller, F. Schopper, L. Struder, C. Thamm and R. Wedell, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 654(1), 250–257 CrossRef CAS
- O. Scharf, S. Ihle, I. Ordavo, V. Arkadiev, A. Bjeoumikhov, S. Bjeoumikhova, G. Buzanich, R. Gubzhokov, A. Gunther, R. Hartmann, M. Kuhbacher, M. Lang, N. Langhoff, A. Liebel, M. Radtke, U. Reinholz, H. Riesemeier, H. Soltau, L. Struder, A. F. Thunemann and R. Wedell, Anal. Chem., 2011, 83(7), 2532–2538 CrossRef CAS
-
N. Kimmel, R. Andritschke, L. Englert, S. Epp, A. Hartmann, R. Hartmann, G. Hauser, P. Holl, I. Ordavo, R. Richter, L. Struder and J. Ullrich, in Advances in X-Ray Free-Electron Lasers: Radiation Schemes, X-Ray Optics, and Instrumentation, ed. T. Tschentscher and D. Cocco, Spie-Int Soc Optical Engineering, Bellingham, 2011, vol. 8078 Search PubMed
- H. T. Philipp, M. Hromalik, M. Tate, L. Koerner and S. M. Gruner, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 649(1), 67–69 CrossRef CAS
- T. Miyoshi, Y. Arai, M. Hirose, R. Ichimiya, Y. Ikemoto, T. Kohriki, T. Tsuboyama and Y. Unno, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 636, S237–S241 CrossRef CAS
- M. D. Wilson, R. Cernik, H. Chen, C. Hansson, K. Iniewski, L. L. Jones, P. Seller and M. C. Veale, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 652(1), 158–161 CrossRef CAS
- P. Seller, S. Bell, R. J. Cernik, C. Christodoulou, C. K. Egan, J. A. Gaskin, S. Jacques, S. Pani, B. D. Ramsey, C. Reid, P. J. Sellin, J. W. Scuffham, R. D. Speller, M. D. Wilson and M. C. Veale, J. Instrum., 2011, 6, C12009 CrossRef
- O. Limousin, F. Lugiez, O. Gevin, A. Meuris, C. Blondel, E. Delagnes, M. Donati, I. Le Mer, J. Martignac, F. Pinsard, M. C. Vassal, R. Bocage and F. Soufflet, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 647(1), 46–54 CrossRef CAS
- E. Guni, J. Durst, T. Michel and G. Anton, J. Instrum., 2011, 6, C01037 CrossRef
- C. B. Kim, D. H. Woo, B. H. Kim and H. C. Lee, IEICE Trans. Electron., 2011, E94C(7), 1212–1219 CrossRef
- X. Wang, D. Meier, S. Mikkelsen, G. E. Maehlum, D. J. Wagenaar, B. M. W. Tsui, B. E. Patt and E. C. Frey, Phys. Med. Biol., 2011, 56(9), 2791–2816 CrossRef CAS
- G. S. Camarda, K. W. Andreini, A. E. Bolotnikov, Y. Cui, A. Hossain, R. Gul, K. H. Kim, L. Marchini, L. Xu, G. Yang, J. E. Tkaczyk and R. B. James, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 652(1), 170–173 CrossRef CAS
- A. L. M. Silva, C. D. R. Azevedo, C. A. B. Oliveira, J. M. F. Dos Santos, M. L. Carvalho and J. Veloso, Spectrochim. Acta, Part B, 2011, 66(5), 308–313 CrossRef CAS
- T. Enomoto, E. Sato, P. Abderyim, A. Abudurexiti, O. Hagiwara, H. Matsukiyo, A. Osawa, M. Watanabe, J. Nagao, S. Sato, A. Ogawa and J. Onagawa, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 635(1), 108–115 CrossRef CAS
- E. Lombi, M. D. de Jonge, E. Donner, C. G. Ryan and D. Paterson, Anal. Bioanal. Chem., 2011, 400(6), 1637–1644 CrossRef CAS
- D. Sharma, Y. Fang, F. Zafar, K. S. Karim and A. Badano, Appl. Phys. Lett., 2011, 98(24), 2111–2113 Search PubMed
- A. Kargar, E. Ariesanti and D. S. McGregor, Nucl. Technol., 2011, 175(1), 131–137 CAS
- Y. Chang, C. H. Grein, C. R. Becker, X. J. Wang, Q. Duan, S. Ghosh, P. Dreiske, R. Bommena, J. Zhao, M. Carmody, F. Aqariden and S. Sivananthan, J. Electron. Mater., 2011, 40(8), 1854–1859 CrossRef CAS
- Q. Zheng, F. Dierre, M. Ayoub, J. Crocco, H. Bensalah, V. Corregidor, E. Alves, R. Fernandez-Ruiz, J. M. Perez and E. Dieguez, Cryst. Res. Technol., 2011, 46(11), 1131–1136 CrossRef CAS
- A. Zappettini, L. Marchini, M. Z. Zha, G. Benassi, N. Zambelli, D. Calestani, L. Zanotti, E. Gombia, R. Mosca, M. Zanichelli, M. Pavesi, N. Auricchio and E. Caroli, IEEE Trans. Nucl. Sci., 2011, 58(5), 2352–2356 CrossRef CAS
- S. Johnsen, Z. F. Liu, J. A. Peters, J. H. Song, S. Nguyen, C. D. Malliakas, H. Jin, A. J. Freeman, B. W. Wessels and M. G. Kanatzidis, J. Am. Chem. Soc., 2011, 133(26), 10030–10033 CrossRef CAS
- S. Johnsen, Z. F. Liu, J. A. Peters, J. H. Song, S. C. Peter, C. D. Malliakas, N. K. Cho, H. S. Jin, A. J. Freeman, B. W. Wessels and M. G. Kanatzidis, Chem. Mater., 2011, 23(12), 3120–3128 CrossRef CAS
- S. J. Stankovic, R. D. Ilic, K. S. Jankovic, A. Vasic-Milovanovic and B. Loncar, Acta Phys. Pol., A, 2011, 120(2), 252–255 CAS
- K. Nakamura, M. Maeda, T. Yasumune, K. Maehata, K. Ishibashi, K. Tanaka, T. Umeno, K. Takasaki and T. Momose, Radiat. Prot. Dosim., 2011, 146(1–3), 88–91 CrossRef CAS
- D. A. Goganov and A. A. Schultz, Instrum. Exp. Tech., 2011, 54(3), 409–413 CrossRef CAS
- P. Russo and G. Mettivier, Med. Phys., 2011, 38(4), 2099–2115 CrossRef
- S. Brown, R. S. Detwiler, B. Lu, A. Gopal, S. Samant and J. E. Baciak, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 652(1), 726–730 CrossRef CAS
- J. E. A. Aviles, S. Pistorius, R. Gordon and I. A. Elbakri, J. X-Ray Sci. Technol., 2011, 19(1), 35–56 Search PubMed
- C. M. P. Vaz, I. C. de Maria, P. O. Lasso and M. Tuller, Soil Sci. Soc. Am. J., 2011, 75(3), 832–841 CrossRef CAS
- W. N. Yang, X. C. Xu, K. Bi, S. Q. Zeng, Q. A. Liu and S. B. Chen, J. X-Ray Sci. Technol., 2011, 19(1), 23–33 Search PubMed
- M. R. Gherase and D. E. B. Fleming, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(10), 1150–1156 CrossRef CAS
- L. D. Horakeri, S. G. Bubbly and S. B. Gudennayar, Radiat. Phys. Chem., 2011, 80(5), 626–628 CrossRef CAS
- R. Yilmaz, K. Arici, E. Oz and M. Tan, J. Electron Spectrosc. Relat. Phenom., 2011, 184(1–2), 1–4 CrossRef CAS
- R. Yilmaz, R. Tas, R. Babayigit and K. Arici, Asian J. Chem., 2011, 23(7), 3148–3150 CAS
- D. Gonzales, S. Requena and S. Williams, Appl. Radiat. Isot., 2012, 70(1), 301–304 CrossRef CAS
- B. D. Kalinin, R. I. Plotnikov and Y. I. Sergeev, Inorg. Mater., 2011, 47(14), 1518–1521 CrossRef CAS
- S. N. Galchenko, E. K. Kirilenko and G. A. Fokov, Acta Phys. Pol., A, 2011, 120(3), 531–535 CAS
- E. V. Bonzi, N. M. Badiger, G. B. Grad, R. A. Barrea and R. G. Figueroa, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(19), 2084–2089 CrossRef CAS
- G. L. Bochek, O. S. Deiev, N. I. Maslov and V. K. Voloshyn, Probl. At. Sci. Technol., Ser.: Plasma Phys., 2011, 3, 42–49 Search PubMed
- H. Parviainen, J. Naranen and K. Muinonen, J. Quant. Spectrosc. Radiat. Transfer, 2011, 112(11), 1907–1918 CrossRef CAS
- R. Mittal and S. Gupta, Appl. Radiat. Isot., 2011, 69(10), 1568–1571 CrossRef CAS
- E. I. Molchanova, A. N. Smagunova and I. V. Shcherbakov, J. Anal. Chem., 2011, 66(9), 824–830 CrossRef CAS
- A. Markowicz, Pramana, 2011, 76(2), 321–329 CrossRef
- V. D. Hodoroaba, M. Radtke, U. Reinholz, H. Riesemeier, L. Vincze and D. Reuter, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(13), 1493–1498 CrossRef CAS
- G. Harding and S. Olesinski, Radiat. Phys. Chem., 2011, 80(9), 929–931 CrossRef CAS
- M. Korun and P. M. Modec, Appl. Radiat. Isot., 2011, 69(9), 1263–1266 CrossRef CAS
- A. K. Soper and E. R. Barney, J. Appl. Crystallogr., 2011, 44, 714–726 CrossRef CAS
- S. Medling and F. Bridges, J. Synchrotron Radiat., 2011, 18, 679–680 CrossRef CAS
- L. J. P. Ament, M. van Veenendaal, T. P. Devereaux, J. P. Hill and J. van den Brink, Rev. Mod. Phys., 2011, 83(2), 63 CrossRef
- R. P. Gardner and F. S. Li, X-Ray Spectrom., 2011, 40(6), 405–410 CrossRef CAS
- S. Arzhantsev, X. A. Li and J. F. Kauffman, Anal. Chem., 2011, 83(3), 1061–1068 CrossRef CAS
- T. Nakazawa, K. Nakano, M. Yoshida and K. Tsuji, Powder Diffr., 2011, 26(2), 163–167 CrossRef CAS
