2019 atomic spectrometry update – a review of advances in X-ray fluorescence spectrometry and its special applications

Christine Vanhoof a, Jeffrey R. Baconb, Andrew T. Ellisc, Ursula E. A. Fittschend and Laszlo Vinczee
aFlemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium. E-mail: Christine.vanhoof@vito.be
b59 Arnhall Drive, Westhill, Aberdeenshire, AB32 6TZ, UK. E-mail: bacon-j2@sky.com
c8 Burgess Close, Abingdon, OX14 3JT, UK
dClausthal University of Technology, Institute of Inorganic and Analytical Chemistry, Arnold-Sommerfeld-Strasse 4, D-38678 Clausthal-Zellerfeld, Germany
eGhent University, Department of Chemistry, Krijgslaan 281 S12, B-9000 Ghent, Belgium

Received 28th June 2019 , Accepted 28th June 2019

First published on 10th July 2019


This review describes advances in the XRF group of techniques published approximately between April 2018 and March 2019. The review is selective with the aim of providing a critical insight into developments in instrumentation, methodologies and data handling that represent a significant advance in XRF spectrometry. It is not the intention of the review to cover comprehensively the applications of XRF techniques except in those cases where the non-destructive and remote sensing nature of XRF analysis makes it particularly valuable and the method of choice. These applications concern samples which are irreplaceable and of great cultural value such as works of art and archaeological artefacts.


1 Introduction

This year sees the departure of Peter Wobrauschek from the writing team after many years of providing incisive insights into XRF developments. Peter was a pioneer in the development and application of polarised XRF and TXRF techniques and was instrumental in introducing these techniques into laboratories around the world. His contributions will be missed but we are pleased to welcome Ursula Fittschen to the writing team to maintain a high level of critical assessment of developments in TXRF spectrometry.

Only in those cases where XRF spectrometry is the method-of-choice and is unlikely to be considered in the application ASUs do we highlight the unique advantages of remote sensing and non-destructive analysis. Such applications are primarily for the purpose of analysing samples of cultural value such as works of art and archaeological artefacts which are irreplaceable. For other applications, readers are referred to the ASUs on the analysis of environmental samples,1 clinical and biological materials, foods and beverages2 and metals, chemicals and materials3 as well as the ASU on elemental speciation.4

A notable development was the use of a multilayer monochromator both as an efficient high-Z Bragg reflector and as a low pass filter for low-Z excitation. This made it possible to improve the LODs of the low-Z elements without the need for individual setups. The problems in sample preparation and calibration posed by slurry sampling TXRF spectrometry has continued to receive attention. Approaches adopted to address matrix issues included the use of calibration strategies from “conventional” XRF spectrometry, the small volume approach and the separation of analytes from the matrix without the need for harmful chemicals. The use of analyte pre-concentration strategies has made it possible to lower LODs for elements such as Np and Hg in waters and ambient air such that it is now possible to measure Hg in aqueous solution with ppt LODs. The combination of GI-XRF spectrometry and XRR using laboratory sources with dedicated software is becoming a powerful non-destructive tool to study surface and ultra-shallow thin films in semiconductor materials. A 2D scanner designed for elemental and molecular spectroscopic imaging of paint works and paper samples collected data simultaneously from XRF spectrometry and FORS image cubes. Because the sample rather than the detectors was moved, multiple point-based spectroscopy modalities could easily be added to the analytical system.

A key development was the use of micro- and nano-scanning SR XRF spectrometry together with complementary techniques such as tomography, XAS and (coherent) diffraction imaging. Spatial resolutions of better than 30 nm in the hard X-ray regime made it possible to carry out elemental nanoanalysis in special sample environments such as cryogenic conditions. The availability of sub-μm- and nano-XRF spectrometry facilities has given rise to the emerging field of in situ/in operando nanoanalysis used in e.g. catalysis research and characterisation of new types of energy generation and storage devices.

A list of abbreviations used in this review appears at the end. Although these abbreviations may not always be used in a strictly grammatically correct manner, the writing team feels that it is important to use terminology that would be easily recognised and understood by the XRF community. It is a convention of ASUs that information given in the paper being reported on is presented in the past tense whereas the views of the ASU reviewers are presented in the present tense. An italicised phrase close to the beginning of each paragraph is intended to highlight the subject area of that individual paragraph.

2 Chemical imaging using X-ray techniques

2.1 Computed tomography and 3D XRF techniques

2.1.1 X-ray fluorescence computed tomography (XRF-CT). We continue to see improvements in spatial resolution, sensitivity and speed of analysis achievable using XRF-CT. Highly focused and intense laboratory and synchrotron X-ray beams are becoming increasingly available and acquisition rates are also increasing. At synchrotron radiation facilities, the technique is regularly applied with sub-μm spatial resolution in combination with complementary imaging modalities such as absorption and phase-contrast CT, XRD-CT, 2D and 3D XAS and ptychography. Possibly the highest resolution XRF-CT experiment to date was reported by Victor et al.5 who demonstrated XRF nanotomography using a sub-15 nm beam produced by Multilayer Laue Lenses at the Hard X-ray Nanoprobe beamline at NSLS-II (Brookhaven, USA). The 3D distributions of minor and trace elements (Ca, Cl, Zn) in intact E. coli cells embedded in small (5–20 μm wide, 1–2 μm thick) NaCl crystals were imaged with an estimated spatial resolution of 36 × 36 nm2. Ptychography was used simultaneously to associate the trace elements with subcellular structures. This approach presented new possibilities in understanding subcellular biochemistry in individual organelles and other subcellular compartments.

In a remarkable study, Deng et al.6 demonstrated the use of 3D XRF in combination with ptychographic tomography to study frozen-hydrated green algae (C. reinhardtii) with a spatial resolution of 130–140 nm in all three dimensions. The study was made using the bionanoprobe beamline, a hard X-ray nanoprobe with cryogenic sample environment and transfer capabilities at the Advanced Photon Source in Argonne National Laboratory (USA). Both XRF-CT and ptychographic datasets were reconstructed by means of the new generalized Fourier iterative reconstruction software (GENFIRE), which was superior to conventional methods such as approaches based on filtered back projection. The combination of X-ray ptychography and XRF-CT made it possible to image a whole frozen-hydrated C. reinhardtii cell in 3D, thereby providing distributions of Ca, Cl, K, P and S within various organelles together with information on the cell’s complex ultrastructure.

Another beautiful example of the use of sub-μm XRF-CT in combination with XAS was given by Nijem et al.7 who characterised Pt–Re bimetallic-nanoporous-network (BNN) particles for catalysis applications. The applied spatial resolution during this experiment (0.5 μm) at the P06 beamline of PETRA III (Hamburg, Germany) was sufficient to observe the decrease in Re surface concentration as the reduction temperature during the particle synthesis was gradually increased from 150 to 350 °C. The XRF tomography measurements showed that process was associated with partial surface segregation of Re. The presence of highly oxidised Re7+ species, as confirmed by XAS measurements, was considered essential for maximising the reactivity of the Pt–Re BNN.

The laboratory-based XRF-CT technique has been developed mainly for biomedical applications such as the 3D detection and visualisation of high-Z contrast agents and NPs in small animals and biological materials. Dunning and Bazalova-Carter8 optimised a table-top system using pencil beam excitation for combined K-shell and L-shell XRF-CT imaging of gold NPs in biological objects. The optimisation was based on Monte Carlo simulations using the GEANT4 toolkit and using a 2.5 cm diameter cylindrical water phantom containing 4 mm diameter vials with gold NPs at concentrations of 0.1–2% by weight. The simulations showed that the use of eight detectors (CdTe detectors or SDDs) in a backscattered grid arrangement gave optimal performance and provided lowest detectable concentrations of 0.055 and 0.095% for K-shell and L-shell XRF-CT systems, respectively. A similar study based on Monte Carlo simulations using GEANT4 concerned9 the performance of a benchtop multi-pinhole XRF-CT imaging system, also optimised for the detection of gold NPs. For a PMMA phantom, an image resolution of 0.88–1.38 mm could be obtained with a configuration of multiple pinholes of 1 mm diameter. This system could be used to detect concentrations of gold NPs in solutions of ca. 0.09 wt%, superior to the 0.13 wt% LOD of a single pinhole configuration. The development and validation of a GEANT4-based Monte Carlo simulation code for a novel XRF-CT instrument was reported by Ahmed et al.10 Although the study was similar to the others, it went further by validating the Monte Carlo calculations using rigorous comparisons of simulated and experimental XRF-CT data.

A notable example of a new XRF-CT setup gave11 high-spatial-resolution XRF tomography optimised for the imaging of metal-core NPs in biological matter. The setup incorporated a liquid–metal-jet (In) microfocus source (ca. 5 μm), multilayer optics and two energy-dispersive detectors for XRF detection and for absorption CT and was demonstrated by the 3D imaging of molybdenum NPs in mice tumours using passive targeting. The source, operated at 170 W and 120 kV, produced a flux of 6 × 1011 photons per s per sr in the 24.14 keV In Kα line, sufficient to achieve 200 μm spatial resolution at exposure times, NP doses and radiation doses suitable for in vivo experiments.

2.1.2 Confocal-XRF spectrometry. Confocal-XRF spectrometry can be considered a well-established technique for 2D and 3D analyses, performed regularly at both laboratory and synchrotron radiation setups. A significant instrumental development, reported by Hampai et al.,12 was the “rainbow X-ray” (RXR) confocal-XRF experimental station at XLab Frascati of Frascati’s National Laboratories (Italy). The flexible RXR layout allowed the investigation of large objects with dimensions ranging from mm to half a meter and weighing several tens of kg to be made. The instrument was optimised for high XRF energies for cultural heritage and geological applications. The spatial resolution was ca. 70 × 70 × 100 μm3 and the LOD for Au was 25 ± 1 μg g−1 when using L-line detection. Use of the RXR instrument was demonstrated13 by 3D-XRF imaging on a phantom sample composed of an organic matrix with a high-Z analyte.

A dual approach using confocal XRF spectrometry to provide elemental information on a well-defined volume at a given depth and micro-spatially offset Raman spectroscopy (μ-SORS) for molecular information represented14 a new analytical tool for combining elemental and molecular information at the μm scale, thereby extending the accessible depths beyond those available with conventional methods. Micro-SORS could be applied in situations in which high turbidity prevented acquisition of conventional Raman signals from a given depth. This dual approach was demonstrated by the non-destructive investigation of μm-scale stratified paint layers.

2.2 Laboratory 2D XRF techniques

A major advantage of 2D μ-XRF spectrometry over many other elemental microscope techniques is in situ analysis with minimal sample preparation. Polishing, drying or cryostatting of the samples can often be omitted. The possibility of analysing non-conductive samples without the need for a vacuum has been exploited in nearly all areas of plant science. Rodrigues et al.15 presented an overview on the applicability of μ-XRF spectrometry (beam diameter of ca. 30 μm at 8.64 keV, information depth for Zn Kα in a typical plant leaf matrix ca. 700 μm) to study the ionome of plant organs at a microscopic level. Quantitative information was obtained by using sensitivities derived from thin metal foils and by applying an absorption correction determined by acquiring the signal of a Zn foil through pressed pellets of cellulose. The pellets were spiked with a range of Zn concentrations to mimic different degrees of Zn accumulation in generic plant tissue. The review also covered the in vivo study of leaves and roots which was shown16 to be feasible without observable damage to the photosynthetic activity. The short (1 s) real-time exposure of the plant leaf meant that the photosynthesis impairment observed with a 4× longer irradiation time was avoided.

Plants and cultural heritage samples often do not exhibit a planar surface. The sample topology usually results in a varying distance between the sample surface and the optic while scanning and results in variations in the spatial resolution and bias. Duan et al.17 built a compact μ-XRF instrument which incorporated real-time adjustment of the sample-to-polycapillary optic working distance. A laser displacement sensor and a programmable logic controller were used to maintain the distance to the laser source at 60 ± 0.02 mm and thereby to reduce deviations in peak intensity to below 10%. The largest distance deviation (16 mm) for pottery samples due to their curvature resulted in a deviation of 96% in the Fe Kα peak intensity. Although the relatively large focal spot of 190 μm led to a large optic focal distance of 38 mm, this method should be adoptable by other researchers working at shorter working distances.

Low power and miniature X-ray sources, as exemplified by the palm-size spectrometers built by the group at Kyoto University, have widened the field of application of XRF spectrometry. Inspired by the report by Ida and Kawai18 in 2005 of a novel spectrometer incorporating a pyroelectric X-ray source powered by a commercial 9 V battery, Wilke et al.19 optimised a pyroelectric source setup for μ-XRF applications using lithium niobate and lithium tantalate crystals for electron emission and a polycapillary lens as focusing optic. Electron self-focusing of the applied rectangular crystals occurred. They optimised the output spectrum by addressing the following five parameters in sequence: self focussing; crystal area; set up geometry; target angle and output energy. A lithium tantalate crystal of ca. 25 mm2 area in an emission geometry of 12° and a pressure of 2 × 10−3 mbar was optimal with respect to output intensity (106 counts per 600 s) and gave a good reproducibility on Cu Kα line net intensities (<1%). The intensity loss due to the applied optics was high at 97% when a distance of 5 mm from the tube window was used with a 1.5 mm diameter aperture and 99.9% at a distance of 13.5 mm when a polycapillary optic was used. Nevertheless, the authors remained optimistic about the potential for application in material sciences and advances in this field of ultra-low power tubes will be highly interesting.

Whereas synchrotron-based μ-XRF spectrometry is mainly used to locate the area of interest for further 2D XANES studies, Veith et al.20 evaluated laboratory μ-XRF spectrometry as a tool to locate cerium NPs in biological tissue prior to TOF-SIMS analysis. This approach was proposed as a means of reducing analysis time substantially. The spatial resolution achievable by μ-XRF analysis was only ca. 25 μm whereas the TOF-SIMS analysis had a lateral resolution of <1 μm, yet the authors considered the approach to be successful.

3 Synchrotron and large scale facilities

3.1 Instrumentation and method development

As illustrated by a number of papers during this review period, one of the key aspects of development was the combination of complementary techniques with scanning XRF spectrometry. A leading example of combining and clustering spectroscopic techniques at synchrotron facilities was given by Diaz-Moreno et al.21 who reported on the current status and technical details of the Spectroscopy Village at the Diamond Light Source (Harwell, UK). The so-called Diamond Spectroscopy Village consisted of four fully operational beamlines and included a hard X-ray microprobe (I18), a quick-scanning multi-purpose XAS beamline (B18), a high-intensity beamline for XAS of dilute samples, X-ray emission spectroscopy and an EXAFS beamline (I20-Scanning and I20-EDE). Microbeam XRF spectrometry was one of the core techniques offered by beamline I18 which used Kirkpatrick–Baez mirrors to focus the X-ray beam down to a spot size smaller than 2 × 2 μm2. The elemental imaging provided by XRF analysis was used with data provided by XAS and XRD analyses. Use of SDDs (Vortex ME-4, crystal thickness 1 mm) for XRF and XAS measurements and new preamplifiers combined with advanced custom readout-electronics gave a total usable XRF input count-rate for the two-detector setup of 12 Mcps.

A very interesting development was reported by Edwards et al.22 who developed a large-range continuous-rapid-scan XRF imaging station at the SSRL at SLAC National Accelerator Laboratory (Stanford, USA). The station incorporated the latest technology in terms of detection and signal processing and provided scanning over an area of 1000 × 600 mm2, and a load capacity of up to 25 kg. The instrument was capable of performing elemental XRF mapping and XAS of a wide range of materials with a spatial resolution of 25–100 μm. Further development will aim to achieve a spatial resolution below 10 μm. The typical dwell-times of 3–5 ms per pixel for scanning areas of hundreds of mm squared allowed Mpixel elemental images to be acquired in an impressive scanning time of only a few hours.

The new XRF beamline jointly operated by IAEA and the synchrotron facility Elettra (Trieste, Italy) was evaluated in terms of its analytical capabilities by Marguí et al.23 for multipurpose TXRF analysis. The instrument was developed to meet the growing demand for high sensitivity trace element analysis at concentration levels lower than 1 ppm as required by a large number of environmental, biological and material science applications. Using an excitation energy of 13.0 keV, elements from Na (Z = 11) up to Se (Z = 34), using K-lines, and from Rb (Z = 37) up to Tl (Z = 81), using L-lines, could be measured under vacuum conditions using an ultrathin window SDD with a nominal area of 30 mm2 and crystal thickness of 450 μm. The LODs for low-Z elements (Z < 23) in liquid samples were 3 μg L−1 and in geological and biological solid samples 0.7–0.9 mg kg−1. The LODs for medium atomic number elements (22 < Z < 35) in liquid samples were all <1 μg L−1 and, for some elements (e.g. Cu), as low as 0.1 μg L−1. For solid samples, the LODs were 0.03–4 mg kg−1 using an acquisition time of ca. 600 s.

In the context of spatially resolved elemental analysis, Rauwolf et al.24 presented a detailed characterisation of a new setup for sub-μm XRF analysis installed on the B16 beamline at the Diamond Light Source. Using excitation energy values of 17.0 and 12.7 keV, the beam size was 500 × 600 nm2. The absolute LOD values for a total acquisition time of 1000 s ranged from 92 ag (Ca) to 5 ag (Zn) and 4 ag (As). The setup was particularly suitable for imaging biological samples such as bone and single cancer cells at sub-μm spatial resolution.

A flexible and customisable X-ray imaging end station developed for synchrotron radiation facilities was presented by Nisius et al.25 The setup could be used for full-field X-ray microscopy, scanning transmission X-ray microspectroscopy (STXM) and XRF microscopy, as well as ptychographic and X-ray holographic imaging, at resolutions in the sub-50 nm range. The end station was described in detail by Andrianov et al.26 for soft X-ray STXM and scanning XRF microscopy. One particularly interesting feature of the setup, apart from its modular concept, was the highly efficient XRF detection capability due to the large solid angle (>1 sr) of the integrated ultrathin-window SDD. The setup was optimised for soft X-ray (<1 keV) bioimaging applications, as illustrated by STXM combined with XRF elemental imaging of C in adipose mice tissue at 100 nm resolution. Further development was aimed at performing analyses under cryogenic conditions.

Boesenberg et al.27 described an important upgrade at the hard X-ray microprobe endstation P06, PETRA III, DESY to enable fast fluorescence mode XANES imaging to be performed. The method made use of a Maia detector and combined XANES measurements with rapid raster scanning of the sample through the focused beam. As demonstrated by XANES mapping experiments on a Ta/Ta2O5 test structure and on a geological thin-section sample containing As-apatite, coordinated monochromator and undulator scanning in combination with 2D XRF scanning enabled acquisition of spectromicroscopy maps. Each XANES spectrum could be acquired in 0.2–30 s in the fluorescence mode. Comparison of XANES spectra from static samples with those recorded in fast mapping mode gave excellent agreement at the single-pixel level. A similar setup for time-resolved fluorescence-mode XAS, described by Guda et al.,28 achieved sub-s time resolution. The setup offered new opportunities for kinetic studies of highly absorbing or dilute materials, including a large variety of heterogeneous catalysts and photocatalysts, which cannot be investigated using conventional transmission-based XAS. The setup was demonstrated at the SuperXAS beamline of the Swiss Light Source (Villigen) at the Paul Scherrer Institute by investigating the kinetics of the reversible evolution of Ce and Pt states in a 1.5 wt% Pt/CeO2 catalyst during redox cycling in CO- and O2-containing atmospheres at 47 °C and 150 °C. The impressive time resolution of up to 20 ms when taking full XAS spectra pushed the limits of time-resolved fluorescence-mode XAS.

Advances in source brilliance and XRF detection methodologies have stimulated renewed interest in XRF holography (XFH) which is used to determine atomic structure by combining the capabilities of XRF and XRD analyses. A comprehensive review of this atomic resolution technique presented by Hayashi and Korecki29 discussed the relevant experimental and theoretical aspects that are essential for the efficient data collection and analysis of XRF holograms and detailed the most recent advances in XFH. Bortel et al.30 showed that high-fidelity atomic positions can be reconstructed from a single-excitation-energy hard-XRF hologram by using the so-called ‘inside-source’ concept, in which the atoms (in this case Ni) serve as internal sources of XRF emission. A statistically meaningful XFH pattern could be taken in 1 s at ESRF ID18 with a photon intensity of ca. 1012 photons per s at an incident energy 14.4 keV. Ang et al.31 developed the XFH method further as a valence sensitive technique by recording XRF holograms of a single crystal Fe3O4 (magnetite) sample at various incident energies near the Fe-K absorption edge. The experiments were performed using beamline BL39XU of the SPring-8 SR facility (Japan) and demonstrated for the first time the recording of valence-sensitive XRF holograms by direct imaging using a modern 2D hybrid detector.

3.2 Fundamental parameter (cross sections and fluorescence yields) studies

High-intensity, highly monochromatic and tunable-energy SR provides an ideal excitation source for performing studies aimed at improving atomic fundamental parameter (FP) data such as X-ray matter interaction cross sections, fluorescence yields and XRF transition probabilities. In the framework of the International Initiative on X-ray Fundamental Parameters, Guerra et al.32 provided a detailed comparison of experimental and theoretical data on fluorescence and Coster–Kronig (CK) yields for the K and L shells of Ni. The Dirac–Fock method, including relativistic and QED corrections, was used to derive the binding energy values and K- and L-shell fluorescence and CK yields. The experiments for the FP determinations were performed at beamlines within the PTB laboratory at the BESSY II synchrotron radiation facility in Berlin. Although the theoretical and experimental K-shell results were in good agreement, there were large percentage discrepancies between theoretical and experimental values for the L-shell fluorescence and CK yields. These discrepancies may have been due to condensed-matter binding effects within the bulk metal samples which had not been taken into account in the theoretical calculations. Similar studies performed by Ménesguen et al.33 at the Metrology beamline of the SOLEIL synchrotron facility (Saint-Aubin, France) had the aim of determining experimental and theoretical L-fluorescence yields of Bi. There were small deviations between experimental values and theoretical data for X-ray energies > 1 keV. Large discrepancies were found only around the L absorption edges. New values for the partial L fluorescence yield were in excellent agreement with the theoretical calculations.

Hiremath et al.34 investigated the effects of crystal structure on radiative vacancy transfer probabilities from L3 to Mi, Ni and Oi subshells for a number of Bi, Hg and Pb compounds. The radiative vacancy transfer probabilities, ηL3-Xi (X = M, N, O; i = 1, 4, 5), were strongly dependent on the crystal structure but independent of oxidation state and chemical bonding. Using the XRF beamline (10.1 L) of the ELETTRA SR facility (Italy), Kaur et al.35 studied the influence of chemical environment on the Li (i = 1–3) subshell XRF intensity ratios and the L3 absorption-edge energy for selected compounds of Dy. The measured L-line intensity ratios were compared with values calculated using non-relativistic Hartree–Fock–Slater-model-based photoionisation cross-sections, the Dirac–Fock-model-based X-ray emission rates and two sets of fluorescence and CK yields. Differences between theoretical and experimental values of up to 36% were attributed to the combined influence of chemical effects and the presence of multiple bodies.

3.3 Emerging topics in synchrotron-based elemental imaging

Synchrotron-based scanning XRF analysis with truly nanoscopic spatial resolution plays an increasingly significant role in biomedical, environmental and material science applications due to its high (trace-element) sensitivity and non-invasive nature, especially when combined with other imaging and spectroscopic modalities. The examples presented in this section illustrate the emerging possibilities offered by SR-based elemental and structural imaging with nanoscale spatial resolution.

A high-spatial-resolution study on Mn accumulation within nanovesicles of the Golgi apparatus of human cells clarified36 the role of a particular cell mutation (SLC30A10) which can lead to Parkinson-like syndromes when elevated Mn exposure occurs. Imaging results obtained at PETRA III P06 (Hamburg) and ESRF ID16A (Grenoble) were used with the latter facility reaching a spatial resolution of 50 nm under cryogenic measuring conditions. Only very small amounts of Mn were detected, even after high exposure, in cells expressing the functional SLC30A10 protein so Mn had been expelled efficiently from the cells. In case of the mutant SLC30A10 protein, excess Mn remained stored within the Golgi vesicles and so was likely to disturb the Golgi functions.

Pushie et al.37 provided a review on the use of synchrotron-based XRF, XAS and FTIR imaging techniques for studying the chemical mechanisms of normal and abnormal brain function. The capability of synchrotron micro- and nano-probes for carrying out direct and label-free elemental and chemical imaging made these techniques suitable not only for neuroscience studies but also for broader health and biological science studies. In an associated study on the effects of stroke, Pushie et al.38 used synchrotron-based XRF imaging to visualise changes in elemental distributions in undamaged penumbra (cells surrounding the core of the stroke lesion) and infarct brain tissue. The XRF imaging of mice brain tissue sections was carried out at the SSRL on beamline 10−2 with an incident energy of 13.45 keV using a microbeam of approximately 35 × 35 μm2. Quantitative results indicated an increase in Ca and Cl concentrations in the affected regions of interest but a significant decrease in the concentrations of most other elements, including Cu, Fe, K, Mn, P, S and Zn. In an effort to find ways to mitigate the long term effects of ischemic strokes, synchrotron XRF microscopy and XAS were used by Wedding et al.39 to examine the cellular distribution and speciation of Se in SH-SY5Y cells pre-treated with one of two diphenyl diselenides. Treatment with peroxide was used to mimic the effects of ischemic strokes. Whereas bis(2-aminophenyl)diselenide protected against the oxidative stress conditions caused by ischemic strokes, its nitro analogue bis(2-nitrophenyl)diselenide did not.