- C. Ozkan, A. Castoldi, C. Guazzoni, D. Dreossi and A. Bjeoumikhov, IEEE Trans. Nucl. Sci., 2011, 58(4), 2124–2128 CrossRef
- L. Wang, Y. Ding, U. Patel, W. G. Yang, Z. L. Xiao, Z. H. Cai, W. L. Mao and H. K. Mao, Rev. Sci. Instrum., 2011, 82(4), 5 Search PubMed
- M. H. Chu, J. Segura-Ruiz, G. Martinez-Criado, P. Cloetens, I. Snigireva, S. Geburt and C. Ronning, Phys. Status Solidi RRL, 2011, 5(8), 283–285 CrossRef CAS
- M. I. Bertoni, D. P. Fenning, M. Rinio, V. Rose, M. Holt, J. Maser and T. Buonassisi, Energy Environ. Sci., 2011, 4(10), 4252–4257 CAS
- L. Mino, D. Gianolio, G. Agostini, A. Piovano, M. Truccato, A. Agostino, S. Cagliero, G. Martinez-Criado, F. d'Acapito, S. Codato and C. Lamberti, Small, 2011, 7(7), 930–938 CrossRef CAS
- J. M. Davis, D. E. Newbury, A. Fahey, N. W. M. Ritchie, E. Vicenzi and D. Bentz, Microsc. Microanal., 2011, 17(3), 410–417 CrossRef CAS
- M. Czyzycki, D. Wegrzynek, P. Wrobel and A. Lankosz, X-Ray Spectrom., 2011, 40(2), 88–95 CrossRef CAS
- T. Wolff, W. Malzer, I. Mantouvalou, O. Hahn and B. Kanngiesser, Spectrochim. Acta, Part B, 2011, 66(2), 170–178 CrossRef
- T. Trojek, J. Anal. At. Spectrom., 2011, 26(6), 1253–1257 RSC
- G. Martinez-Criado, R. Tucoulou, P. Cloetens, P. Bleuet, S. Bohic, J. Cauzid, I. Kieffer, E. Kosior, S. Laboure, S. Petitgirard, A. Rack, J. A. Sans, J. Segura-Ruiz, H. Suhonen, J. Susini and J. Villanova, J. Synchrotron Radiat., 2012, 19, 10–18 CrossRef
- E. Fontes, D. H. Bilderback and S. M. Gruner, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 649(1), 3–5 CrossRef CAS
- V. De Andrade, J. Thieme, P. Northrup, Y. Yao, A. Lanzirotti, P. Eng and Q. Shen, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 649(1), 46–48 CrossRef CAS
- R. Klein, R. Thornagel, G. Ulm, J. Feikes and G. Wustefeld, J. Electron Spectrosc. Relat. Phenom., 2011, 184(3–6), 331–334 CrossRef CAS
- G. R. Pereira, H. S. Rocha, C. Calza, M. J. Anjos, I. Lima, C. A. Perez and R. T. Lopes, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 652(1), 684–686 CrossRef CAS
- M. I. Mazuritskiy, J. Synchrotron Radiat., 2012, 19, 129–131 CrossRef CAS
- A. R. Cabral, M. Radtke, F. Munnik, B. Lehmann, U. Reinholz, H. Riesemeier, M. Tupinamba and R. Kwitko-Ribeiro, Chem. Geol., 2011, 281(1–2), 125–132 CrossRef CAS
- J. C. Andrews, F. Meirer, Y. J. Liu, Z. Mester and P. Pianetta, Microsc. Res. Tech., 2011, 74(7), 671–681 CrossRef CAS
- K. Marquardt, E. Petrishcheva, E. Gardes, R. Wirth, R. Abart and W. Heinrich, Contrib. Mineral. Petrol., 2011, 162(4), 739–749 CrossRef CAS
- Z. Y. Qin, B. Toursarkissian and B. Lai, Metallomics, 2011, 3(8), 823–828 RSC
- H. A. O. Wang, D. Grolimund, L. R. Van Loon, K. Barmettler, C. N. Borca, B. Aeschimann and D. Gunther, Anal. Chem., 2011, 83(16), 6259–6266 CrossRef CAS
- D. P. Fenning, J. Hofstetter, M. I. Bertoni, S. Hudelson, M. Rinio, J. F. Lelievre, B. Lai, C. del Canizo and T. Buonassisi, Appl. Phys. Lett., 2011, 98(16), 3 CrossRef
- E. Lombi, G. M. Hettiarachchi and K. G. Scheckel, J. Environ. Qual., 2011, 40(3), 659–666 CrossRef CAS
- J. Y. Shi, X. F. Yuan, X. C. Chen, B. Wu, Y. Y. Huang and Y. X. Chen, Biol. Trace Elem. Res., 2011, 141(1–3), 294–304 CrossRef CAS
- F. Yan, J. C. Zhang, A. G. Li, K. Yang, H. Wang, C. W. Mao, D. X. Liang, S. A. Yan, J. O. Li and X. H. Yu, Acta Phys. Sin., 2011, 60(9), 7 Search PubMed
- J. K. Qiu, B. A. Deng, Q. Yang, F. Yan, A. G. Li and X. H. Yu, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(22), 2662–2666 CrossRef CAS
- N. V. Alov, Inorg. Mater., 2011, 47(14), 1487–1499 CrossRef CAS
- C. Horntrich, S. Smolek, A. Maderitsch, R. Simon, P. Kregsamer and C. Streli, Anal. Bioanal. Chem., 2011, 400(8), 2649–2654 CrossRef CAS
- C. Horntrich, P. Kregsamer, S. Smolek, A. Maderitsch, P. Wobrauschek, R. Simon, A. Nutsch, M. Knoerr and C. Streli, J. Anal. At. Spectrom., 2012, 27(2), 340–345 RSC
- C. Horntrich, P. Kregsamer, P. Wobrauschek and C. Streli, Spectrochim. Acta, Part B, 2011, 66(11–12), 815–821 CrossRef CAS
- A. Kuhn, O. Scharf, I. Ordavo, H. Riesemeier, U. Reinholz, M. Radtke, A. Berger, M. Ostermann and U. Panne, J. Anal. At. Spectrom., 2011, 26(10), 1986–1989 RSC
- L. Sartore, M. Barbaglio, L. Borgese and E. Bontempi, Sens. Actuators, B, 2011, 155(2), 538–544 CrossRef
- S. Dhara and N. L. Misra, Pramana, 2011, 76(2), 361–366 CrossRef CAS
- N. L. Misra, Pramana, 2011, 76(2), 201–212 CrossRef CAS
- N. L. Misra, S. Dhara, A. Das, G. S. Lodha, S. K. Aggarwal and I. Varga, Pramana, 2011, 76(2), 357–360 CrossRef CAS
- V. S. Hatzistavros and N. G. Kallithrakas-Kontos, Anal. Chem., 2011, 83(9), 3386–3391 CAS
- J. A. Abraham, H. J. Sanchez, M. C. Valentinuzzi and M. S. Grenon, X-Ray Spectrom., 2010, 39(6), 372–375 CrossRef CAS
- Z. Polgari, F. Meirer, S. Sasamori, D. Ingerle, G. Pepponi, C. Streli, K. Rickers, A. Reti, B. Budai, N. Szoboszlai and G. Zaray, Spectrochim. Acta, Part B, 2011, 66(3–4), 274–279 CrossRef CAS
- Z. Polgari, N. Szoboszlai, M. Ovari and G. Zaray, Microchem. J., 2011, 99(2), 339–343 CrossRef CAS
- A. Migliori, P. Bonanni, L. Carraresi, N. Grassi and P. A. Mando, X-Ray Spectrom., 2011, 40(2), 107–112 CrossRef CAS
- A. M. Cuevas and H. P. Gravie, Nucl. Instrum. Methods Phys. Res., Sect. A, 2011, 633(1), 72–78 CrossRef CAS
- G. M. Hansford, J. Appl. Crystallogr., 2011, 44, 514–525 CrossRef CAS
- J. Suzumura, Y. Sone, A. Ishizaki, D. Yamashita, Y. Nakajima and M. Ishida, Wear, 2011, 271(1–2), 47–53 CrossRef CAS
- B. H. Foing, C. Stoker, J. Zavaleta, P. Ehrenfreund, C. Thiel, P. Sarrazin, D. Blake, J. Page, V. Pletser, J. Hendrikse, S. Direito, J. M. Kotler, Z. Martins, G. Orzechowska, C. Gross, L. Wendt, J. Clarke, A. M. Borst, S. T. M. Peters, M. B. Wilhelm, G. R. Davies and I. E. Team, Int. J. Astrobiol., 2011, 10(3), 141–160 CrossRef
- L. R. Nittler, R. D. Starr, S. Z. Weider, T. J. McCoy, W. V. Boynton, D. S. Ebel, C. M. Ernst, L. G. Evans, J. O. Goldsten, D. K. Hamara, D. J. Lawrence, R. L. McNutt, C. E. Schlemm, S. C. Solomon and A. L. Sprague, Science, 2011, 333(6051), 1847–1850 CrossRef CAS
- S. Narendranath, P. S. Athiray, P. Sreekumar, B. J. Kellett, L. Alha, C. J. Howe, K. H. Joy, M. Grande, J. Huovelin, I. A. Crawford, U. Unnikrishnan, S. Lalita, S. Subramaniam, S. Z. Weider, L. R. Nittler, O. Gasnault, D. Rothery, V. A. Fernandes, N. Bhandari, J. N. Goswami, M. A. Wieczorek and C. X. Team, Icarus, 2011, 214(1), 53–66 CrossRef CAS
- F. J. Zurfluh, B. A. Hofmann, E. Gnos and U. Eggenberger, X-Ray Spectrom., 2011, 40(6), 449–463 CrossRef CAS
- C. Schroder, G. Klingelhofer, R. V. Morris, B. Bernhardt, M. Blumers, I. Fleischer, D. S. Rodionov, J. G. Lopez and P. A. de Souza, Geochem.: Explor., Environ., Anal., 2011, 11(2), 129–143 CrossRef
- L. C. Prinsloo, P. Colomban, J. D. Brink and I. Meiklejohn, J. Raman Spectrosc., 2011, 42(4), 626–632 CrossRef CAS
- L. J. McHenry, V. Chevrier and C. Schroder, J. Geophys. Res., [Planets], 2011, 116, 15 CrossRef
- J. J. Papike, P. V. Burger, C. K. Shearer, S. R. Sutton, M. Newville, Y. Choi and A. Lanzirotti, Am. Mineral., 2011, 96(5–6), 932–935 CrossRef CAS
- K. Steiner, J. Mater. Civ. Eng., 2011, 23(7), 1050–1056 CrossRef CAS
- V. Balasubramanian, T. M. Spear, J. F. Hart and J. D. Larson, J. Environ. Health, 2011, 73(10), 14–19 CAS
-