Cancer research is an area of study in which synchrotron-based elemental imaging and spectroscopy are becoming more widely used. Sanchez-Cano et al.40 used the detection of Os L-lines and the excitation of the Os LIII edge when using microfocus synchrotron XRF imaging and spectroscopy at the Diamond synchrotron beamline I18 in order to demonstrate that an organo-Os metallodrug candidate penetrated efficiently into the interior of A2780 human ovarian cancer cell spheroids.

Elemental and chemical-state imaging remain important techniques in environmental science studies. A noteworthy review article by Chen et al.41 discussed the application of SR-based XRF, XAS and XRD techniques for the analysis of radioactive microparticles emitted from the Fukushima Daiichi Nuclear Power Plant. The review summarised separation and measurement technologies and emphasised the application of SR-based techniques to the characterisation of the microparticles as well as the use of SR microbeams to provide spatial resolution and sensitivity substantially superior to those achievable with conventional XRF and XRD analyses. The complementary μ-XAS measurements could also be applied to speciation studies.

Heavy metal pollution in soils has received a lot of attention in recent decades and is regularly investigated by synchrotron XRF and associated spectroscopic techniques. Understanding the distribution and binding behaviour of metal ions in organomineral composites in soils is important in order to predict metal mobility and fate in the environment. Du et al.42 used synchrotron-based XRF imaging to determine the distributions of Cd, Cu and Ni within an organo-goethite composite made with Bacillus cereus cells. The BL15U1 beamline of the Shanghai Synchrotron Radiation Facility was used with a spot size of 2 μm2 for the elemental imaging studies which, combined with complementary XPS measurements, indicated that the B. cereus cells were more effective for removal of Cd, Cu and Ni from solution than goethite. The goethite–B. cereus composite exhibited an intermediate metal sorption behaviour.

The use of two species of plants (Brassica napus and Festuca arundinacea) for the phytoremediation of Pb-contaminated soils was investigated by Mera et al.43 using SR μ-XRF techniques at the D09B XRF Fluorescence beamline of the Brazilian Synchrotron Light Laboratory. The spatial distributions of Pb in the roots and leaves of living plants confirmed that Brassica napus extracts Pb from the soil and relocates it in its leaves, thereby making it a suitable candidate for the phytoremediation of contaminated soils.

Chen et al.44 studied the mechanism with which Rhizophagus irregularis (an arbuscular mycorrhizal fungus) improved plant tolerance to Cd contamination. The uptake of Cd by Lotus japonicus and its localisation in the mycorrhizal roots at the sub-cellular level were studied using SR μ-XRF spectrometry at BL37XU of Spring-8 (Japan). The results provided direct evidence that the intraradical immobilisation of Cd by arbuscular mycorrhizal fungi contributed largely to the protection of the host plant against Cd contamination.

Very high spatial-resolution (20–100 nm) nano-XRF analyses were performed at the nano-imaging beamline ID16A of the ESRF in Grenoble (France) by Vigani et al.45 to investigate the subcellular Zn distribution in Fe-deficient leaf cells of cucumber plants and to have a greater understanding of the Zn interaction with Fe homeostasis. Under Fe-deficiency conditions, Zn accumulated both in chloroplasts and, to a lesser extent, in mitochondria of the cells. These findings highlighted the importance of investigating further Fe and Zn interaction at the subcellular level.

Siebecker et al.46 used SR-based μ-XRF, μ-XAS and μ-XRD techniques to identify naturally occurring Ni-rich soils (e.g. serpentine soils and ultramafic laterites). An important conclusion of the work was that many of the identified minerals, whether iron oxides or layered phyllosilicates, could affect Ni release into solution and Ni mobility in the environment and so the relationship between serpentine soils, Ni trace metal mobility and associated environmental risks could be better understood.

A subject of intense interest is the fate and effects of engineered NPs in the environment as they pose a risk to human health and the ecosystems. The transformation of cerium oxide NPs (CeO2-NPs) in soil and their role in plant uptake was the subject of a study performed by Rico et al.47 who investigated the reduction and speciation of CeO2-NPs in barley (Hordeum vulgare L.) cultivated in soil amended with 250 mg CeO2-NPs per kg soil. Synchrotron μ-XRF spectrometry was employed to determine the spatial distribution and μ-XAS to study the speciation of CeO2-NPs at the soil–root interface. Most of the Ce (84–90%) was localised in the soil and at the root surface in its NP form (84–90%). In a few “hot spots” on the root surfaces, a highly significant reduction (56–98%) of CeIV to CeIII occurred suggesting that reduction of CeO2-NPs to CeIII was needed to facilitate uptake of Ce by the roots. Servin et al.48 investigated the interactions of CeO2-NPs with biochar and soil components which could substantially influence NP availability and toxicity to biota. Earthworms (Eisenia fetida) were exposed for 28 days to a residential or agricultural soil contaminated with CeO2-NPs (0–2000 mg kg−1) and with biochar under various conditions. Cerium localisation, speciation and persistence in the exposed earthworms after depuration for 12, 48, and 72 h were studied using μ-XRF spectrometry and μ-XANES at ESRF ID21.

The emerging field of in situ/in operando nanoanalysis is increasingly taking advantage of the sub-μm- and nano-XRF capabilities offered by a growing number of SR facilities. A leading example of combining nano-XRF spectrometry data and X-ray beam induced current measurements was presented by Correa-Baena et al.49 who studied the role of the alkali metal cations in halide perovskite solar cells. The nano-XRF spectrometry experiments used a 250 nm (FWHM) focused beam at 16.3 keV at beamline 2-IDD of the Advanced Photon Source at Argonne National Laboratory. The results were used to elucidate the elemental distribution of the alkali metals and their relation to electronic properties and device performance. Luo et al.50 reviewed how the nanoscale elemental distribution and charge collection in hybrid perovskite materials evolved as chemical complexity increased and highlighted recent results from non-destructive in operando synchrotron-based X-ray nanoprobe spectroscopy. Synchrotron-based nano-XRF spectrometry was used by Schöppe et al.51 to investigate the distribution of Rb in highly efficient thin-film Cu(In,Ga)Se2 solar cells. The record conversion efficiencies of such solar cells (22%) can be enhanced by processing the absorber with an alkali fluoride post-deposition treatment using heavy alkali elements such as Cs, K or Rb. The effects of the incorporated alkali metals were investigated by measuring the local distribution of Rb within these devices using very-high-resolution nano-XRF spectrometry at the Nanoanalysis Beamline ID16B of the European Synchrotron Radiation Facility in Grenoble, France. The energy of the synchrotron nanobeam was 29.06 keV and the spot size, measured using Au-knife edge scans, was 54 × 52 nm2.

Considerable efforts have been devoted to understanding the degradation that occurs during use of proton exchange membrane fuel cells (PEMFCs) employed as energy storage devices in electric vehicles. The Co cation mobility in the membrane of an operating PEMFC was monitored52 in real time using synchrotron-based sub-μm XRF spectrometry at the APS beamline 2-ID-D (250 nm beam at 8.5 keV). The Co Kα XRF maps revealed through-plane transient Co transport driven by cell potential and current density. The measurements also demonstrated that Co distributions were strongly impacted by the configuration of membrane-electrode assemblies.

An interesting combination of SR nano-XRF and XRD tomography was used by Ho et al.53 at the ESRF ID16B beamline to demonstrate the feasibility of electrodeposition for fast in situ synthesis of Rh/Mg/Al hydrotalcite-type syngas catalyst precursors with controlled composition, morphology and thickness (5–20 μm). This remarkable XRF-XRD nanotomography experiment used a 80 × 70 nm2 nanobeam with monochromatic energy (29.6 keV) and was complemented by SEM-EDX spectrometry, HR TEM and μ-Raman spectroscopy for sample pre-characterisation.

4 Grazing X-ray techniques including TXRF spectrometry

The TXRF technique is defined by the excitation beam impinging the sample carrier surface at a fixed angle below the critical angle of total reflection. In grazing X-ray techniques, the angle is usually scanned from below to above the critical angle. Overall, the focus of this year’s contributions to TXRF spectrometry was on sample preparation strategies (including pre-concentration) and calibration. Advances in instrument development led to improvements for detection of low Z elements. Several applications of GI-XRF spectrometry in combination with XRR were included54 in the Proceedings of the 17th International Conference on Total Reflection X-ray Fluorescence Analysis and Related Methods, held in 2017 in Brescia. Whereas the TXRF technique can be considered mature for the analysis of thin films such as semiconductor wafers or of low concentration aqueous samples, the analysis of samples with complex matrices continues to be an area requiring further development. Such samples include NPs and energy storage materials like electrodes and electrolytes. In this review, selected papers which develop procedures alongside theoretical considerations are included so that they may serve as guidance for other researchers. The new EU-COST initiative recognised55 the need to promote TXRF spectrometry as a sustainable tool for elemental analysis. Core work areas of this project will be instrumentation, metrology and standardisation as well as sample preparation and analytical procedures.

Currently, TXRF instrumentation can be categorised as: (a) highly specialised instrumentation available for the analysis of silicon wafers in manufacturing plants known as FABs and used complementary to other techniques such as TOF-SIMS;56 (b) commercially available bench-top instruments for analysis of a wide range of sample types; and (c) dedicated TXRF spectrometry setups for high-end applications offered at a number of synchrotron beamlines. In complete contrast to the use of large-scale SR facilities are developments in miniaturisation resulting in small low-power TXRF spectrometers. Such a low-power instrument (0.5 W), now available commercially, was used by Damdinsuren and Kawai57 to study trace elements in Kyoto snow. They obtained ppm and sub-ppm LODs for most elements. Other advances included58,59 developments in instrumentation for the determination of the low-Z elements. A simple procedure developed by Prost et al.59 used a multilayer monochromator to enhance the sensitivity of both low- and high-Z element detection simultaneously. The setup made use of a Pd/B4C multilayer reflector in combination with a 35 W rhodium target X-ray tube and a vacuum chamber. The multilayer acted as a Bragg reflector for the Rh Kα radiation as well as a low pass filter for energies below ca. 5 keV, allowing the Rh Lα radiation also to pass through the filter. The LODs (1000 s live time, 50 kV, 700 μA) determined using NIST SRM 1640 (natural water) were 138 μg kg−1 and 1 mg kg−1 for Mg and Na, respectively.

A confocal imaging TXRF instrument with an elliptical monocapillary and a polycapillary half lens, designed by Zhu et al.60 with the aim of decreasing scatter from the bulk material in the measurement of layers on semiconductors, was used to study a single-layer nickel film (30 nm) on a silicon substrate. The elliptical monocapillary provided a focal spot size of 16.5 μm at 17.4 keV with a divergence of 3.4 mrad and was used to illuminate the sample under TXRF conditions. A polycapillary half-lens (focal spot size 27 μm) was also used with the SDD at 17.4 keV. A respectable Ni LOD of ca. 0.1 mg L−1 (1000 s, 25 kV, 20 mA) was achieved using a Mo rotating anode tube. Unfortunately, it was not demonstrated how the polycapillary half-lens on the detector side had a positive effect on the figures of merits.

The combination of GI-XRF spectrometry and XRR improves the ability to distinguish between thickness and mass density of thin layers and so is an active field of research for characterisation of elemental composition and layer thickness in multilayer functional materials. Key to the performance of microelectronic devices are nanoscopic metal-containing layers, well defined in concentration and location. The development of several computer codes for modelling layer characteristics using GI-XRF spectrometry and XRR data was reported in our previous (2018) ASU.61 Subsequently, several groups published results using such codes. Maderitsch et al.62 investigated the depth distribution of S in OLEDs manufactured by two different processes. They were able to identify shortcomings in one of these manufacturing processes. The instrument setup included a commercial diffractometer and a SDD. The JGIXA software package employed for the mathematical reconstruction of the layers made use of the complementary information obtained from both XRR spectrometry and GI-XRF measurements, the first being sensitive to the electron density and the latter to the atomic density of a layer. Ultrathin (<10 nm) films of amorphous titanium telluride capped with a 5 nm tantalum passivation layer were investigated by Pessoa et al.63 Both laboratory-based equipment and the synchrotron facilities at Soleil and Elettra were used. The combined GI-XRF spectrometry and XRR approach (known as the GI-XRF/XRR approach) revealed unexpected interdiffusion between Te and the tantalum cap as confirmed by MS and XPS. The JGIXA software was applied to model the layers. The XRF beamline at Elettra and the JGIXA program were used by Nolot et al.64 to evaluate titanium nitride and nickel layers as a cost-effective alternative to noble-metal electrodes in Ta2O5 switching-material resistive RAMs. The TOF-SIMS and GI-XRF/XRR approaches gave comparable results and both were able to show the unfavourable intermixing of titanium nitride, nickel reduction and layer separation for the nickel electrode. Although TOF-SIMS was sensitive for the measurement of light elements like O, the GI-XRF/XRR approach had the advantage of being non-destructive and GI-XRF spectrometry was generally more accurate for studying material surfaces and ultra shallow layers.