M. Iovea, M. Neagu, G. Mateiasi and O. Duliu, in Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, ed. R. S. Harmon, J. H. Holloway and J. T. Broach, Spie-Int Soc Optical Engineering, Bellingham, 2011, vol. 8017 Search PubMed
- J. Breen, P. de Souza, G. P. Timms and R. Ollington, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(12), 1341–1345 CrossRef CAS
- A. Carapelle, J. M. Defise, D. Strivay and H. P. Garnir, Comput. Phys. Commun., 2011, 182(6), 1304–1306 CrossRef CAS
- L. Bonizzoni, C. Colombo, S. Ferrati, M. Gargano, M. Greco, N. Ludwig and M. Realini, X-Ray Spectrom., 2011, 40(4), 247–253 CrossRef CAS
- A. R. Hasan, J. Schindler, H. M. Solo-Gabriele and T. G. Townsend, Waste Manag., 2011, 31(4), 688–694 CrossRef
- A. R. Hasan, H. Solo-Gabriele and T. Townsend, Waste Manag., 2011, 31(4), 695–704 CrossRef CAS
- K. Nakayama, S. Ichikawa and T. Nakamura, X-Ray Spectrom., 2012, 41(1), 16–21 CrossRef CAS
- Q. Wang, X. H. Ying and J. B. Zhang, Spectrosc. Spectr. Anal., 2011, 31(9), 2574–2577 CAS
- S. P. Verma, R. Gonzalez-Ramirez and R. Rodriguez-Rios, Geostand. Geoanal. Res., 2011, 35(2), 183–192 CrossRef CAS
- V. Zivanovic, Chem. Ind. Chem. Eng. Q., 2011, 17(2), 231–237 CrossRef CAS
- Q. Wang, J. B. Zhang, X. H. Ying, B. L. Wu, Q. W. Wang and H. Wang, Chin. J. Anal. Chem., 2011, 39(11), 1726–1731 CrossRef CAS
- S. A. James, D. E. Myers, M. D. de Jonge, S. Vogt, C. G. Ryan, B. A. Sexton, P. Hoobin, D. Paterson, D. L. Howard, S. C. Mayo, M. Altissimo, G. F. Moorhead and S. W. Wilkins, Anal. Bioanal. Chem., 2011, 401(3), 853–864 CrossRef CAS
- E. de Almeida, P. R. Massoni, A. A. Menegario, L. C. Leite, D. P. D. Lanna and V. F. do Nascimento, X-Ray Spectrom., 2011, 40(6), 424–426 CrossRef CAS
- C. G. Worley, C. Soderberg and L. Townsend, Powder Diffr., 2011, 26(2), 168–170 CrossRef CAS
- F. Wang, Z. Li and B. Qiao, J. X-Ray Sci. Technol., 2011, 19(3), 417–421 Search PubMed
- T. Inui, W. Abe, M. Kitano and T. Nakamura, X-Ray Spectrom., 2011, 40(4), 301–305 CrossRef CAS
- B. Zawisza and R. Sitko, Appl. Spectrosc., 2011, 65(10), 1218–1221 CrossRef CAS
- R. Sitko, K. Kocot, B. Zawisza, B. Feist and K. Pytlakowska, J. Anal. At. Spectrom., 2011, 26(10), 1979–1985 RSC
- Z. A. Temerdashev, D. N. Konshina, E. Y. Logacheva and V. V. Konshin, J. Anal. Chem., 2011, 66(10), 930–936 CrossRef CAS
- J. Tian, X. Xie, W. T. Ma, H. Y. Jin and P. X. Wang, Paleoceanography, 2011, 26, 17 CrossRef
- S. Lauterbach, A. Brauer, N. Andersen, D. L. Danielopol, P. Dulski, M. Huls, K. Milecka, T. Namiotko, M. Obremska, U. Von Grafenstein and P. Declakes, J. Quaternary Sci., 2011, 26(3), 253–267 CrossRef
- L. Lowemark, H. F. Chen, T. N. Yang, M. Kylander, E. F. Yu, Y. W. Hsu, T. Q. Lee, S. R. Song and S. Jarvis, J. Asian Earth Sci., 2011, 40(6), 1250–1256 CrossRef
- N. L. Balascio, Z. H. Zhang, R. S. Bradley, B. Perren, S. O. Dahl and J. Bakke, Quat. Res., 2011, 75(1), 288–300 CrossRef
- J. Olsen, S. Bjorck, M. J. Leng, E. R. Gudmundsdottir, B. V. Odgaard, C. M. Lutz, C. P. Kendrick, T. J. Andersen and M. S. Seidenkrantz, Quat. Sci. Rev., 2010, 29(19–20), 2764–2780 CrossRef
- S. Solignac, M. S. Seidenkrantz, C. Jessen, A. Kuijpers, A. K. Gunvald and J. Olsen, Holocene, 2011, 21(4), 539–552 CrossRef
- Y. L. Zhao, Z. F. Liu, C. Colin, M. Paterne, G. Siani, X. R. Cheng, S. Duchamp-Alphonse and X. Xie, Palaeogeogr., Palaeoclimatol., Palaeoecol., 2011, 311(3–4), 230–241 CrossRef
- K. M. R. Matsuzaki, F. Eynaud, B. Malaize, F. E. Grousset, A. Tisserand, L. Rossignol, K. Charlier and E. Jullien, Mar. Micropaleontol., 2011, 79(3–4), 67–79 CrossRef
- I. Aarnes, A. E. Bjune, H. H. Birks, N. L. Balascio, J. Bakke and M. Blaauw, Veg. Hist. Archaeobot., 2012, 21(1), 17–35 CrossRef
- A. Marcelli, D. Hampai, F. Giannone, M. Sala, V. Maggi, F. Marino, S. Pignotti and G. Cibin, J. Anal. At. Spectrom., 2012, 27(1), 33–37 RSC
- S. Giralt, M. T. Rico-Herrero, J. C. Vega and B. L. Valero-Garces, J. Paleolimnol., 2011, 46(3), 487–502 CrossRef
- K. Vasskog, A. Nesje, E. N. Storen, N. Waldmann, E. Chapron and D. Ariztegui, Holocene, 2011, 21(4), 597–614 CrossRef
- C. van der Land, F. Mienis, H. de Haas, H. C. de Stigter, R. Swennen, J. J. G. Reijmer and T. C. E. van Weering, Mar. Geol., 2011, 284(1–4), 86–95 CrossRef CAS
- T. N. Moroz, N. A. Palchik, T. N. Grigorieva, Y. P. Kolmogorov and A. N. Derkachev, J. Surf. Ingestig.-X-Ray Synchro., 2011, 5(6), 1073–1078 CAS
- I. Martini, Geomorphology, 2011, 134(3–4), 452–460 CrossRef
- L. Guo, Z. X. Jiang, J. C. Zhang and Y. X. Li, Energy Explor. Exploit., 2011, 29(5), 597–616 CrossRef CAS
- S. H. Buttner, Mineral. Petrol., 2012, 104(1–2), 129–135 CrossRef
- Y. Kon, H. Murakami, T. Takagi and Y. Watanabe, Geochem. J., 2011, 45(5), 387–416 CAS
- M. Boone, J. Dewanckele, V. Cnudde, G. Silversmit, E. Van Ranst, P. Jacobs, L. Vincze and L. Van Hoorebeke, Geosphere, 2011, 7(1), 79–86 CrossRef
- Y. Y. Wang, X. C. Zhan, J. H. Yuan and X. T. Fan, Spectrosc. Spectr. Anal., 2011, 31(6), 1707–1711 CAS
- R. Fan and A. R. Gerson, Geochim. Cosmochim. Acta, 2011, 75(21), 6400–6415 CrossRef CAS
- C. Jones, S. A. Crowe, A. Sturm, K. L. Leslie, L. C. W. MacLean, S. Katsev, C. Henny, D. A. Fowle and D. E. Canfield, Biogeosciences, 2011, 8(10), 2977–2991 CrossRef CAS
- M. Garcon, C. Chauvel and S. Bureau, Chem. Geol., 2011, 287(3–4), 182–192 CrossRef CAS
- O. Jacquat, C. Rambeau, A. Voegelin, N. Efimenko, A. Villard, K. B. Follmi and R. Kretzschmar, Swiss J. Geosci., 2011, 104(3), 409–424 CrossRef CAS
- D. Genna, D. Gaboury, L. Moore and W. U. Mueller, J. Geochem. Explor., 2011, 108(2), 131–142 CrossRef CAS
- D. Fiantis, M. Nelson, J. Shamshuddin, T. B. Goh and E. Van Ranst, Eurasian Soil Sci., 2010, 43(13), 1477–1485 CrossRef
- M. Y. Hu, X. T. Fan, B. Stoll, D. Kuzmin, Y. Liu, Y. S. Liu, W. D. Sun, G. Wang, X. C. Zhan and K. P. Jochum, Geostand. Geoanal. Res., 2011, 35(2), 235–251 CrossRef CAS
- M. Grafe, M. Landers, R. Tappero, P. Austin, B. Gan, A. Grabsch and C. Klauber, J. Environ. Qual., 2011, 40(3), 767–783 CrossRef CAS
- M. F. Gazley, J. K. Vry, E. du Plessis and M. R. Handler, J. Geochem. Explor., 2011, 110(2), 74–80 CrossRef CAS
- F. Reith, B. Etschmann, R. C. Dart, D. L. Brewe, S. Vogt, A. S. Mumm and J. Brugger, Geochim. Cosmochim. Acta, 2011, 75(7), 1942–1956 CrossRef CAS
- J. Figueroa-Cisterna, M. G. Bagur-Gonzalez, S. Morales-Ruano, J. Carrillo-Rosua and F. Martin-Peinado, Talanta, 2011, 85(5), 2307–2315 CrossRef CAS
- Y. M. Wang, X. H. Wang, W. J. Qu, Y. S. Gao, T. X. Gu, X. T. Fan, S. I. Andreev and X. F. Shi, Geostand. Geoanal. Res., 2011, 35(3), 341–352 CrossRef CAS
- O. Haavisto and H. Hyotyniemi, J. Process Control, 2011, 21(2), 246–253 CrossRef CAS
- J. R. Lin, Y. M. Pan, N. Chen, M. Mao, R. Li and R. F. Feng, Can. Mineral., 2011, 49(3), 809–822 CrossRef CAS
- M. Tauhid-Ur-Rahman, A. Mano, K. Udo and Y. Ishibashi, Appl. Geochem., 2011, 26(4), 636–647 CrossRef CAS
- S. Kumar and A. Saxena, J. Geol. Soc. India, 2011, 77(5), 459–477 CrossRef CAS
- S. Mitsunobu, Y. Takahashi, S. Utsunomiya, M. A. Marcus, Y. Terada, T. Iwamura and M. Sakata, Am. Mineral., 2011, 96(7), 1171–1181 CrossRef CAS
- C. Carbone, P. Marescotti, G. Lucchetti, J. Cauzid and E. Chalmin, Neues Jahrb. Mineral., Abh., 2011, 188(1), 21–30 CrossRef CAS
- O. B. Odumo, A. O. Mustapha, J. P. Patel and H. K. Angeyo, Bull. Environ. Contam. Toxicol., 2011, 86(5), 484–489 CrossRef CAS
- X. Boes, J. Rydberg, A. Martinez-Cortizas, R. Bindler and I. Renberg, J. Paleolimnol., 2011, 46(1), 75–87 CrossRef
- R. A. Wildman, L. F. Pratson, M. DeLeon and J. G. Hering, J. Environ. Qual., 2011, 40(2), 575–586 CrossRef CAS
- S. B. Baines, B. S. Twining, M. A. Brzezinski, D. M. Nelson and N. S. Fisher, Global Biogeochem. Cycles, 2011, 24, 15 Search PubMed
- S. B. Baines, B. S. Twining, S. Vogt, W. M. Balch, N. S. Fisher and D. M. Nelson, Deep-Sea Res., Part II, 2011, 58(3–4), 512–523 CrossRef CAS
- E. Binner, J. Facun, L. G. Chen, Y. Ninomiya, C. Z. Li and S. Bhattacharya, Energy Fuels, 2011, 25(7), 2764–2771 CrossRef CAS
- S. I. Arbuzov, A. V. Volostnov, L. P. Rikhvanov, A. M. Mezhibor and S. S. Ilenok, Int. J. Coal Geol., 2011, 86(4), 318–328 CrossRef CAS
- B. Y. Yang, B. Hu, Z. Y. Bao and Z. G. Zhang, J. Rare Earths, 2011, 29(5), 499–506 CrossRef CAS
- B. Datangel and J. L. Goldfarb, Energy Fuels, 2011, 25(8), 3522–3529 CrossRef CAS
- A. Doyle, A. Saavedra, M. L. B. Tristao, M. Nele and R. Q. Aucelio, Spectrochim. Acta, Part B, 2011, 66(5), 368–372 CrossRef CAS
- J. L. Goncalves, A. J. F. Bombard, D. A. W. Soares, R. D. M. Carvalho, A. Nascimento, M. R. Silva, G. B. Alcantara, F. Pelegrini, E. D. Vieira, K. R. Pirota, M. Bueno, G. M. S. Lucas and N. O. Rocha, Energy Fuels, 2011, 25(8), 3537–3543 CrossRef CAS
- N. Shimobayashi, M. Ohnishi and H. Miura, J. Mineral. Petrol. Sci., 2011, 106(3), 158–163 CrossRef CAS
- M. F. Gazulla, S. Vicente and M. Orduna, X-Ray Spectrom., 2011, 40(4), 265–272 CrossRef CAS
- S. Bayulken, E. Bascetin, K. Guclu and R. Apak, Environ. Prog. Sustainable Energy, 2011, 30(1), 70–80 CrossRef
- R. P. Orosco, E. Perino, M. D. Ruiz and J. A. Gonzalez, Int. J. Miner. Process., 2011, 98(3–4), 195–201 CrossRef CAS
- V. A. Arus, G. Jinescu, I. D. Nistor, N. D. Miron, A. V. Ursu, G. Isopencu and A. M. Mares, Rev. Chim., 2011, 61(11), 1100–1104 Search PubMed
- E. dos Santos, R. B. Scorzelli, L. C. Bertolino, O. C. Alves and P. Munayco, Appl. Clay Sci., 2012, 55, 164–167 CrossRef CAS
- A. R. Tehrani-Bagha, H. Nikkar, N. M. Mahmoodi, M. Markazi and F. M. Menger, Desalination, 2011, 266(1–3), 274–280 CrossRef CAS
- M. O. Caglayan and B. Otman, J. Food Process Eng., 2011, 34(5), 1381–1393 CrossRef
- D. Bondar, C. J. Lynsdale, N. B. Milestone, N. Hassani and A. A. Ramezanianpour, Construct. Build. Mater., 2011, 25(10), 4065–4071 CrossRef
- S. Meseguer, F. Pardo, M. M. Jordan, T. Sanfeliu and J. Gonzalez, Appl. Clay Sci., 2011, 52(4), 414–418 CrossRef CAS
- B. K. Ngun, H. Mohamad, S. K. Sulaiman, K. Okada and Z. A. Ahmad, Appl. Clay Sci., 2011, 53(1), 33–41 CrossRef CAS
- K. S. A. Halim, M. Bahgat, M. B. Morsi and K. El-Barawy, Ironmaking Steelmaking, 2011, 38(4), 279–284 CrossRef
- F. S. de Oliveira, A. Varajao, C. A. C. Varajao, B. Boulange and N. S. Gomes, Geoderma, 2011, 167–68, 319–327 CrossRef
- S. Yamasaki, H. Matsunami, A. Takeda, K. Kimura, I. Yamaji, Y. Ogawa and N. Tsuchiya, Bunseki Kagaku, 2011, 60(4), 315–323 CrossRef CAS
- A. Vott, F. Lang, H. Bruckner, K. Gaki-Papanastassiou, H. Maroukian, D. Papanastassiou, A. Giannikos, H. Hadler, M. Handl, K. Ntageretzis, T. Willershauser and A. Zander, Quat. Int., 2011, 242(1), 213–239 Search PubMed
- H. Roschzttardtz, L. Grillet, M. P. Isaure, G. Conejero, R. Ortega, C. Curie and S. Mari, J. Biol. Chem., 2011, 286(32), 27863–27866 CrossRef CAS
- M. Regvar, D. Eichert, B. Kaulich, A. Gianoncelli, P. Pongrac, K. Vogel-Mikus and I. Kreft, J. Exp. Bot., 2011, 62(11), 3929–3939 CrossRef CAS
- J. Frommer, A. Voegelin, J. Dittmar, M. A. Marcus and R. Kretzschmar, Eur. J. Soil Sci., 2011, 62(2), 305–317 CrossRef
- A. M. Carey, G. J. Norton, C. Deacon, K. G. Scheckel, E. Lombi, T. Punshon, M. L. Guerinot, A. Lanzirotti, M. Newville, Y. S. Choi, A. H. Price and A. A. Meharg, New Phytol., 2011, 192(1), 87–98 CrossRef CAS
- A. A. T. Johnson, B. Kyriacou, D. L. Callahan, L. Carruthers, J. Stangoulis, E. Lombi and M. Tester, PLoS One, 2011, 6(9), 11 Search PubMed
- P. M. Kopittke, N. W. Menzies, M. D. de Jonge, B. A. McKenna, E. Donner, R. I. Webb, D. J. Paterson, D. L. Howard, C. G. Ryan, C. J. Glover, K. G. Scheckel and E. Lombi, Plant Physiol., 2011, 156(2), 663–673 CrossRef CAS
- Y. Yu, L. Luo, K. Yang and S. Z. Zhang, Pedobiologia, 2011, 54(5–6), 267–272 CrossRef CAS
- N. Yamaguchi, S. Mori, K. Baba, S. Kaburagi-Yada, T. Arao, N. Kitajima, A. Hokura and Y. Terada, Environ. Exp. Bot., 2011, 71(2), 198–206 CrossRef CAS
- S. K. Tian, L. L. Lu, J. Labavitch, X. E. Yang, Z. L. He, H. N. Hu, R. Sarangi, M. Newville, J. Commisso and P. Brown, Plant Physiol., 2011, 157(4), 1914–1925 CrossRef CAS
- S. Carrasco-Gil, A. Alvarez-Fernandez, J. Sobrino-Plata, R. Millan, R. O. Carpena-Ruiz, D. L. Leduc, J. C. Andrews, J. Abadia and L. E. Hernandez, Plant, Cell Environ., 2011, 34(5), 778–791 CrossRef CAS
- I. Nakai, N. Oda and Y. Terada, Chem. Lett., 2011, 40(12), 1398–1399 CrossRef CAS
- J. A. Hernandez-Viezcas, H. Castillo-Michel, A. D. Servin, J. R. Peralta-Videa and J. L. Gardea-Torresdey, Chem. Eng. J., 2011, 170(2–3), 346–352 CrossRef CAS
- R. Dumlupinar, M. Genisel, S. Erdal, T. Korkut, M. S. Taspinar and M. Taskin, Biol. Trace Elem. Res., 2011, 143(3), 1740–1745 CrossRef CAS
- U. Akbaba, Y. Sahin and H. Turkez, Fresenius Environ. Bull., 2011, 20(7), 1655–1660 CAS
- U. Akbaba, Y. Sahin and H. Turkez, Fresenius Environ. Bull., 2011, 20(10), 2594–2600 CAS
- A. Csog, V. G. Mihucz, E. Tatar, F. Fodor, I. Virag, C. Majdik and G. Zaray, J. Plant Physiol., 2011, 168(10), 1038–1044 CrossRef CAS
- Z. Matasin, V. Orescanin, V. V. Jukic, S. Nejedli, M. Matasin and I. T. Gajger, J. Anim. Vet. Adv., 2011, 10(8), 1069–1072 CrossRef CAS
- A. Aich, A. Chakraborty, M. Sudarshan, B. Chattopadhyay and S. K. Mukhopadhyay, Aquacult. Res., 2012, 43(1), 53–65 CrossRef
- S. E. Sabatini, I. Rocchetta, D. E. Nahabedian, C. M. Luquet, M. R. Eppis, L. Bianchi and M. D. R. de Molina, Comp. Biochem. Physiol., Part C: Toxicol. Pharmacol., 2011, 154(4), 391–398 CrossRef CAS
- D. Zimmer, J. Kruse, C. Baum, C. Borca, M. Laue, G. Hause, R. Meissner and P. Leinweber, Sci. Total Environ., 2011, 409(19), 4094–4100 CAS
- E. Harada, A. Hokura, I. Nakai, Y. Terada, K. Baba, K. Yazaki, M. Shiono, N. Mizuno and T. Mizuno, Metallomics, 2011, 3(12), 1340–1346 RSC
- A. D. Stewart, R. R. Anand, J. S. Laird, M. Verrall, C. G. Ryan, M. D. de Jonge, D. Paterson and D. L. Howard, PLoS One, 2011, 6(11), 7 Search PubMed
- E. D. Wannaz, H. A. Carreras, G. A. Abril and M. L. Pignata, Environ. Exp. Bot., 2011, 74, 296–301 CrossRef CAS
- D. C. Weindorf, Y. D. Zhu, S. Chakraborty, N. Bakr and B. A. Huang, Environ. Monit. Assess., 2012, 184(1), 217–227 CrossRef
- A. Takeda, S. Yamasaki, H. Tsukada, Y. Takaku, S. Hisamatsu and N. Tsuchiya, Soil Sci. Plant Nutr., 2011, 57(1), 19–28 CrossRef CAS
- M. B. B. Guerra, C. Schaefer, P. D. Rosa, F. N. B. Simas, T. T. C. Pereira and E. R. Pereira, Water, Air, Soil Pollut., 2011, 222(1–4), 91–102 CrossRef CAS
- Y. S. Shimamoto, Y. Takahashi and Y. Terada, Environ. Sci. Technol., 2011, 45(6), 2086–2092 CrossRef CAS
- F. Degryse, A. Voegelin, O. Jacquat, R. Kretzschmar and E. Smolders, Eur. J. Soil Sci., 2011, 62(2), 318–330 CrossRef CAS
- D. R. Schwer and D. H. McNear, J. Environ. Qual., 2011, 40(4), 1172–1181 CrossRef CAS
- S. Khaokaew, R. L. Chaney, G. Landrot, M. Ginder-Vogel and D. L. Sparks, Environ. Sci. Technol., 45(10), 4249–4255 Search PubMed.