Yamada et al.65 used a commercially available laboratory TXRF instrument in a GI-XRF investigation of the alloying of Au and Cu in a thin layer on a glass substrate but unfortunately the model calculations were not described in detail. The GI-XRF results were evaluated using XRD, XRF and XRR data. The GI-XRF results for layer thickness (3 nm Au, 8 nm Cu and 11 nm Au/Cu alloy layers) agreed to within 0.1 to 0.3 nm with XRR data and to within 0.1 to 1 nm with XRF data. The three techniques required different information for successful analysis. The XRR analysis required information on the composition for both the thickness and the density of the layers to be determined. The GI-XRF and XRF spectrometry techniques required density information and the latter also an FP calculation for layer thickness to be determined. These studies neatly highlighted the strengths of the different techniques as well as the need to combine both density and sensitive elemental analyses.

The direct analysis of solids by TXRF spectrometry is possible in theory as long as appropriate sample preparation can be achieved so the technique would be attractive for analyses when sample digestion is undesirable. The use of slurry sampling TXRF spectrometry avoids the low recoveries for elements which form volatile species during digestion. Fernandez-Ruiz et al.66 concluded that the digestion-free determination of Ge in organometallic materials was superior to most digestion approaches. Recoveries for Ge were increased from 0.05 to 95.2%. In order to avoid the HF digestion of refractory materials such as silicon nitride, Takahara et al.67 spin-coated Si3N4 CRM powders dispersed in a polymer solution for direct TXRF analysis of thin film polymers and quartz carriers. Unfortunately, they did not find the expected linear increase of the signal for trace impurities when using an ionic Ga IS but the recovery could be improved by normalising the net signals to the background. Use of the background intensities (the intensities under the background curve determined by a peak-stripping algorithm) improved the recoveries from 93 to 98% for Cr, 73 to 98% for Fe and 98 to 99.6% for Mn. For some samples, however, the requirement for thin films limits the applicability of digestion-free TXRF analysis. Fernandez-Ruiz et al.68 found it preferable to digest beverages rich in involatile organic compounds (e.g. sugars and sweeteners) in order to eliminate the scatter from the matrix. For example, the LOD for Cu was improved from 19 to 4 μg L−1 when digestion was used.

As already mentioned, achieving the thin film requirement is key for accurate TXRF analyses. By using a nL dispenser to produce microscopic deposits of Li-ion battery electrolytes in the determination of leached Co, Mn and Ni, Evertz et al.69 mitigated the formation of salt crystals on the dried deposits. The recovery rates were improved from 85–90% using the conventional approach to 98–105% using the new procedure. A different approach was taken by Tsuji et al.70 who prepared a resist pattern layer with alternating 10–20 μm hydrophobic and hydrophilic domains on the reflector to obtain an optimal thin film deposit of a standard solution, i.e. a film-like deposit <1 μm in thickness. Aqueous 10 ppm solutions (10 μL) of Cr, Ga, Ni, Pb and Ti, were prepared both by a conventional and the new procedure. Whereas the intensity variation for the conventional approach was 12–20%, the approach using resist pattern substrates improved this to 2–4%. Thin specimen layers are automatically produced through impaction of aerosols onto collectors. In a comprehensive study, Prost et al.71 evaluated the key steps in collecting ambient air aerosols required for TXRF spectrometry analysis. They used a Dekati impactor which allowed common quartz reflectors to be used directly as impactor stages. A mask was used to limit the aerosol deposition to the middle of the quartz carrier, thereby ensuring the sample was limited to the area visible to the detector. Self absorption was thereby reduced so increased loading could be tolerated. For example, the detected ambient air Ca concentrations increased by ca. 50 ng m−3 when the mask was used.

Analyte enrichment and/or matrix separation steps are sometimes required to limit the sample mass on the reflector. Marguí et al.72 used PVC-based membranes with functional dithizone groups to preconcentrate ionic Hg from aqueous solutions prior to TXRF spectrometry measurement. The affinity to the functionalised membranes also prevented Hg from volatilising during the sample preparation procedure. The LOD for Hg was 0.3 μg L−1 (50 W, 2000 s live time). Very impressive LODs as low as 21 ng L−1 (50 W, 1000 s) for Hg were obtained by Oskolok et al.73 using an LLE approach for extracting ionic Hg into benzene as a molecular iodine complex. A prerequisite to the success of this approach was to stay within an I concentration range of 10−4 to 10−3 mol L−1 because outside this concentration range charged HgI-complexes formed. The poorer LODs of the first approach probably stemmed from high background scatter caused by the membrane. The latter approach, however, is less attractive in that it used small volumes (50 μL) of the carcinogenic solvent benzene for extraction.

Speciation is generally required in the analysis of NPs in environmental samples and consumer products. Bahadir et al.74 extracted gold and silver NPs from aqueous samples by CPE both to conserve speciation and to preconcentrate the NPs. A so called “ligandless surfactant-assistant emulsification microextraction” was used75 by the same group to separate and determine ionic Au in aqueous solutions of gold NPs. The use of this extraction procedure allowed an LOD of 0.03 μg L−1 to be achieved and Au3+ to be quantified selectively in extracts that also contained gold NPs.

Several papers addressed the challenge posed by the determination of elements in radioactive waste matrices. Such samples are, in general, element-rich and so spectral interferences present a major problem. Accordingly, Dhara et al.76 used the tunable energy of the BL-16 beamline of the Indus2 synchrotron source at Raja Ramanna Centre for Advanced Technology to evaluate profile fitting of Rb Kα and U L series lines both above (17.57 keV) and below (16.57 keV) the U LIII absorption edge. They used this information to validate their fitting routine and then applied the routine to data obtained using a commercial TXRF instrument operated with 17.57 keV excitation. Recoveries for all approaches and most elements were 98–104%. Yoshii et al.77 used a UTEVA® resin to separate both Rb and U present in drainage waters from the damaged Fukushima Daiichi Nuclear Power plant and thereby successfully eliminated the Rb interference.

Calibration of TXRF spectrometry measurements can be achieved either through use of an IS or by using external calibration samples. A novel sub-monolayer calibration sample produced by physical vapour deposition by Hönicke et al.78 gave consistent results when characterised at three different SR beamlines using reference-free XRF and GI-XRF spectrometries at the PTB beamlines at BESSYII and μ-XRF spectrometry at P04 at DESY. It was therefore considered ready for use as a RM for investigations into surface contamination. Shulyumova et al.79 improved accuracy in the determination of elements in aqueous solution by applying a PLS fitting approach. They compared the quality of the univariate approach which comprised individual external five point calibration curves for eight elements with the multivariate five-level (concentrations) eight-factor (elements) approach. The multivariate approach was superior with recoveries ranging from 92% for Al to 102% for K whereas recoveries obtained using the univariate approach ranged from 42% for K to 180% for Hg.

The presence of spectrum background and matrix effects may require additional attention for optimisation of the internal standardisation step when using slurry-sampling for TXRF spectrometry. Pashkova et al.80 presented a comprehensive study on calibration strategies combining the use of ISs and external calibration to study sediment CRMs using slurry-sampling TXRF spectrometry. They compared the following approaches: (a) using only an IS; (b) using an IS to normalise the analyte signal and then to incorporate the normalised signal in an external calibration; and (c) using the net intensity of the Compton scatter (Mo Kα) for normalisation and an external calibration. Approaches (b) and (c) produced data that were more accurate than those produced by approach (a). The rms value of the bias for (b) and (c) was ca. 10% for most elements and highest (20–27%) for Ba, Ca, Cu and Rb. The deviations for approach (a) were higher than for the other two approaches except for Ca and Ti, for which they were similar. The highest deviations were 60, 50 and 40% for Al, Cr and Rb, respectively.

In the determination of gas phase Hg, Böttger et al.81 developed a procedure to amalgamate the gas phase Hg directly onto quartz carriers prepared with silver NPs. Calibration using acidic ISs was unsuitable because large Ag crystals formed. Use of a neutral pH Cr IS gave better results even though μ-XRF mapping showed that it dried inhomogeneously. The LOD for Hg collected passively and determined by TXRF spectrometry was 0.12 μg m−3, well below the EU workplace limit of 0.02 mg m−3.

5 Hand-held, mobile and on-line XRF techniques

Nowadays, portable spectroscopy is indispensable as an analytical technique. The maturity of the EDXRF technique and its applications was highlighted82 in a review which also considered future developments. The applicability of portable and hand-held XRF spectrometers to the analysis of a wide range of matrices was demonstrated.

In medical applications, the non-invasive character of the hand-held XRF technique is a tremendous benefit. It was demonstrated83 that skin Fe content measured with a portable XRF device could be used as a surrogate marker for organ Fe content. Rats were loaded with iron dextran and the Fe signal for skin, liver and kidney measured. A quadratic correlation was observed between liver and skin Fe signals (R2 = 0.91) and a linear correlation between kidney and skin Fe signals (R2 = 0.83). Both these correlations were confirmed by analysis using a conventional XRF spectrometer. A 1 minute exposure to the collimated beam from the 40 kV tube resulted in an average skin equivalent dose of 30 ± 10 mSv, which was below the human skin equivalent dose limit of 50 mSv. A hand-held XRF system was used84 to measure Cr in tissue phantoms and to detect Cr levels in the dermis of cadavers. The system operated at 40 kV and 100 μA. Calibration lines were developed for Kα and Kβ X-ray peaks from fiberglass resin phantoms dosed with a 1000 mg L−1 CrIII atomic standard solution. It was assumed that Cr was distributed homogeneously in skin. This configuration had a MDL of ca. 5 μg g−1 and resulted in an average equivalent dose of 25.6 mSv to ca. 1 cm2 area of the skin. However, as the XRF beam was very narrow, the skin dose delivered at the central axis of the beam was 201 mSv. Although this feasibility study seemed promising, modifications were needed to produce a less strictly collimated beam, thereby distributing the dose over a larger area of skin. Fleming et al.85 measured Zn in human nails using a portable XRF system to investigate whether Zn could be tracked spatially across the length of an intact nail. Whole nail phantoms were constructed from resin and dosed with various concentrations of Zn. A MDL of ca. 0.15 μg g−1 could be achieved by using a beam diameter of ca. 9 mm. A smaller beam diameter of 2.9 mm gave a MDL of ca. 1.1 μg g−1, very sensitive for a narrow beam. The non-invasive XRF measurements also demonstrated the capability of differentiating patterns of Zn uptake over time.

The in situ analysis of soil samples using portable XRF spectrometry is common practice even though moisture content and sample thickness can affect the XRF results. The influence of soil moisture and sample thickness on measured concentrations of Cd, Ni, Pb and Zn in a mixture of glass beads as well as Windsor loamy sand and Webster loam soils was studied86 in a well-defined experiment. Although Compton normalisation calibration was used, an inverse correlation between measured concentrations and soil moisture was observed. The greatest influence of moisture on XRF signals occurred for those elements emitting lower energy characteristic XRF lines. It was also concluded that in order to account for energy differences across a range of trace elements and matrices, portable XRF measurements should be limited to soil samples having a thickness of at least 10 mm, especially for elements such as Cd. A portable XRF spectrometry system was used87 to analyse soils in order to predict the base saturation percentage (BSP), defined as the sum of the concentrations of the elements (Ca, K, Mg and Na) which play an important role in the assessment of soil taxonomic classification and soil fertility. A total of 300 surface (0–5 cm depth) soil samples were collected, dried and disaggregated to pass a 2 mm sieve. Results were validated using four different multivariate models: generalised additive model; multiple linear regression; random forest; and regression tree. The hypothesis that the Na concentration would be a negligible factor in BSP prediction in agricultural soils proved to be correct so the non-detectability of Na when using a portable XRF spectrometry system was not a constraining factor on the use of BSP. A non-dispersive characteristic X-ray detector (CXRD) with a large sensitive area of 199 cm2 was studied88 as a candidate imaging device with high sensitivity, light weight and low-cost features for visualising environmental 137Cs deposited after the Fukushima Dai-ichi Nuclear Power Station accident. The CXRD, described in detail, could be used to visualise the spatial distribution of 137Cs by scanning the flux of 32 keV characteristic X-rays arising from the disintegration of 137Cs. The counting efficiency of the CXRD (105 cps for a 1 MBq 137Cs source at a distance of 1 m) was very high when a specific direction was used. Images of the spatial distribution of 137Cs in a contaminated forest in Fukushima Prefecture were successfully obtained. Most of the measured 137Cs was present in the forest floor and nothing was detected in the atmosphere or tree canopy.