- B. S. Gilfedder, M. Petri, M. Wessels and H. Biester, Geochim. Cosmochim. Acta, 2011, 75(12), 3385–3401 CrossRef CAS
- T. L. Gerke, K. G. Scheckel and J. B. Maynard, Sci. Total Environ., 2010, 408(23), 5845–5853 CrossRef CAS
- F. Cozzi, G. Grzinic, S. Cozzutto, P. Barbieri, M. Bovenzi and G. Adami, X-Ray Spectrom., 2012, 41(1), 34–41 CrossRef CAS
- E. V. Fischer, K. D. Perry and D. A. Jaffe, J. Geophys. Res., [Atmos.], 2011, 116, 13 Search PubMed
- M. L. Lopez, S. Ceppi, G. G. Palancar, L. E. Olcese, G. Tirao and B. M. Toselli, Atmos. Environ., 2011, 45(31), 5450–5457 CrossRef CAS
- S. Y. Artamonova, J. Surf. Ingestig.-X-Ray Synchro., 2011, 5(6), 1085–1090 CAS
- M. C. Corriveau, H. E. Jamieson, M. B. Parsons, J. L. Campbell and A. Lanzirotti, Appl. Geochem., 2011, 26(9–10), 1639–1648 CrossRef CAS
- A. Godelitsas, P. Nastos, T. J. Mertzimekis, K. Toli, R. Simon and J. Gottlicher, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(24), 3077–3081 CrossRef CAS
- L. C. W. MacLean, S. Beauchemin and P. E. Rasmussen, Environ. Sci. Technol., 2011, 45(13), 5491–5497 CrossRef CAS
- S. R. Waker, H. E. Jamieson and P. E. Rasmussen, Environ. Sci. Technol., 2011, 45(19), 8233–8240 CrossRef
- G. H. Asbury and R. F. Shannon, AATCC Rev., 2011, 11(2), 58–64 Search PubMed
- E. Remoundaki, A. Bourliva, P. Kokkalis, R. E. Mamouri, A. Papayannis, T. Grigoratos, C. Samara and M. Tsezos, Sci. Total Environ., 2011, 409(20), 4361–4372 CrossRef CAS
- E. Apeagyei, M. S. Bank and J. D. Spengler, Atmos. Environ., 2011, 45(13), 2310–2323 CrossRef CAS
- W. Hamza, M. R. Enan, H. Al-Hassini, J. B. Stuut and D. de-Beer, Aquat. Ecosyst. Health Manage., 2011, 14(3), 260–268 CrossRef
- F. Lucarelli, S. Nava, G. Calzolai, M. Chiari, R. Udisti and F. Marino, X-Ray Spectrom., 2011, 40(3), 162–167 CrossRef CAS
- V. Bernardoni, E. Cuccia, G. Calzolai, M. Chiari, F. Lucarelli, D. Massabo, S. Nava, P. Prati, G. Valli and R. Vecchi, X-Ray Spectrom., 2011, 40(2), 79–87 CrossRef CAS
- F. Reinhardt, J. Osan, S. Torok, A. E. Pap, M. Kolbe and B. Beckhoff, J. Anal. At. Spectrom., 2012, 27(2), 248–255 RSC
- T. X. Sun, Z. G. Liu, Y. D. Li, Y. Z. Ma, G. F. Wang, G. H. Zhu, Q. Xu, X. Y. Lin, P. Luo, Q. L. Pan, H. Liu, Y. P. Teng and X. L. Ding, Appl. Spectrosc., 2011, 65(12), 1398–1402 CrossRef CAS
- S. M. Jones and G. Flynn, Meteorit. Planet. Sci., 2011, 46(9), 1253–1264 CrossRef CAS
- D. Eliche-Quesada, C. Martinez-Garcia, M. L. Martinez-Cartas, M. T. Cotes-Palomino, L. Perez-Villarejo, N. Cruz-Perez and F. A. Corpas-Iglesias, Appl. Clay Sci., 2011, 52(3), 270–276 CrossRef CAS
- M. Felipe-Sese, D. Eliche-Quesada and F. A. Corpas-Iglesias, Ceram. Int., 2011, 37(8), 3019–3028 CrossRef CAS
- M. Z. Chen, J. T. Lin and S. P. Wu, Construct. Build. Mater., 2011, 25(10), 3909–3914 CrossRef
- X. M. Liu and L. R. Xu, J. Wuhan Univ. Technol., Mater. Sci. Ed., 2011, 26(2), 336–339 Search PubMed
- T. C. Esteves, R. Rajamma, D. Soares, A. S. Silva, V. M. Ferreira and J. A. Labrincha, Construct. Build. Mater., 2012, 26(1), 687–693 CrossRef
- E. Donner, D. L. Howard, M. D. de Jonge, D. Paterson, M. H. Cheah, R. Naidu and E. Lombi, Environ. Sci. Technol., 2011, 45(17), 7249–7257 CAS
- S. E. Fawcett and H. E. Jamieson, Chem. Geol., 2011, 283(3–4), 109–118 CrossRef CAS
- Y. Y. Shao, C. B. Xu, J. Zhu, F. Preto, J. S. Wang, H. N. Li and C. Badour, Energy Fuels, 2011, 25(7), 2841–2849 CrossRef CAS
- O. Gonzalez-Fernandez, I. Queralt, M. L. Carvalho and G. Garcia, Water, Air, Soil Pollut., 2011, 220(1–4), 279–291 CrossRef CAS
- T. Tomiyasu, A. Matsuyama, R. Imura, H. Kodamatani, J. Miyamoto, Y. Kono, D. Kocman, J. Kotnik, V. Fajon and M. Horvat, Environ. Earth Sci., 2012, 65(4), 1309–1322 CrossRef CAS
- H. Higashiyama, F. Yagishita, M. Sano and O. Takahashi, Construct. Build. Mater., 2012, 26(1), 96–101 CrossRef
- M. Eveno, B. Moignard and J. Castaing, Microsc. Microanal., 2011, 17(5), 667–673 CrossRef CAS
- A. Deneckere, B. Vekemans, L. Van de Voorde, P. De Paepe, L. Vincze, L. Moens and P. Vandenabeele, Appl. Phys. A: Mater. Sci. Process., 2012, 106(2), 363–376 CrossRef CAS
- B. Kanngiesser, W. Malzer, I. Mantouvalou, D. Sokaras and A. G. Karydas, Appl. Phys. A: Mater. Sci. Process., 2012, 106(2), 325–338 CrossRef CAS
- L. Bertrand, L. Robinet, M. Thoury, K. Janssens, S. X. Cohen and S. Schoder, Appl. Phys. A: Mater. Sci. Process., 2012, 106(2), 377–396 CrossRef CAS
- S. S. Shilstein and S. Shalev, J. Archaeol. Sci., 2011, 38(7), 1690–1698 CrossRef
- M. Rodrigues, F. Cappa, M. Schreiner, P. Ferloni, M. Radtke, U. Reinholz, B. Woytek and M. Alram, J. Anal. At. Spectrom., 2011, 26(5), 984–991 RSC
- M. Rodrigues, M. Schreiner, M. Melcher, M. Guerra, J. Salomon, M. Radtke, M. Alram and N. Schindel, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(24), 3041–3045 CrossRef CAS
- V. Kantarelou, F. J. Ager, D. Eugenidou, F. Chaves, A. Andreou, E. Kontou, N. Katsikosta, M. A. Respaldiza, P. Serafin, D. Sokaras, C. Zarkadas, K. Polikreti and A. G. Karydas, Spectrochim. Acta, Part B, 2011, 66(9–10), 681–690 CrossRef CAS
- C. Canovaro, I. Calliari, S. Gottardello and M. Asolati, Metall. Ital., 2011, 2, 21–25 Search PubMed
- M. F. Alberghina, R. Barraco, M. Brai, T. Schillaci and L. Tranchina, Spectrochim. Acta, Part B, 2011, 66(2), 129–137 CrossRef
- S. Leroy, R. Simon, L. Bertrand, A. Williams, E. Foy and P. Dillmann, J. Anal. At. Spectrom., 2011, 26(5), 1078–1087 RSC
- R. Cattaneo, C. C. Trere, L. Mordeglia, G. Gorini, E. P. Cippo, L. Bartoli, W. Kockelmann and A. Scherillo, J. Anal. At. Spectrom., 2011, 26(5), 1024–1029 RSC
- E. Gliozzo, W. Kockelmann, L. Bartoli and R. H. Tykot, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(3), 277–283 CrossRef CAS
- A. Galli, L. Bonizzoni, E. Sibilia and M. Martini, X-Ray Spectrom., 2011, 40(2), 74–78 CrossRef CAS
- E. Figueiredo, P. Valerio, M. F. Araujo, R. J. C. Silva and A. M. M. Soares, X-Ray Spectrom., 2011, 40(5), 325–332 CrossRef CAS
- M. Martinon-Torres and L. Ladra, Trabajos de Prehistoria, 2011, 68(1), 187–198 CrossRef
- I. C. A. Sandu, M. H. de Sa and M. C. Pereira, Surf. Interface Anal., 2011, 43(8), 1134–1151 CrossRef CAS
- Y. Abe, H. Gondai, S. Takeuchi, J. Shirataki, T. Uchida and I. Nakai, Bunseki Kagaku, 2011, 60(6), 477–487 CrossRef CAS
- S. Liu, Q. H. Li and F. X. Gan, Spectrosc. Spectral Anal., 2011, 31(7), 1954–1959 CAS
- S. Liu, Q. H. Li, F. X. Gan and P. Zhang, X-Ray Spectrom., 2011, 40(5), 364–375 CrossRef CAS
- S. Cagno, G. Nuyts, S. Bugani, K. De Vis, O. Schalm, J. Caen, L. Helfen, M. Cotte, P. Reischig and K. Janssens, J. Anal. At. Spectrom., 2011, 26(12), 2442–2451 RSC
- J. Delgado, M. Vilarigues, A. Ruivo, V. Corregidor, R.