Portable XRF spectrometry systems are now being successfully used in the compost and fertiliser industries. The concentrations of Th and U in a 100 mg sample of industrial waste generated from phosphate fertilisers and known to contain naturally-occurring radioactive material were determined89 using a portable EDXRF spectrometer. The measurements were performed using a silver anode tube (30 kV, 5 μA) with an acquisition time of 100 s. The background was reduced by introducing aluminium and tungsten filters (250 and 25 μm thick, respectively) after the X-ray tube to absorb low-energy emissions. The improved X-ray peak discrimination was necessary to quantify Th and U at trace concentrations (tens of ppm). Weindorf et al.90 used data from the analysis of 74 compost samples as a proxy for the prediction of compost salinity. Principal component regression models were built to predict the compost electrical conductivity and pH values using the elemental concentrations. Correlation between the salinity determined by electrical conductance and that predicted by portable-XRF analyses had an R2 of 0.80. The prediction of other compost parameters might also be possible using portable XRF data.

The combination of disk SPE and hand-held XRF spectrometry was developed91 for the on-site determination of As, CrVI and Se in drinking water. Initially, the elements were preconcentrated by adjusting the pH of a 50 mL sample to 4 and then the solution was passed through a Ti-loaded anion-exchange disk (Ti-AED). Both sides of the Ti-AED were coated with an adhesive cellophane tape and then dried. The Ti-AED adsorbed AsIII, AsV, CrVI, SeIV and SeVI without the need for oxidation or reduction. The LODs for As, CrVI and Se were all 1.0 μg L−1. Good recoveries of 94–109% were obtained by analysing CRMs and natural mineral water spiked with As, CrVI and Se.

The portable XRF spectrometry technique is an excellent tool for the fast screening of toxic components restricted in the EU, as described extensively in two contributions. The first described92 the use of two hand-held XRF spectrometry systems to screen for Sn on ship hulls coated with banned antifouling organotin paint. Both the thickness and composition of the organotin paint itself and the composition and paint thickness of overcoats of paint affected the measurement accuracy and led to an underestimation of the Sn concentration. Ships built after 2003, when restrictions were imposed, had concentrations of up to 68 μg cm−2, probably due to impurities of inorganic Sn in the marine paints, confirmed by chemical analysis of 21 organotin-free paints. Screening showed 10% of commercial vessels (n = 30) and 23–29% of leisure boats (n = 693) had Sn concentrations exceeding the threshold value of 100 μg cm−2. In the second contribution, Br concentrations in a variety of waste articles (soft furnishings and textiles from furniture and scrapped vehicles, WEEE plastics and insulation materials) were measured93 by non-destructive portable XRF spectrometry and subsequently selected samples were analysed by GC-MS or LC-MS-MS to confirm the presence of low concentrations of brominated flame retardants. The strengths and weaknesses of the portable XRF spectrometry technique were discussed and potential improvements presented. For XRF spectrometry to be effective for the screening of waste products, matrix effects needed to be better understood and suitable calibration standards were required.

The Planetary Instrument for X-ray Lithochemistry is an XRF instrument scheduled to be on the rover in NASA’s 2020 mission to Mars.94 Despite its inability to quantify light elements, high resolution data could be acquired by applying a methodology that took full advantage of the scattered X-ray peaks in the XRF spectra taken at short collection times. The calculations of the bremsstrahlung baseline and intensity of the scattered peak area were improved to give a more robust result. The FP model was refined to predict for any given composition the Compton/Rayleigh ratio that could be compared to an experimentally measured ratio. The methodology was validated through comparison of data for a set of seven materials with those either predicted using a published Monte Carlo model or obtained experimentally.

6 Cultural heritage applications

Chemometric processing tools for XRF spectrometry data allow a range of procedures to be undertaken, including data visualisation, exploration of hidden relations in the data, classification of samples and quantitative treatment of noisy and overlapped spectra. In a review of chemometric techniques employed in XRF spectrometry studies, Panchuk et al.95 discussed typical applications such as assessment of sample provenance or authenticity of cultural heritage samples. An overview96 of the research published in the last 20 years on medieval wall paintings using complementary analytical diagnostic techniques included the use of portable XRF instruments. This review highlighted the substantial change that has taken place in recent years in the study of wall paintings, focussing mainly on the identification of degradation processes for preservation and restoration purposes.

Use of a position-controlled easel which allowed the artwork rather than the detection system to be moved took advantage of multiplexing in which co-collection of multiple point-based imaging spectroscopy modalities was performed. This led to a significant reduction in total collection time. A 2D scanner that simultaneously collected XRF and reflectance spectra from 350 to 2500 nm across the surfaces of works of art consisted97 of a stationary XRF spectrometer and a FORS setup and a 2D position-controlled easel that moved the artwork in front of the two detection systems. A detailed description of the construction of the integrated scanning system was given. The validity of the 2D scanner was demonstrated by the XRF spectrometry scanning of a large warped panel painting by Andrea del Sarto, Charity, and by a combined XRF and reflectance scan of Georges Seurat’s painting, entitled Haymakers at Montfermeil. The XRF and reflectance spectral data were collected at 1 and 3 mm spatial samplings, respectively. Combining the results from the data sets enhanced the identification of pigments and provided yield distribution maps, despite the relatively low resolution spatial sampling. The elemental and reflectance maps allowed lead white, cobalt blue, viridian, ochres and chrome yellow to be identified and mapped. The maps also provided information on the mixing of pigments.

Confocal-XRF spectrometry is widely accepted as being a valuable tool for studies of archaeological and cultural heritage samples. Hlozek et al.98 used confocal-XRF spectrometry combined with conventional scanning XRF spectrometry and X-ray microradiography for the investigation of medieval fabrics with metal threads from Brno (Czech Republic). Confocal-XRF spectrometry was used to identify Ag, Au and Cu and provided evidence that the elements were associated with individual fibres used in the fabric. Paint layers of bohemian panel paintings originating from the 15th century, part of the collection of the National Gallery in Prague, were analysed99 by confocal μ-XRF spectrometry with depth resolutions of 46 ± 2 and 27 ± 2 μm using Ti-Kα or Pb-Lα radiation, respectively. Results provided evidence for the origin of the primary panels. Element depth analysis by confocal-XRF spectrometry was used100 successfully for the authentication of two samples of ancient Chinese coins. The depth profiles of Ca, Cu and Fe made it possible to conclude that one coin was genuine whereas the other was a reproduction. A remarkable application of synchrotron-based high-resolution confocal-XRF spectrometry imaging was employed101 to visualise Pb distributions within archaeological bone and tooth microstructures at the μm scale. Previous analyses of bone, hair and soft tissue samples from the crew of the Franklin expedition launched in 1845 found that crewmembers’ tissues contained elevated Pb concentrations, suggesting that Pb poisoning may have contributed to their death. However, the skeletal microstructural Pb-distribution data did not support the assumption that Pb played a pivotal role in the loss of Franklin and his crew.

The ability of macro-XRF scanning to visualise the distribution of elements detected at and below paint surfaces makes the technique particularly useful for studying painting techniques and for revealing materials that remain hidden below the paint surface. A system equipped with a 10 W rhodium anode tube (45 kV, 200 μA) and an SDD (50 mm2 active area) was used102 to study Rubens’ painting practices and to identify the materials he used. The macro-XRF imaging procedure performed on the Portrait of Hélène Fourment (map size 460 × 470 mm2, step size 750 μm, 200 ms per pixel) provided full access to the animated background behind the sitter. For Venus Frigida (map size 510 × 490 mm2, step size 750 μm, 200 ms per pixel), the visualisation of various technical differences between the centre piece and subsequent additions provided evidence that the additions were made outside Rubens’ studio. The separation of two painting campaigns in Saul and David, attributed to Rembrandt, was studied103 using macroscopic chemical imaging based on reflectance and XRF imaging spectroscopy and microscopic analysis. For this purpose, a macro-XRF scanner with a 50 W molybdenum target X-ray tube (50 kV, 1 mA), a fixed polycapillary lens and four ED X-ray detectors was used to scan the painting at a step size of 1 mm and an integration time of 0.2 s per pixel. The integration time was increased up to 1.9 s per pixel for areas of enhanced interest. The mapping revealed that whereas the orange-red colour of David’s garment and the Greek key design in Saul’s turban were painted with predominately red ochre mixed with vermilion, the orange-red slashing strokes in the interior of Saul’s cloak, associated with the second painting stage, were painted with predominately red ochre without vermilion. The last missing quarter of La pose enchantéé, a 1927 Magritte oil painting which had disappeared in 1932, was discovered104 beneath Dieu n’est pas un saint, a picture painted by the Belgian surrealist between 1935 and 1936. The pigments used for both the visible and the hidden composition were characterised both through macro-XRF analysis of the whole picture (achieved in 35 h) and Raman measurements on selected points. A virtual colorisation of La pose enchantée was based on evidence collected from the top right part lying beneath Dieu n’est pas un saint. The Virgin with the Child, a wood panel painted by de Saliba in 1497 and on view at the Castello Ursino Museum in Catania (Italy), was investigated105 in situ by the use of a macro-XRF spectrometry fast scanner equipped with a 30 W rhodium anode tube, polycapillary focussing optics with a focal distance of 1 cm and a beam size at the focus of 25 μm diameter (at Rh K-lines) and an SDD (50 mm2 active area). Measurements were performed with a step size of 50 to 500 μm in the scanning macro-XRF spectrometry mode over a maximum area of 110 × 70 cm2 and a dwell time of 20 ms per step. The real-time imaging of the chemical elements allowed the pigments employed both in the original painting and in the restoration to be characterised. There was also evidence of restorations at different periods of time. The same real-time macro-XRF spectrometry scanner was used106 in an attempt to authenticate a painting of a bearded man, on display at the Eremitani Museum in Padua, attributed to Jacopo Tintoretto but possibly the lost portrait of Galileo Galilei created by the Tuscan master Santi di Tito in 1602. The results of the macro-XRF elemental distribution did not discriminate between the two painters but the colour of the eyes had been changed from the light blue of Galileo’s eyes seen in other portraits to the current brown. Moreover, the study demonstrated that the sitter had reddish hair and wore a coat that could be a gown. The analysis also revealed an anomalous concentration of Hg (vermilion pigment) under the sitter’s left eye where Galileo had a characteristic nevus. This feature was in the copy of Santi di Tito’s painting engraved by Giuseppe Calendi at the end of the 18th century, and thus consistent with evidence supporting the identity of the sitter as Galileo.

The in situ use of macro-XRF spectrometry scanning on the vault of the Loggia of Cupid and Psyche, frescoed by Raphael and his workshop in the Villa Farnesina (Rome), demonstrated107 the potential of this technique for in situ studies of wall paintings. Care was needed both because the wide non-planar walls dictated continuous setup adjustments and because specific features related to the constituent materials of walls and fresco paintings presented a challenge. Previous knowledge of the surface composition through extensive single-point XRF analysis was important for planning the mapping, demonstrating the great interplay between the single-spot and imaging modalities. A multi-disciplinary study of wall paintings preserved in the Saint Stephen Church located in the Valderejo Natural Park (Álava, Spain) involved108 portable Raman and XRF spectrometric analyses supported by additional laboratory analysis. The XRF measurements (50 s accumulation time) were performed with a commercial hand-held system equipped with a rhodium target X-ray tube and a high resolution SDD. The in situ analyses provided a comprehensive evaluation of the original pigments used by the artists and also led to identification of an area of interest for which targeted sampling was performed for laboratory analysis. Despite the challenges in the study of heterogeneous and multilayered matrices, the multidisciplinary and non-invasive study of the wall paintings at the Domus of Octavius Quartio in Pompeii allowed109 pigments and painting techniques to be identified. The composition of the pigments was consistent with those largely found in Pompeii during the 1st century AD for the decoration of wall paintings.

A set of complementary analytical methods outlined110 a complex picture of the painting techniques and materials used in the wooden panel paintings of the altar of St. James (Levoca, Eastern Slovakia), thus providing essential information needed for professional restoration. A hand-held XRF spectrometer, equipped with a 45 kV X-ray tube and an SDD, was used to select sites suitable for taking samples <2 mm in size to reveal the stratigraphy of the colour paintings. A depth-resolved analysis of aged multilayered model samples of easel paintings used111 a combination of LIBS and XRF spectrometry (2 mm diameter measuring spot, 60 s counting time). The results of the two techniques provided essential complementary information on the elemental composition of the multilayered samples. The XRF signal was affected by layer thickness and absorption by particular layers and the presence of heavy elements could attenuate the signal. In addition, the greater penetration of X-ray radiation through organic material could result in amplification of the signal.