C. da Silva and L. C. Alves, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(20), 2383–2388 CrossRef CAS
- K. Polikreti, J. M. A. Murphy, V. Kantarelou and A. G. Karydas, J. Archaeol. Sci., 2011, 38(11), 2889–2896 CrossRef
- G. Vaggelli and R. Cossio, Analyst, 2012, 137(3), 662–667 RSC
- R. J. Speakman, N. C. Little, D. Creel, M. R. Miller and J. G. Inanez, J. Archaeol. Sci., 2011, 38(12), 3483–3496 CrossRef
- N. Forster, P. Grave, N. Vickery and L. Kealhofer, X-Ray Spectrom., 2011, 40(5), 389–398 CrossRef CAS
- F. De Vleeschouwer, V. Renson, P. Claeys, K. Nys and R. Bindler, Geoarchaeology, 2011, 26(3), 440–450 CrossRef
- P. Sciau, Y. Leon, P. Goudeau, S. C. Fakra, S. Webb and A. Mehta, J. Anal. At. Spectrom., 2011, 26(5), 969–976 RSC
- Q. L. Li, C. T. Xu, S. W. He and Z. Q. Yao, Acta Chim. Sin., 2011, 69(8), 912–918 CAS
- F. Bardelli, G. Barone, V. Crupi, F. Longo, D. Majolino, P. Mazzoleni and V. Venuti, Anal. Bioanal. Chem., 2011, 399(9), 3147–3153 CrossRef CAS
- M. Alfeld, K. Janssens, J. Dik, W. de Nolf and G. van der Snickt, J. Anal. At. Spectrom., 2011, 26(5), 899–909 RSC
- J. Zemlicka, J. Jakubek, M. Kroupa, D. Hradil, J. Hradilova and H. Mislerova, J. Instrum., 2011, 6, C01066 CrossRef
- A. Pitarch, A. Ramon, A. Alvarez-Perez and I. Queralt, Anal. Bioanal. Chem., 2012, 402(4), 1481–1492 CrossRef CAS
- M. Thoury, J. K. Delaney, E. R. de la Rie, M. Palmer, K. Morales and J. Krueger, Appl. Spectrosc., 2011, 65(8), 939–951 CrossRef CAS
- S. Valadas, A. Candeias, J. Mirao, D. Tavares, J. Coroado, R. Simon, A. S. Silva, M. Gil, A. Guilherme and M. L. Carvalho, Microsc. Microanal., 2011, 17(5), 702–709 CrossRef CAS
- M. K. Donais, D. George, B. Duncan, S. M. Wojtas and A. M. Daigle, Anal. Methods, 2011, 3(5), 1061–1071 RSC
- G. Gauthier and A. L. Burke, Geoarchaeology, 2011, 26(2), 269–291 CrossRef
- H. Yoshida, R. Metcalfe, S. Nishimoto, H. Yamamoto and N. Katsuta, Appl. Geochem., 2011, 26(9–10), 1706–1721 CrossRef CAS
- J. K. Millhauser, E. Rodriguez-Alegria and M. D. Glascock, J. Archaeol. Sci., 2011, 38(11), 3141–3152 CrossRef
- F. C. Sun, H. X. Zhao and F. X. Gan, Spectrosc. Spectr. Anal., 2011, 31(11), 3134–3139 CAS
- D. V. Burley, P. J. Sheppard and M. Simonin, J. Archaeol. Sci., 2011, 38(10), 2625–2632 CrossRef
- M. D. Glascock, Y. V. Kuzmin, A. V. Grebennikov, V. K. Popov, V. E. Medvedev, I. Y. Shewkomud and N. N. Zaitsev, J. Archaeol. Sci., 2011, 38(8), 1832–1841 CrossRef
- G. M. Smith and J. Kielhofer, J. Archaeol. Sci., 2011, 38(12), 3568–3576 CrossRef
- L. Lancaster, G. Sottili, F. Marra and G. Ventura, Archaea, 2011, 53, 707–727 CrossRef CAS
- L. C. Lancaster, G. Sottili, F. Marra and G. Ventura, Archaea, 2010, 52, 949–961 CAS
- E. Gliozzo, D. Damiani, S. Camporeale, I. Memmi and E. Papi, J. Archaeol. Sci., 2011, 38(5), 1026–1036 CrossRef
- A. M. De Francesco, T. Graziano, E. Andaloro, A. La Marca, C. Colelli, G. M. Crisci, E. Barrese and M. Bocci, Period. Mineral., 2011, 80(2), 217–230 Search PubMed
- D. Miriello, D. Barca, A. Bloise, A. Ciarallo, G. M. Crisci, T. De Rose, C. Gattuso, F. Gazineo and M. F. La Russa, J. Archaeol. Sci., 2010, 37(9), 2207–2223 CrossRef
- H. H. M. Mahmoud, M. F. Ali, E. Pavlidou, N. Kantiranis and A. El-Badry, Archaea, 2011, 53, 693–706 CrossRef
- J. Sanjurjo-Sanchez, J. R. V. Romani and C. Alves, Geomorphology, 2012, 138(1), 231–242 CrossRef
- A. D. Smith, D. I. Green, J. M. Charnock, E. Pantos, S. Timberlake and A. Prag, J. Archaeol. Sci., 2011, 38(11), 3029–3037 CrossRef
- Y. Fors, F. Jalilehvand and M. Sandstrom, Anal. Sci., 2011, 27(8), 785–792 CrossRef CAS
- I. Mantouvalou, T. Wolff, O. Hahn, I. Rabin, L. Luhl, M. Pagels, W. Malzer and B. Kanngiesser, Anal. Chem., 2011, 83(16), 6308–6315 CrossRef CAS
- T. Wolff, I. Rabin, I. Mantouvalou, B. Kanngiesser, W. Malzer, E. Kindzorra and O. Hahn, Anal. Bioanal. Chem., 2012, 402(4), 1493–1503 CrossRef CAS
- W. G. Luo, Y. Si, H. M. Wang, Y. Qin, F. C. Huang and C. S. Wang, Spectrochim. Acta, Part A, 2011, 79(5), 1630–1633 CrossRef CAS
- K. Castro, E. Princi, N. Proietti, M. Manso, D. Capitani, S. Vicini, J. M. Madariaga and M. L. De Carvalho, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(12), 1401–1410 CrossRef CAS
- M. Zotti, A. Ferroni and R. Calvini, Int. Biodeterior. Biodegrad., 2011, 65(4), 569–578 CrossRef CAS
- R. Van Grieken and A. Worobiec, Pramana, 2011, 76(2), 191–200 CrossRef
- V. Kontozova-Deutsch, C. Cardell, M. Urosevic, E. Ruiz-Agudo, F. Deutsch and R. Van Grieken, Environ. Earth Sci., 2011, 63(7–8), 1433–1445 CrossRef CAS
- R. Kigawa, T. Strang, N. Hayakawa, N. Yoshida, H. Kimura and G. Young, Stud. Conserv., 2011, 56(3), 191–215 CrossRef CAS
- G. Zammit, S. Sanchez-Moral and P. Albertano, Sci. Total Environ., 2011, 409(14), 2773–2782 CrossRef CAS
-
M. P. Fiorucci, J. Lamas, A. J. Lopez, T. Rivas and A. Ramil, in International Conference on Applications of Optics and Photonics, ed. M. F. M. Costa, Spie-Int Soc Optical Engineering, Bellingham, 2011, vol. 8001 Search PubMed
- A. Saeed, Z. Khan, M. Clark, M. Nel and R. Smith, Insight, 2011, 53(7), 382–386 CAS
- I. Janos, L. Szathmary, E. Nadas, A. Beni, Z. Dinya and E. Mathe, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(21), 2593–2599 CrossRef CAS
- D. B. Thomas and A. Chinsamy, X-Ray Spectrom., 2011, 40(6), 441–445 CrossRef CAS
- G. Piga, A. Santos-Cubedo, A. Brunetti, M. Piccinini, A. Malgosa, E. Napolitano and S. Enzo, Palaeogeogr., Palaeoclimatol., Palaeoecol., 2011, 310(1–2), 92–107 CrossRef
- K. Nakano, C. Nishi, K. Otsuki, Y. Nishiwaki and K. Tsuji, Anal. Chem., 2011, 83(9), 3477–3483 CAS
- J. Zieba-Palus and B. M. Trzcinska, J. Forensic Sci., 2011, 56(3), 819–821 CrossRef CAS
- A. Li, Y. W. Yat, W. K. Yap, C. W. Lim and S. H. Chan, Food Chem., 2011, 129(2), 528–532 CrossRef CAS
- I. S. Khalikov and Y. I. Savin, Russ. Meteorol. Hydrol., 2011, 36(5), 315–323 CrossRef
- W. S. K. Bong, I. Nakai, S. Furuya, H. Suzuki, Y. Abe, K. Osaka, T. Matsumoto, M. Itou, N. Imai and T. Ninomiya, Chem. Lett., 2011, 40(11), 1310–1312 CrossRef CAS
- A. M. Christensen, M. A. Smith and R. M. Thomas, J. Forensic Sci., 2012, 57(1), 47–51 CrossRef CAS
- G. G. Shimamoto, B. Kazitoris, L. F. R. de Lima, N. D. de Abreu, V. T. Salvador, M. Bueno, E. V. R. de Castro, E. A. S. Filho and W. Romao, Quim. Nova, 2011, 34(8), 1389–1393 CrossRef CAS
- H. M. Stapleton, S. Klosterhaus, A. Keller, P. L. Ferguson, S. van Bergen, E. Cooper, T. F. Webster and A. Blum, Environ. Sci. Technol., 2011, 45(12), 5323–5331 CrossRef CAS
- S. Matsuyama, S. Kinugasa and H. Ohtani, Bunseki Kagaku, 2011, 60(3), 301–305 CrossRef CAS
- K. G. Lee, Y. K. Son, J. S. Lee, T. M. Noh and H. S. Lee, Trans. Nonferrous Met. Soc. China, 2011, 21, S160–S164 CrossRef
- Z. Hejzlar, J. Test. Eval., 2011, 39(1), 105–110 CAS