The non-invasive nature of the XRF technique is valuable for the study of manuscript fragments. Portable microphotography, XRF spectrometry and UV-VIS-NIR FORS were used112 in an in situ investigation of two Tibetan manuscripts from the Asian Collection of the Museum of Natural History in Florence. A commercially available portable XRF spectrometer (3 mm diameter spot size) was used. The total analysis time was set at 120 s, divided into 4 steps of 30 s each in which operating conditions (kV, μA and beam filter) were adjusted in order to optimise the instrumental response to the four different energy ranges. The elemental compositions of the inks and pigments were consistent with those of materials in use in the period when the manuscripts were thought to be written. The strength of the combined use of macro-XRF spectrometry with macroscopic reflection mode FTIR spectrometry as complementary techniques was demonstrated113 in a non-invasive study of a 15th century Florentine illuminated manuscript fragment. Although macro-XRF measurements provided the distributions of the different painters’ materials with sufficient lateral detail, they were not specific enough to identify unambiguously all materials present. Both XRF spectrometry measurements (mapping and point analysis) and visible hyperspectral reflectance imaging were used114 in a study of a precious 15th century illuminated manuscript of Petrarch’s work, De remediis utriusque fortunae, held in the Méjanes library in Aix-en-Provence (France). An XRF instrument (1.2 mm beam size, 1 cm typical working distance) built in-house was used for single-point analysis with an acquisition time of 300 s. For XRF imaging, the measurement head was mounted on a motorised xy stage with 20 cm travel range in both directions. Pigments and dyes were investigated with particular emphasis placed on the superimposed colours to provide a better understanding of the artist’s technique. A partly hidden coat of arms was revealed, supporting the hypothesis that this manuscript was decorated at the workshop of François Le Barbier.

Reducing the analytical time and increasing the sample throughput for the analysis of a large numbers of coins was achieved115 by using a tuneable synchrotron X-ray source. The combination of high intensity and spatial resolution provided by a SR source with the sensitivity afforded by a high resolution WD spectrometer was evaluated for the rapid, quantitative and non-destructive XRF mapping of trace Pt in ancient Roman gold coins. The rapid mapping of more than 3300 data points in 400 × 400 μm2 areas took <20 minutes with each data point collected in 300 ms. Quantitative analysis was performed by using gold RMs with known Pt concentrations. The Pt concentrations determined in this study agreed within −11 to +3% with those determined previously in the same gold coins. The small spot size available from the SR source made it possible to determine Pt concentrations on imprinted surfaces so the analysis could be considered non-destructive. A set of Venetian sesino coins minted between 1554 and 1605 were investigated116 in order to shed light on some aspects of the so-called mistura alloy. The XRF spectrometer was equipped with a molybdenum target X-ray source operating at 40 kV, 30 mA, a parabolic multilayer monochromator and an SSD with an active area of 50 mm2. The XRF spectrometry results together with XRD data showed that the mistura alloy was composed of only copper rather than a Cu–Ag two-phase alloy as previously thought. The performance of an EDXRF spectrometer, built in-house and equipped with a transmission-type compact X-ray tube with silver anode (50 kV, 30 μA) and an SDD, was validated117 through the analysis of silver–copper alloys. The element contents were determined using three different approaches: a FP method; a calibration method in which the ratio of Ag peak area to Cu peak area was plotted against the ratio of Ag concentration to Cu concentration; and the Casting approximation. The elemental compositions of two silver–copper Polish coins from 19th and early 20th centuries were examined by using all three calculation methods. Comparable results were achieved resulting in a Ag[thin space (1/6-em)]:[thin space (1/6-em)]Cu concentration ratio of 95[thin space (1/6-em)]:[thin space (1/6-em)]5 for 15 kopek and 1 złoty coins and 88[thin space (1/6-em)]:[thin space (1/6-em)]12 for a 2 złote coin. The MDLs, determined using RMs, were 110 and 30 mg kg−1 for Ag and Cu, respectively. The XRF technique is not restricted to analysis of ancient coins but has also been used to study modern coins, as demonstrated118 by analysis of a series of coins minted in Peru from 1950 to 1965. These coins were expected to be composed of zinc and copper (95 + 5) but in fact the Cu content changed from year to year and was usually less than the legally acceptable limit (3%). The results for 313 coins showed a debasement over time with two minimums which corresponded to adverse economic events.

An example of the use of XRF spectrometry to study copper-based artefacts was the analysis119 of Sn-rich soldering in 10 handle attachments of Roman situlae from Conimbriga (Portugal) using μ-EDXRF spectrometry, SEM-EDX microanalysis and optical microscopy. The solders were composed of Cu–Sn alloys with Sn contents of 30–60%. An enrichment of the outer layers of the filler with Pb from the leaded copper substrate was observed in some of the artefacts. The thinness of the filler presented an analytical problem in that the EDXRF spectrometry results could be influenced not only by the composition of the substrate but also by exchange of chemical elements between the solder and the substrate. The challenges posed by surface variations to portable XRF spectrometry analysis were assessed120 by the analysis of both the original corroded surface and of the subsequently cleaned surface of a group (n = 187) of Roman brooch fragments from Nijmegen (The Netherlands). Although systematic compositional differences were found for the major elements (Pb, Sn, Zn), the compositional ratios remained within a satisfactory tolerance and so could be used for simple alloy classification. The suitability of XRF-based methods for a non-invasive assessment of the coating thickness on ancient silver artefacts was investigated.121 Measurements (2.5 mm spot size) were carried out on 4 mock-up samples made by assembling several Mylar sheets on a silver substrate and on 10 silver plates treated with organic polymers used in conservation. Of three quantification approaches tested (empirical and theoretical calibration curves and FP method), the empirical approach proved to be the most accurate but its application was limited by the lack of suitable calibration standards. Therefore, there is a requirement for the preparation of stand-alone films to be used for calibration. The uniquely high Sr concentration of the white marble artefacts of Göktepe was used122 as an indicator in an efficient and non-destructive analysis. The commercially available portable XRF analyser had a measuring spot of approximately 4 × 7 mm2 in size. The spectra were collected at 40 kV and 12 μA and with a count time of 180 s. Other potential provenance indicators such as Fe and Mn were determined after empirical calibration of the instrument by using 17 quarry samples of known composition. It was almost always possible to discriminate between Göktepe and other samples so additional analyses were required only when the Sr value was at the lower edge of the concentration range (ca. 200 mg kg−1).

Although the XRF technique is generally considered non-destructive, some samples may require a destructive sample preparation step to obtain the best results. A total of 41 pottery shards originating in the Jomon period (14[thin space (1/6-em)]000–300 BC) and Yayoi period (300 BC–250 AD) and excavated from the Shimotakabora site on Oshima Island of the Izu islands (Tokyo, Japan) were analysed123 by WDXRF spectrometry using glass beads with a 1[thin space (1/6-em)]:[thin space (1/6-em)]10 sample-to-flux ratio. The calibration curves were constructed using synthetic standards with a chemical composition similar to that of ancient Japanese pottery. The pottery provenance was established by multivariate statistics (PCA and cluster analysis) on the chemical compositions. The provenance assignment indicated that 37 of the 41 pottery shards were brought to Oshima island from Japan’s main island, Honshu, in the prehistoric age. Fused bead samples in a 1[thin space (1/6-em)]:[thin space (1/6-em)]20 sample-to-flux ratio were prepared124 from Late Roman Pottery from a rural site on the island of Eivissa (Balearic Islands, Spain). The ceramic samples included common wares, amphorae and cooking wares and were analysed by WDXRF spectrometry for chemical characterisation, by thin-section optical microscopy analysis for mineralogical and petrographic characterisation and by XRD analysis for mineralogical characterisation. Whereas common wares and amphorae were produced using locally sourced materials, the cooking wares were made from imported materials.

As part of an archaeological study, the investigation of remnants of antique polychromy on the surface of the frieze of the Siphnian Treasury (Cyclades, Greece) used125 mobile hyperspectral reflectance imaging in the visible and NIR ranges and scanning macro-XRF spectrometry imaging. A macro-XRF spectrometry instrument built in-house was used to perform more than 62 macro-XRF spectrometry scans of various sizes and parameters and to collect 100 spot analyses. Previously unknown traces of ancient paint were revealed, illustrating the potential of combining both techniques to obtain new insights in well-described and investigated objects. For example, the data showed that Pb-containing pigments were used to paint pictorial details but were not used in the earth-based underlayers. A challenging task in imaging spectroscopy is data treatment in order to maximise the amount of information produced. A novel approach to the joint evaluation of XRF and reflectance imaging spectroscopy data by vertical data fusion and t-distributed stochastic neighbour embedding (t-SNE) was presented126 for data acquired in a Ramesside tomb (13th century BC) of the Theban Necropolis in Egypt. High-dimensional hyperspectral data were converted into an easily legible 2D representation using a t-SNE module. The t-SNE representation highlighted clearly the presence of sub-surface layers without needing manual comparison to an aligned photograph. Evaluation of data produced by portable XRF spectrometry measurements made127 it possible to identify the stratified structure of an investigated object and to determine the approximate concentrations of elements and their mean depth. The Kα/Kβ intensity ratio diagrams for Cu, Fe, Ni and Ti, drawn by means of combination of measurements and Monte Carlo simulations, were then applied to the determination of approximate structures of several objects. The Kα/Kβ intensity ratios, which were essential for the correct interpretation of the structure, could be determined with an uncertainty sufficient for depth profiling. However, the fluctuations of Kα count rates made quantification of the individual measurements difficult.

Portable XRF spectrometry was used to determine elemental composition in a wide range of applications. An investigation on the Etruscan lituus (a musical instrument), the axe and the shield from Pian di Civita (Tarquinia, Italy) took128 advantage of the non-invasive nature of portable XRF spectrometry, video-microscopy and radiography. Characterisation of the Cu–Sn alloys used to make the objects was crucial in identifying the relationship between the three objects and to understand the process used to manufacture the lituus. The XRF system had a gold target tube operating at 50 kV and 300 μA. Each 2 mm measured point was analysed with an acquisition time of 60 s. A comparative investigation of two icons (17–18th and 19th centuries), representative of the Russian Lipovan cultural communities, used129 a multi-analytical approach. Imaging techniques were used to identify areas requiring more detailed analysis by FTIR spectroscopy (molecular) and XRF spectrometry (elemental). The sculpture of the Red Jaguar Throne, located inside the pyramid of Kukulkan at Chichen Itza (Mexico), was studied130 using a non-invasive portable XRF spectrometry technique to identify the chemical composition. The red pigment that covered the sculpture surface consisted of a combination of hematite and cinnabar, the 77 incrustations of green stones were jadeite minerals and the four fangs were manufactured from a marine gastropod (Lobatus costatus). A preliminary study used131 a portable XRF spectrometer and a hand-held Raman spectrometer to perform the first on-site elemental analyses of glazes and colouring agents on Iznik tiles at Edirne mosques (15th and 16th centuries). The objective was to understand the technology of Ottoman tile revetments used in architectural buildings in Edirne. About 40 tiles were analysed. The XRF spectrometry results were normalised to Si concentrations in order to eliminate the variation between different positions on the tiles. Bismuth concentrations and Sn/Pb, Co/Mn, and Co/Ni concentration ratios proved to be very useful for comparing the different glazes and to identify the sources of cobalt minerals used to prepare the glazes. A non-destructive analytical approach based on EDXRF and Raman spectrometries was conducted132 in an attempt to resolve the issue of the introduction of overglaze enamelling in Japan. The investigation focussed specifically on the overglaze yellow enamel and the underglaze blue pigment of a polychrome mukozuke (1624–1644) porcelain dish. The results confirmed that Sb was used for the first time as the colouring agent for yellow-enamelled porcelains when Jesuit missionaries first arrived in Japan and then in China. The analytical evidence was crucial for identifying the first use of Naples Yellow in Japan and for resolving the issue of the origin of overglaze enamelling, thereby providing the missing step that actually led to the first development of the technique in Arita in the 1630s.