- Z. Hejzlar, J. Test. Eval., 2011, 39(1), 111–117 CAS
- L. Gredmaier, C. J. Banks and R. B. Pearce, Construct. Build. Mater., 2011, 25(12), 4477–4486 CrossRef
- M. Bouchard, J. Anzelmo, S. Rivard, A. Seyfarth, L. Arias, K. Behrens and S. Durali-Muller, Powder Diffr., 2011, 26(2), 176–185 CrossRef CAS
- N. M. Ahmed, H. S. Emira and M. M. Selim, Pigm. Resin Technol., 2011, 40(2), 91–99 CrossRef CAS
- N. M. Ahmed and M. M. Selim, Pigm. Resin Technol., 2011, 40(1), 4–16 CrossRef CAS
- C. M. Alonso-Hernandez, J. Bernal-Castillo, Y. Bolanos-Alvarez, M. Gomez-Batista and M. Diaz-Asencio, Fuel, 2011, 90(8), 2820–2823 CrossRef CAS
- M. Dorri and D. Harandizadeh, Eng. Failure Anal., 2012, 19, 87–96 CrossRef CAS
- F. Kirnbauer and H. Hofbauer, Energy Fuels, 2011, 25(8), 3793–3798 CrossRef CAS
- X. M. Meng, P. Benito, W. de Jong, F. Basile, A. H. M. Verkooijen, G. Fornasari and A. Vaccari, Energy Fuels, 2012, 26(1), 722–739 CrossRef CAS
- J. A. Hurst, J. A. Volpato and G. E. O'Donnell, X-Ray Spectrom., 2011, 40(2), 61–68 CrossRef CAS
- P. Gamaletsos, A. Godelitsas, T. J. Mertzimekis, J. Gottlicher, R. Steininger, S. Xanthos, J. Berndt, S. Klemme, A. Kuzmin and G. Bardossy, Nucl. Instrum. Methods Phys. Res., Sect. B, 2011, 269(24), 3067–3073 CrossRef CAS
- M. Malinouski, S. Kehr, L. Finney, S. Vogt, B. A. Carlson, J. Seravalli, R. Jin, D. E. Handy, T. J. Park, J. Loscalzo, D. L. Hatfield and V. N. Gladyshev, Antioxid. Redox Signaling, 2012, 16(3), 185–192 CrossRef CAS
- M. V. Kasaikina, A. V. Lobanov, M. Y. Malinouski, B. C. Lee, J. Seravalli, D. E. Fomenko, A. A. Turanov, L. Finney, S. Vogt, T. J. Park, R. A. Miller, D. L. Hatfield and V. N. Gladyshev, J. Biol. Chem., 2011, 286(19), 17005–17014 CrossRef CAS
- C. M. Weekley, J. B. Aitken, S. Vogt, L. A. Finney, D. J. Paterson, M. D. de Jonge, D. L. Howard, P. K. Witting, I. F. Musgrave and H. H. Harris, J. Am. Chem. Soc., 2011, 133(45), 18272–18279 CrossRef CAS
- X. Carpentier, D. Bazin, C. Combes, A. Mazouyes, S. Rouziere, P. A. Albouy, E. Foy and M. Daudon, J. Trace Elem. Med. Biol., 2011, 25(3), 160–165 CAS
- J. J. Liu, J. E. Kohler, A. L. Blass, J. A. Moncaster, A. Mocofanescu, M. A. Marcus, E. A. Blakely, K. A. Bjornstad, C. Amarasiriwardena, N. Casey, L. E. Goldstein and D. I. Soybel, PLoS One, 2011, 6(6), 10 Search PubMed
- E. J. Grasso, G. A. Bongiovanni, R. D. Perez and R. O. Calderon, Toxicology, 2011, 284(1–3), 26–33 CrossRef CAS
- M. Szczerbowska-Boruchowska, M. Lankosz and D. Adamek, JBIC, J. Biol. Inorg. Chem., 2011, 16(8), 1217–1226 CrossRef CAS
- B. F. G. Popescu and H. Nichol, CNS Neurosci. Ther., 2011, 17(4), 256–268 CrossRef CAS
- G. R. Pereira, H. S. Rocha, C. Calza, M. J. Anjos, I. Lima, C. A. Perez and R. T. Lopes, X-Ray Spectrom., 2011, 40(4), 260–264 CrossRef CAS
- S. C. Dodani, D. W. Domaille, C. I. Nam, E. W. Miller, L. A. Finney, S. Vogt and C. J. Chang, Proc. Natl. Acad. Sci. U. S. A., 2011, 108(15), 5980–5985 CrossRef CAS
- M. P. Jensen, D. Gorman-Lewis, B. Aryal, T. Paunesku, S. Vogt, P. G. Rickert, S. Seifert, B. Lai, G. E. Woloschak and L. Soderholm, Nat. Chem. Biol., 2011, 7(8), 560–565 CrossRef CAS
- B. P. Aryal, D. Gorman-Lewis, T. Paunesku, R. E. Wilson, B. Lai, S. Vogt, G. E. Woloschak and M. P. Jensen, Int. J. Radiat. Biol., 2011, 87(10), 1023–1032 CrossRef CAS
- L. Leoni, A. Dhyani, P. La Riviere, S. Vogt, B. Lai and B. B. Roman, Contrast Media Mol. Imaging, 2011, 6(6), 474–481 CrossRef CAS
- S. Zaichick and V. Zaichick, X-Ray Spectrom., 2011, 40(6), 464–469 CrossRef CAS
- Z. Polgari, Z. Ajtony, P. Kregsamer, C. Streli, V. G. Mihucz, A. Reti, B. Budai, J. Kralovanszky, N. Szoboszlai and G. Zaray, Talanta, 2011, 85(4), 1959–1965 CrossRef CAS
- M. L. de Moraes, R. D. Barbosa, R. E. Santo, F. D. Santos, L. B. de Almeida, E. F. O. de Jesus, F. L. D. Sardinha and M. D. T. do Carmo, Biol. Trace Elem. Res., 2011, 143(3), 1271–1281 CrossRef
- Y. P. Tong, H. B. Sun, Q. Luo, J. X. Feng, X. H. Liu, F. Liang, F. Yan, K. Yang, X. H. Yu, Y. L. Li and J. M. Chen, Biol. Trace Elem. Res., 2011, 142(3), 380–387 CrossRef CAS
- D. R. Chettle, Pramana, 2011, 76(2), 249–259 CrossRef CAS
- C. J. Lodwick, J. C. Lodwick and H. B. Spitz, Health Phys., 2011, 100(5), 502–507 CrossRef CAS
- S. Behinaein, D. R. Chettle, J. Atanackovic, L. M. Egden, D. E. B. Fleming, L. H. Nie, N. Richard and S. Stever, Phys. Med. Biol., 2011, 56(3), 653–665 CrossRef
- K. D. Eum, L. H. Nie, J. Schwartz, P. S. Vokonas, D. Sparrow, H. Hu and M. G. Weisskopf, Environ. Health Perspect., 2011, 119(7), 940–944 CrossRef CAS
- E. Wilker, S. Korrick, L. H. Nie, D. Sparrow, P. Vokonas, B. Coull, R. O. Wright, J. Schwartz and H. Hu, J. Occup. Environ. Med., 2011, 53(8), 850–855 CrossRef CAS
- M. Afeiche, K. E. Peterson, B. N. Sanchez, D. Cantonwine, H. Lamadrid-Figueroa, L. Schnaas, A. S. Ettinger, M. Hernandez-Avila, H. Hu and M. M. Tellez-Rojo, Environ. Health Perspect., 2011, 119(10), 1436–1441 CrossRef CAS
- J. L. Peters, L. D. Kubzansky, A. Ikeda, A. Spiro, R. O. Wright, M. G. Weisskopf, D. Kim, D. Sparrow, L. H. Nie, H. Hu and J. Schwartz, Am. J. Epidemiol., 2011, 174(12), 1345–1353 CrossRef
- M. C. Fortin, D. A. Cory-Slechta, P. Ohman-Strickland, C. Nwankwo, T. S. Yanger, A. C. Todd, J. Moynihan, J. Walton, A. Brooks and N. Fiedler, Environ. Health Perspect., 2012, 120(2), 278–283 CrossRef
- D. E. B. Fleming, M. R. Gherase and K. M. Alexander, X-Ray Spectrom., 2011, 40(5), 343–347 CrossRef CAS
- D. Guimaraes, M. L. Carvalho, V. Geraldes, I. Rocha and J. P. Santos, Metallomics, 2012, 4(1), 66–71 RSC
-
A. G. Diamantino, R. A. Nicolau, M. A. de Oliveira and A. M. E. Santo, in Medical Laser Applications and Laser–Tissue Interactions V, ed. R. Sroka and L. D. Lilge, Spie-Int Soc Optical Engineering, Bellingham, 2011, vol. 8092 Search PubMed
- C. Lange, C. Li, I. Manjubala, W. Wagermaier, J. Kuhnisch, M. Kolanczyk, S. Mundlos, P. Knaus and P. Fratzl, J. Struct. Biol., 2011, 176(2), 159–167 CrossRef CAS
- F. M. Gasperini, M. D. Calasans-Maia, R. F. B. Resende, J. M. Granjeiro, A. M. Rossi, R. T. Lopes and I. Lima, X-Ray Spectrom., 2012, 41(1), 6–11 CrossRef CAS
- M. Mehdikhani-Nahrkhalaji, M. H. Fathi, V. Mortazavi, S. B. Mousavi and S. M. Razavi, J. Biomed. Nanotechnol., 2011, 7(3), 460–465 CrossRef CAS
- I. Stanimirova, K. Michalik, Z. Drzazga, H. Trzeciak, P. D. Wentzell and B. Walczak, Anal. Chim. Acta, 2011, 689(1), 1–7 CrossRef CAS
- B. Pemmer, J. G. Hofstaetter, F. Meirer, S. Smolek, P. Wobrauschek, R. Simon, R. K. Fuchs, M. R. Allen, K. W. Condon, S. Reinwald, R. J. Phipps, D. B. Burr, E. P. Paschalis, K. Klaushofer, C. Streli and P. Roschger, J. Synchrotron Radiat., 2011, 18, 835–841 CrossRef CAS
- M. Gajda, J. Kowalska, A. Banas, K. Banas, W. M. Kwiatek, R. B. Kostogrys, L. Mateuszuk, S. Chlopicki, J. A. Litwin and K. Appel, Radiat. Phys. Chem., 2011, 80(10), 1072–1077 CrossRef CAS
- G. F. Molina, G. R. C. de Almeida, C. D. Guerra, J. A. Cury, A. P. de Almeida, R. C. Barroso and R. F. Gerlach, Caries Res., 2011, 45(5), 469–474 CrossRef CAS
- L. E. S. Soares, A. Brugnera, F. A. A. Zanin, A. M. E. Santo and A. A. Martin, Lasers Med. Sci., 2011, 26(5), 605–613 CrossRef
- S. R. Stock, A. Veis, A. Telser and Z. Cai, J. Struct. Biol., 2011, 176(2), 203–211 CrossRef CAS
- F. Berglund and B. Carlmark, Biol. Trace Elem. Res., 2011, 143(1), 1–7 CrossRef CAS
- M. R. Gherase and D. E. B. Fleming, Phys. Med. Biol., 2011, 56(20), N215–N225 CrossRef CAS
- L. Telgmann, M. Holtkamp, J. Kunnemeyer, C. Gelhard, M. Hartmann, A. Klose, M. Sperling and U. Karst, Metallomics, 2011, 3(10), 1035–1040 RSC
- J. G. Ray, R. Ghosh, D. Mallick, N. Swain, P. Gandhi, S. S. Ram, S. Selvaraj, A. Rathore, S. Mathummal and A. Chakraborty, Biol. Trace Elem. Res., 2011, 144(1–3), 295–305 CrossRef CAS
- T. S. Baptista, M. M. Redigolo, C. B. Zamboni, I. M. Sato and J. R. Marcelino, J. Radioanal. Nucl. Chem., 2012, 291(2), 399–403 CrossRef CAS
- M. I. Camejo, L. Abdala, G. Vivas-Acevedo, R. Lozano-Hernandez, M. Angeli-Greaves and E. D. Greaves, Biol. Trace Elem. Res., 2011, 143(3), 1247–1254 CrossRef CAS
- R. S. Ortiz, K. C. Mariotti, N. V. Schwab, G. P. Sabin, W. F. C. Rocha, E. V. R. de Castro, R. P. Limberger, P. Mayorga, M. Bueno and W. Romao, J. Pharm. Biomed. Anal., 2012, 58, 7–11 CrossRef CAS
- W. Romao, P. M. Lalli, M. F. Franco, G. Sanvido, N. V. Schwab, R. Lanaro, J. L. Costa, B. D. Sabino, M. Bueno, G. F. de Sa, R. J. Daroda, V. de Souza and M. N. Eberlin, Anal. Bioanal. Chem., 2011, 400(9), 3053–3064 CrossRef CAS
- V. Mazel, I. Reiche, V. Busignies, P. Walter and P. Tchoreloff, Talanta, 2011, 85(1), 556–561 CrossRef CAS
- X. D. Yuan, R. L. Chapman and Z. Q. Wu, Phytochem. Anal., 2011, 22(3), 189–198 CrossRef CAS
- B. Wu and J. S. Becker, Int. J. Mass Spectrom., 2011, 307(1–3), 112–122 CAS
- R. G. Ge, X. S. Sun and Q. Y. He, Curr. Drug Metab., 2011, 12(3), 287–299 CrossRef CAS
- D. V. Rao, M. Swapna, R. Cesareo, A. Brunetti, T. Akatsuka, T. Yuasa, T. Takeda and G. E. Gigante, Pramana, 2011, 76(2), 261–269 CrossRef CAS
- M. Spilde, A. Lanzirotti, C. Qualls, G. Phillips, A. M. Ali, L. Agenbroad and O. Appenzeller, PLoS One, 2011, 6(6), 14 Search PubMed
- E. Nakazawa, T. Ikemoto, A. Hokura, Y. Terada, T. Kunito, T. Yamamoto, T. K. Yamada, F. C. W. Rosas, G. Fillmann, S. Tanabe and I. Nakai, J. Environ. Monit., 2011, 13(6), 1678–1686 RSC
- E. Nakazawa, T. Ikemoto, A. Hokura, Y. Terada, T. Kunito, S. Tanabe and I. Nakai, Metallomics, 2011, 3(7), 719–725 RSC
- E. Lombi, M. D. de Jonge, E. Donner, P. M. Kopittke, D. L. Howard, R. Kirkham, C. G. Ryan and D. Paterson, PLoS One, 2011, 6(6), 5 Search PubMed
- S. Erdal and R. Dumlupinar, Biol. Trace Elem. Res., 2011, 143(1), 500–506 CrossRef CAS
- R. Evens, K. A. C. De Schamphelaere, B. De Samber, G. Silversmit, T. Schoonjans, B. Vekemans, L. Balcaen, F. Vanhaecke, I. Szaloki, K. Rickers, G. Falkenberg, L. Vincze and C. R. Janssen, Environ. Sci. Technol., 2012, 46(2), 1178–1184 CrossRef CAS
- J. C. Lye, J. E. C. Hwang, D. Paterson, M. D. de Jonge, D. L. Howard and R. Burke, PLoS One, 2011, 6(10), 8 Search PubMed
- M. R. Krejci, B. Wasserman, L. Finney, I. McNulty, D. Legnini, S. Vogt and D. Joester, J. Struct. Biol., 2011, 176(2), 192–202 CrossRef CAS
- T. M. Mascari, R. W. Stout and L. D. Foil, J. Med. Entomol., 2012, 49(1), 227–230 CrossRef CAS
- J. Dendooven, S. P. Sree, K. De Keyser, D. Deduytsche, J. A. Martens, K. F. Ludwig and C. Detavernier, J. Phys. Chem. C, 2011, 115(14), 6605–6610 CAS
- R. Mainz and R. Klenk, J. Appl. Phys., 2011, 109(12), 13 CrossRef
- S. Dill and V. Rössiger, Circuit World, 2011, 37(2), 20–26 CrossRef CAS
- C. E. R. Torres, F. Golmar, M. Ziese, P. Esquinazi and S. P. Heluani, Phys. Rev. B: Condens. Matter Mater. Phys., 2011, 84(6), 5 Search PubMed
- K. Devloo-Casier, J. Dendooven, K. F. Ludwig, G. Lekens, J. D'Haen and C. Detavernier, Appl. Phys. Lett., 2011, 98(23), 3 CrossRef
- A. Iida, X-Ray Spectrom., 2011, 40(5), 376–378 CrossRef CAS
- G. C. Chen, X. C. Chen, Y. Q. Yang, A. G. Hay, X. H. Yu and Y. X. Chen, Appl. Environ. Microbiol., 2011, 77(14), 4719–4727 CrossRef CAS
- S. I. Yang, J. R. Lawrence, G. D. W. Swerhone and I. J. Pickering, Environ. Chem., 2011, 8(6), 543–551 CrossRef CAS
- Y. Qu, W. Li, Y. L. Zhou, X. F. Liu, L. L. Zhang, L. M. Wang, Y. F. Li, A. Iida, Z. Y. Tang, Y. L. Zhao, Z. F. Chai and C. Y. Chen, Nano Lett., 2011, 11(8), 3174–3183 CrossRef CAS
- Y. Qu, Y. F. Li and C. Y. Chen, Prog. Chem., 2011, 23(7), 1534–1546 CAS
- P. Marmorato, G. Ceccone, A. Gianoncelli, L. Pascolo, J. Ponti, F. Rossi, M. Salome, B. Kaulich and M. Kiskinova, Toxicol. Lett., 2011, 207(2), 128–136 CrossRef CAS
- Y. Morishita, K. Yamashita, T. Yoshikawa, Y. Terada, H. Nabeshi, Y. Yoshioka, N. Itoh and Y. Tsutsumi, Pharmazie, 2011, 66(10), 808–809 CAS
- R. Unterumsberger, B. Pollakowski, M. Muller and B. Beckhoff, Anal. Chem., 2011, 83(22), 8623–8628 CrossRef CAS
- J. Segura-Ruiz, G. Martinez-Criado, M. H. Chu, S. Geburt and C. Ronning, Nano Lett., 2011, 11(12), 5322–5326 CrossRef CAS
- C. R. Durham, J. M. Chase, D. A. Nivens, W. H. Baird and C. W. Padgett, J. Chem. Educ., 2011, 88(6), 819–821 CrossRef CAS
- D. Sokaras, A. G. Kochur, M. Muller, M. Kolbe, B. Beckhoff, M. Mantler, C. Zarkadas, M. Andrianis, A. Lagoyannis and A. G. Karydas, Phys. Rev. A: At., Mol., Opt. Phys., 2011, 83(5), 12 CrossRef
- S. Porikli and Y. Kurucu, J. Radioanal. Nucl. Chem., 2011, 289(3), 739–750 CrossRef CAS
- I. Tsuyumoto and Y. Maruyama, Anal. Chem., 2011, 83(19), 7566–7569 CrossRef CAS
- G. Silversmit, B. Vekemans, K. Appel, S. Schmitz, T. Schoonjans, F. E. Brenker, F. Kaminsky and L. Vincze, Anal. Chem., 2011, 83(16), 6294–6299 CrossRef CAS
- E. Curti, D. Grolimund and C. N. Borca, Appl. Geochem., 2012, 27(1), 56–63 CrossRef CAS
- L. E. Mayhew, S. M. Webb and A. S. Templeton, Environ. Sci. Technol., 2011, 45(10), 4468–4474 CrossRef CAS
- Y. F. Hu, H. Piao, J. Fronheiser and K. Matocha, J. Electron Spectrosc. Relat. Phenom., 2011, 184(3–6), 245–248 CrossRef CAS
- S. Kikuchi, H. Makita, S. Mitsunobu, Y. Terada, N. Yamaguchi, K. Takai and Y. Takahashi, Chem. Lett., 2011, 40(7), 680–681 CrossRef CAS
- Y. Tamenori, M. Morita and T. Nakamura, J. Synchrotron Radiat., 2011, 18, 747–752 CrossRef CAS
- J. Prietzel, I. Kogel-Knabner, J. Thieme, D. Paterson and I. McNulty, Org. Geochem., 2011, 42(10), 1308–1314 CrossRef CAS
- J. J. Leani, H. Sanchez, M. Valentinuzzi and C. Perez, X-Ray Spectrom., 2011, 40(4), 254–256 CrossRef CAS
Footnote |
| † Review coordinator. |
| This journal is © The Royal Society of Chemistry 2012 |