Natural and synthetic arsenic sulfide pigments used in Japanese woodblock prints of the late Edo period (1615–1868) and early Meiji period were investigated.133 Two sets (originals and copies) of a series of eight prints, entitled A Tour of the Waterfalls in Various Provinces (Shokoku Taki Meguri) and designed by Katsushika Hokusai, were analysed with particular attention given to the yellow, orange and green printed areas. A multi-analytical approach that included XRF spectrometry revealed the use of natural orpiment in the original set and of artificial arsenic sulfide and ultramarine blue pigments in the reproduction set. The results of the comparative analysis highlighted differences in pigment use between Edo and Meiji periods, and identified arsenic sulfide pigments as useful markers for the date of original production for popular prints of the Edo period. In a non-invasive and non-destructive study of the colour prints from 16th century Northern European chiaroscuro woodcuts, the chemical composition of the inks and papers was determined134 and the sequence of printed layers defined in order to understand how the artists and their workshops achieved visual effects. Imaging techniques provided microscopic and macroscopic observations of the colour prints. The XRF spectrometry analysis detected most chemical elements present in the paper support and in the inks, so it was possible to characterise most of the compounds used to prepare the inks.

Readers seeking additional information on cultural heritage applications are referred to our companion ASU review on advances in the analysis of metals, chemicals and functional materials.3

Conflicts of interest

There are no conflicts to declare.

Abbreviations

2Dtwo dimensional
3Dthree dimensional
ADanno domini
AEDanion-exchange disk
ASUAtomic Spectrometry Update
BCbefore Christ
BNNbimetallic-nanoporous-network
BSPbase saturation percentage
CKCoster–Kronig
COSTCooperation in Science and Technology
CPEcloud point extraction
CRMcertified reference material
CTcomputed tomography
CXRDcharacteristic X-ray detector
EDenergy dispersive
EDXenergy dispersive X-ray
EDXRFenergy dispersive X-ray fluorescence
ESRFEuropean Synchrotron Radiation Facility
EUEuropean Union
EXAFSextended X-ray absorption fine structure
FORSfibre optic reflectance spectroscopy
FPfundamental parameter
FTIRFourier transform infrared
FWHMfull width at half maximum
GC-MSgas chromatography mass spectrometry
GENFIREgeneralised Fourier iterative reconstruction
GI-XRFgrazing incidence X-ray fluorescence
HRhigh resolution
IAEAInternational Atomic Energy Agency
ISinternal standard
LC-MS-MSliquid chromatography mass spectrometry mass spectrometry
LIBSlaser induced breakdown spectroscopy
LLEliquid–liquid extraction
LODlimit of detection
MDLmethod detection limit
MSmass spectrometry
NASANational Aeronautics and Space Administration
NIRnear infrared
NISTNational Institute of Standards and Technology
NPnanoparticle
NSLSNational Synchrotron Light Source
OLEDorganic light emitting diode
PCAprincipal component analysis
PEMFCproton exchange membrane fuel cells
PLSpartial least squares
PMMApolymethylmethacrylate
pptparts per trillion (109)
PTBPhysikalisch-Technische Bundesanstalt
PVCpoly(vinyl chloride)
QEDquantum electrodynamics
RAMrandom-access memory
RMreference material
rmsroot mean square
RXRRainbow X-ray
SDDsilicon drift detector
SEMscanning electron microscopy
SIMSsecondary ion mass spectrometry
SNEstochastic neighbour embedding
SOLEILSource optimisée de lumière d’énergie intermédiaire du LURE
SORSspatially offset Raman spectroscopy
SPEsolid phase extraction
SRsynchrotron radiation
SRMstandard reference material
SSRLStanford synchrotron radiation lightsource
STXMscanning transmission X-ray microspectroscopy
TEMtransmission electron microscopy
TOFtime-of-flight
TXRFtotal reflection X-ray fluorescence
UV-VISultraviolet-visible
WDwavelength dispersive
WDXRFwavelength dispersive X-ray fluorescence
WEEEwaste electrical and electronic equipment
XANESX-ray absorption near edge structure
XASX-ray absorption spectroscopy
XFHX-ray fluorescence holography
XPSX-ray photoelectron spectroscopy
XRDX-ray diffraction
XRFX-ray fluorescence
XRRX-ray reflectometry
Zatomic number

References

  1. J. R. Bacon, O. T. Butler, W. R. L. Cairns, J. M. Cook, R. Mertz-Kraus and J. F. Tyson, J. Anal. At. Spectrom., 2019, 34(1), 9–58 RSC.
  2. A. Taylor, N. Barlow, M. P. Day, S. Hill, N. Martin and M. Patriarca, J. Anal. At. Spectrom., 2019, 34(3), 426–459 RSC.
  3. S. Carter, R. Clough, A. Fisher, B. Gibson, B. Russell and J. Waack, J. Anal. At. Spectrom., 2018, 33(11), 1802–1848 RSC.
  4. R. Clough, C. F. Harrington, S. J. Hill, Y. Madrid and J. F. Tyson, J. Anal. At. Spectrom., 2018, 33(7), 1103–1149 RSC.
  5. T. W. Victor, L. M. Easthon, M. Ge, K. H. O’Toole, R. J. Smith, X. Huang, H. Yan, K. N. Allen, Y. S. Chu and L. M. Miller, Sci. Rep., 2018, 8, 13415,  DOI:10.1038/s41598-018-31461-y.
  6. J. J. Deng, Y. H. Lo, M. Gallagher-Jones, S. Chen, A. Pryor, Q. L. Jin, Y. P. Hong, Y. S. G. Nashed, S. Vogt, J. W. Miao and C. Jacobsen, Sci. Adv., 2018, 4(11) DOI:10.1126/sciadv.aau4548.
  7. S. Nijem, S. Dery, M. Carmiel, G. Horesh, J. Garrevoet, K. Spiers, G. Falkenberg, C. Marini and E. Gross, J. Phys. Chem. C, 2018, 122(43), 24801–24808 CrossRef CAS.
  8. C. A. S. Dunning and M. Bazalova-Carter, Phys. Med. Biol., 2018, 63(23) DOI:10.1088/1361-6560/aaece9.
  9. L. Z. Deng, B. Wei, P. He, Y. Zhang and P. Feng, Int. J. Nanomed., 2018, 13, 7207–7216 CrossRef CAS.
  10. M. F. Ahmed, S. Yasar and S. H. Cho, IEEE Trans. Med. Imaging, 2018, 37(11), 2483–2492 Search PubMed.
  11. J. C. Larsson, C. Vogt, W. Vagberg, M. S. Toprak, J. Dzieran, M. Arsenian-Henriksson and H. M. Hertz, Phys. Med. Biol., 2018, 63(16) DOI:10.1088/1361-6560/aad51e.
  12. D. Hampai, Y. M. Cherepennikov, A. Liedl, G. Cappuccio, E. Capitolo, M. Iannarelli, C. Azzutti, Y. P. Gladkikh, A. Marcelli and S. B. Dabagov, J. Instrum., 2018, 13 DOI:10.1088/1748-0221/13/04/C04024.
  13. Y. M. Cherepennikov, D. Hampai, C. Azzutti, A. A. Krasnykh, I. A. Miloichikova, S. G. Stuchebrov, A. V. Batranin and S. B. Dabagov, J. Instrum., 2018, 13 DOI:10.1088/1748-0221/13/07/C07003.
  14. C. Conti, A. Botteon, C. Colombo, M. Realini, P. Matousek, P. Vandenabeele, B. Laforce, B. Vekemans and L. Vincze, Anal. Methods, 2018, 10(31), 3837–3844 RSC.
  15. E. S. Rodrigues, M. H. F. Gomes, N. M. Duran, J. G. B. Cassanji, T. N. M. da Cruz, A. S. Neto, S. M. Savassa, E. de Almeida and H. W. P. Carvalho, Front. Plant Sci., 2018, 9 DOI:10.3389/fpls.2018.01588.
  16. U. E. A. Fittschen, H.-H. Kunz, R. Höhner and A. Fittschen, X-Ray Spectrom., 2017, 46(5), 374–381 CrossRef CAS.
  17. Z. M. Duan, J. Liu, Q. L. Jiang, Q. L. Pan and L. Cheng, Nucl. Instrum. Methods Phys. Res., Sect. B, 2019, 442, 13–18 CrossRef.
  18. H. Ida and J. Kawai, X-Ray Spectrom., 2005, 34, 225–229 CrossRef CAS.
  19. M. Wilke, K. Harnisch, W. Knapp, M. Ecke and T. Halle, J. Vac. Sci. Technol., B: Nanotechnol. Microelectron.: Mater., Process., Meas., Phenom., 2019, 37(1), 011203,  DOI:10.1116/1.5067322.
  20. L. Veith, D. Dietrich, A. Vennemann, D. Breitenstein, C. Engelhard, U. Karst, M. Sperling, M. Wiemann and B. Hagenhoff, J. Anal. At. Spectrom., 2018, 33(3), 491–501 RSC.
  21. S. Diaz-Moreno, M. Amboage, M. Basham, R. Boada, N. E. Bricknell, G. Cibin, T. M. Cobb, J. Filik, A. Freeman, K. Geraki, D. Gianolio, S. Hayama, K. Ignatyev, L. Keenan, I. Mikulska, J. F. W. Mosselmans, J. J. Mudd and S. A. Parry, J. Synchrotron Radiat., 2018, 25, 998–1009 CrossRef.
  22. N. P. Edwards, S. M. Webb, C. M. Krest, D. van Campen, P. L. Manning, R. A. Wogelius and U. Bergmann, J. Synchrotron Radiat., 2018, 25, 1565–1573 CrossRef CAS.
  23. E. Marguí, M. Hidalgo, A. Migliori, J. J. Leani, I. Queralt, N. Kallithrakas-Kontos, C. Streli, J. Prost and A. G. Karydas, Spectrochim. Acta, Part B, 2018, 145, 8–19 CrossRef.
  24. M. Rauwolf, A. Turyanskaya, D. Ingerle, N. Szoboszlai, I. Pape, A. W. Malandain, O. J. L. Fox, L. Hahn, K. J. S. Sawhney and C. Streli, J. Synchrotron Radiat., 2018, 25, 1189–1195 CrossRef CAS.
  25. T. Nisius, K. Andrianov, A. Haidl, B. Kanngiesser and T. Wilhein, J. Instrum., 2018, 13 DOI:10.1088/1748-0221/13/07/C07004.
  26. K. Andrianov, A. Haidl, L. Luhl, A. Dehlinger, H. Dierks, R. Gnewkow, T. Nisius, B. Kanngiesser and T. Wilhein, J. Instrum., 2018, 13 DOI:10.1088/1748-0221/13/05/C05013.
  27. U. Boesenberg, C. G. Ryan, R. Kirkham, A. Jahn, A. Madsen, G. Moorhead, G. Falkenberg and J. Garrevoet, J. Synchrotron Radiat., 2018, 25, 892–898 CrossRef CAS.
  28. A. A. Guda, A. L. Bugaev, R. Kopelent, L. Braglia, A. V. Soldatov, M. Nachtegaal, O. V. Safonova and G. Smolentsev, J. Synchrotron Radiat., 2018, 25, 989–997 CrossRef CAS PubMed.
  29. K. Hayashi and P. Korecki, J. Phys. Soc. Jpn., 2018, 87(6) DOI:10.7566/JPSJ.87.061003.
  30. G. Bortel, G. Faigel, M. Tegze and B. Angelov, J. Synchrotron Radiat., 2019, 26, 170–174 CrossRef CAS.
  31. A. K. R. Ang, T. Matsushita, Y. Hashimoto, N. Happo, Y. Yamamoto, M. Mizuguchi, A. Sato-Tomita, N. Shibayama, Y. C. Sasaki, K. Kimura, M. Taguchi, H. Daimon and K. Hayashi, Phys. Status Solidi B, 2018, 255(11) DOI:10.1002/pssb.201800100.
  32. M. Guerra, J. M. Sampaio, F. Parente, P. Indelicato, P. Honicke, M. Muller, B. Beckhoff, J. P. Marques and J. P. Santos, Phys. Rev. A: At., Mol., Opt. Phys., 2018, 97(4) DOI:10.1103/PhysRevA.97.042501.
  33. Y. Ménesguen, M. C. Lepy, J. M. Sampaio, J. P. Marques, F. Parente, M. Guerra, P. Indelicato and J. P. Santos, Metrologia, 2018, 55(5), 621–630 CrossRef.
  34. G. B. Hiremath, S. Mirji, M. M. Hosamani, N. M. Badiger and M. K. Tiwari, Chem. Phys. Lett., 2019, 715, 317–322 CrossRef CAS.
  35. R. Kaur, A. Kumar, M. Czyzycki, A. Migliori, A. G. Karydas and S. Puri, X-Ray Spectrom., 2019, 48(2), 129–140 CrossRef.
  36. A. Carmona, C. E. Zogzas, S. Roudeau, F. Porcaro, J. Garrevoet, K. M. Spiers, M. Salome, P. Cloetens, S. Mukhopadhyay and R. Ortega, ACS Chem. Neurosci., 2019, 10(1), 599–609 CrossRef CAS.
  37. M. J. Pushie, M. E. Kelly and M. J. Hackett, Analyst, 2018, 143(16), 3761–3774 RSC.
  38. M. J. Pushie, A. M. Crawford, N. J. Sylvain, H. S. Hou, M. J. Hackett, G. N. George and M. E. Kelly, ACS Chem. Neurosci., 2018, 9(5), 886–893 CrossRef CAS.
  39. J. L. Wedding, B. Lai, S. Vogt and H. H. Harris, Biochim. Biophys. Acta, 2018, 1862(11), 2393–2404 CrossRef CAS.
  40. C. Sanchez-Cano, I. Romero-Canelon, K. Geraki and P. J. Sadler, J. Inorg. Biochem., 2018, 185, 26–29 CrossRef CAS.
  41. F. Chen, J. Hu, Y. Takahashi, M. Yamada, M. S. Rahman and G. S. Yang, J. Environ. Radioact., 2019, 196, 29–39 CrossRef CAS PubMed.
  42. H. H. Du, Q. Y. Huang, C. L. Peacock, B. Q. Tie, M. Lei, X. L. Liu and X. D. Wei, Environ. Pollut., 2018, 243, 444–452 CrossRef CAS.
  43. M. F. Mera, M. Rubio, C. A. Perez, S. Cazon, M. Merlo and S. E. Munoz, Radiat. Phys. Chem., 2019, 154, 69–73 CrossRef CAS.
  44. B. D. Chen, K. Nayuki, Y. Kuga, X. Zhang, S. L. Wu and R. Ohtomo, Microbes Environ., 2018, 33(3), 257–263 CrossRef.
  45. G. Vigani, S. Bohic, F. Faoro, B. Vekemans, L. Vincze and R. Terzano, Front. Plant Sci., 2018, 9 DOI:10.3389/fpls.2018.01112.
  46. M. G. Siebecker, R. L. Chaney and D. L. Sparks, Geochem. Trans., 2018, 19(14) DOI:10.1186/s12932-018-0059-2.
  47. C. M. Rico, M. G. Johnson and M. A. Marcus, Environ. Sci.: Nano, 2018, 5(8), 1807–1812 RSC.
  48. A. D. Servin, H. Castillo-Michel, J. A. Hernandez-Viezcas, W. De Nolf, R. De La Torre-Roche, L. Pagano, J. Pignatello, M. Uchimiya, J. Gardea-Torresdey and J. C. White, J. Agric. Food Chem., 2018, 66(26), 6609–6618 CrossRef CAS.
  49. J. P. Correa-Baena, Y. Q. Luo, T. M. Brenner, J. Snaider, S. J. Sun, X. Y. Li, M. A. Jensen, N. T. P. Hartono, L. Nienhaus, S. Wieghold, J. R. Poindexter, S. Wang, Y. S. Meng, T. Wang, B. Lai, M. V. Holt, Z. H. Cai, M. G. Bawendi, L. B. Huang, T. Buonassisi and D. P. Fenning, Science, 2019, 363(6427), 627–631 CrossRef CAS.
  50. Y. Q. Luo, S. Aharon, M. Stuckelberger, E. Magana, B. Lai, M. I. Bertoni, L. Etgar and D. P. Fenning, Adv. Funct. Mater., 2018, 28(18), 1706995,  DOI:10.1002/adfm.201706995.
  51. P. Schöppe, S. Schönherr, P. Jackson, R. Wuerz, W. Wisniewski, M. Ritzer, M. Zapf, A. Johannes, C. S. Schnohr and C. Ronning, ACS Appl. Mater. Interfaces, 2018, 10(47), 40592–40598 CrossRef.
  52. Y. Cai, J. M. Ziegelbauer, A. M. Baker, W. B. Gu, R. S. Kukreja, A. Kongkanand, M. F. Mathias, R. Mukundan and R. L. Borup, J. Electrochem. Soc., 2018, 165(6), F3132–F3138 CrossRef CAS.
  53. P. H. Ho, W. de Nolf, F. Ospitali, A. Gondolini, G. Fornasari, E. Scavetta, D. Tonelli, A. Vaccari and P. Benito, Appl. Catal., A, 2018, 560, 12–20 CrossRef CAS.
  54. Spectrochim. Acta, Part B, 2018, 145 (July) Search PubMed.
  55. CA18130 – European Network for Chemical Elemental Analysis by Total Reflection X-Ray Fluorescence, https://www.cost.eu/actions/CA18130 Search PubMed.
  56. M. L. Polignano, G. Borionetti, A. Galbiati, S. Grasso, I. Mica and A. Nutsch, Spectrochim. Acta, Part B, 2018, 149, 313–321 CrossRef CAS.
  57. B. Damdinsuren and J. Kawai, X-Ray Spectrom., 2018, 47(4), 273–276 CrossRef CAS.
  58. K. Sanyal and N. L. Misra, J. Anal. At. Spectrom., 2018, 33(5), 876–882 RSC.
  59. J. Prost, P. Wobrauschek and C. Streli, Rev. Sci. Instrum., 2018, 89(9), 093108,  DOI:10.1063/1.5044527.
  60. Y. Zhu, Y. B. Wang, T. X. Sun, X. P. Sun, X. Y. Zhang, Z. G. Liu, Y. F. Li and F. S. Zhang, Appl. Radiat. Isot., 2018, 137, 172–176 CrossRef CAS.
  61. C. Vanhoof, J. R. Bacon, A. T. Ellis, L. Vincze and P. Wobrauschek, J. Anal. At. Spectrom., 2018, 33(9), 1413–1431 RSC.
  62. A. Maderitsch, D. Ingerle, T. Bretschneider, M. Rauwolf, C. Pflumm, H. Buchholz, H. Borchert, C. Streli and J. Parisi, Spectrochim. Acta, Part B, 2018, 148, 188–192 CrossRef CAS.
  63. W. Pessoa, A. Roule, E. Nolot, Y. Mazel, M. Bernard, M. C. Lepy, Y. Menesguen, A. Novikova, P. Gergaud, F. Brigidi and D. Eichert, Spectrochim. Acta, Part B, 2018, 149, 143–149 CrossRef CAS.
  64. E. Nolot, B. Caby, R. Gassilloud, M. Veillerot and D. Eichert, Spectrochim. Acta, Part B, 2018, 149, 71–75 CrossRef CAS.
  65. T. Yamada, H. Takahara, A. Ohbuchi, W. Matsuda and Y. Shimizu, Spectrochim. Acta, Part B, 2018, 149, 256–260 CrossRef CAS.
  66. R. Fernandez-Ruiz, M. J. Redrejo and E. J. Friedrich, Spectrochim. Acta, Part B, 2018, 149, 107–111 CrossRef CAS.
  67. H. Takahara, A. Ohbuchi and K. Murai, Spectrochim. Acta, Part B, 2018, 149, 276–280 CrossRef CAS.
  68. R. Fernandez-Ruiz, A. von Bohlen, E. J. Friedrich and M. J. Redrejo, Spectrochim. Acta, Part B, 2018, 145, 99–106 CrossRef CAS.
  69. M. Evertz, T. N. Kroger, M. Winter and S. Nowak, Spectrochim. Acta, Part B, 2018, 149, 118–123 CrossRef CAS.
  70. K. Tsuji, N. Yomogita and Y. Konyuba, Spectrochim. Acta, Part B, 2018, 144, 68–74 CrossRef CAS.
  71. J. Prost, A. Zinkl, D. Ingerle, P. Wobrauschek and C. Streli, Spectrochim. Acta, Part B, 2018, 147, 13–20 CrossRef CAS.
  72. E. Marguí, I. Queralt, M. Guerra and N. Kallithrakas-Kontos, Spectrochim. Acta, Part B, 2018, 149, 84–90 CrossRef.
  73. K. V. Oskolok, O. V. Monogarova and N. V. Alov, Anal. Lett., 2018, 51(15), 2457–2467 CrossRef CAS.
  74. Z. Bahadir, L. Torrent, M. Hidalgo and E. Marguí, Spectrochim. Acta, Part B, 2018, 149, 22–29 CrossRef CAS.
  75. Z. Bahadir, M. Yazar and E. Margui, Anal. Chem., 2018, 90(23), 14081–14087 CrossRef CAS PubMed.
  76. S. Dhara, A. Khooha, A. K. Singh, M. K. Tiwari and N. L. Misra, Spectrochim. Acta, Part B, 2018, 144, 87–91 CrossRef CAS.
  77. H. Yoshii, Y. Izumoto, T. Matsuyama, K. Ishii and Y. Sakai, Spectrochim. Acta, Part B, 2018, 148, 183–187 CrossRef CAS.
  78. P. Hönicke, M. Krämer, L. Lühl, K. Andrianov, B. Beckhoff, R. Dietsch, T. Holz, B. Kanngieβer, D. Weißbach and T. Wilhein, Spectrochim. Acta, Part B, 2018, 145, 36–42 CrossRef.
  79. A. Shulyumova, A. Maltsev and N. Umarova, X-Ray Spectrom., 2018, 47(5), 396–404 CrossRef CAS.
  80. G. V. Pashkova, T. S. Aisueva, A. L. Finkelshtein, T. Y. Cherkashina and A. A. Shchetnikov, Microchem. J., 2018, 143, 264–271 CrossRef CAS.
  81. S. Böttger, I. M. B. Tyssebotn, W. Jansen and U. E. A. Fittschen, Spectrochim. Acta, Part B, 2018, 147, 93–99 CrossRef.
  82. R. A. Crocombe, Appl. Spectrosc., 2018, 72(12), 1701–1751 CrossRef CAS.
  83. E. Dao, M. P. Zeller, B. C. Wainman and M. J. Farquharson, J. Trace Elem. Med. Biol., 2018, 50, 305–311 CrossRef CAS.
  84. F. S. M. Afzal, A. Al-Ebraheem, D. R. Chettle, E. D. Desouza, M. J. Farquharson, J. M. O’Meara, A. Pidruczny, B. C. Wainman and F. E. McNeill, Nucl. Instrum. Methods Phys. Res., Sect. B, 2018, 433, 1–9 CrossRef CAS.
  85. D. E. B. Fleming, S. R. Bennett and C. J. Frederickson, J. Trace Elem. Med. Biol., 2018, 50, 609–614 CrossRef CAS PubMed.
  86. J. T. Padilla, J. Hormes and H. M. Selim, Geoderma, 2019, 337, 143–149 CrossRef CAS.
  87. A. Rawal, S. Chakraborty, B. Li, K. Lewis, M. Godoy, L. Paulette and D. C. Weindorf, Geoderma, 2019, 338, 375–382 CrossRef.
  88. S. Kobayashi, T. Shinomiya, Y. Uchihori, H. Kitamura, S. Iwamoto, K. Kojima, Y. Goto, S. Kobayashi, K. Tanimoto, Y. Terakado, Y. Nakajima, H. Yoshida and A. Yamanishi, Radiat. Meas., 2018, 118, 43–49 CrossRef CAS.
  89. M. A. G. da Silveira, B. R. Pereira, N. H. Medina and M. A. Rizzutto, J. Environ. Radioact., 2018, 189, 250–254 CrossRef.
  90. D. C. Weindorf, S. Chakraborty, B. Li, S. Deb, A. Singh and N. Y. Kusi, Waste Manag., 2018, 78, 158–163 CrossRef CAS.
  91. K. Hagiwara, Y. Koike, M. Aizawa and T. Nakamura, Anal. Sci., 2018, 34(11), 1309–1315 CrossRef CAS.
  92. M. Lagerstrom, D. Yngsell, B. Eklund and E. Ytreberg, J. Hazard. Mater., 2019, 362, 107–114 CrossRef.
  93. M. Sharkey, M. A. Abdallah, D. S. Drage, S. Harrad and H. Berresheim, Sci. Total Environ., 2018, 639, 49–57 CrossRef CAS.
  94. L. P. O’Neil, D. C. Catling and W. T. Elam, Nucl. Instrum. Methods Phys. Res., Sect. B, 2018, 436, 173–178 CrossRef.
  95. V. Panchuk, I. Yaroshenko, A. Legin, V. Semenov and D. Kirsanov, Anal. Chim. Acta, 2018, 1040, 19–32 CrossRef CAS.
  96. I. Costantini, K. Castro and J. M. Madariaga, Anal. Methods, 2018, 10(40), 4854–4870 RSC.
  97. J. K. Delaney, D. M. Conover, K. A. Dooley, L. Glinsman, K. Janssens and M. Loew, Heritage Sci., 2018, 6, 31,  DOI:10.1186/s40494-018-0197-y.
  98. M. Hlozek, T. Trojek, R. Prokes and V. Linhart, Radiat. Phys. Chem., 2019, 155, 299–303 CrossRef CAS.
  99. R. Prokes, V. Antuskova, R. Sefcu, T. Trojek, S. Chlumska and T. Cechak, Radiat. Phys. Chem., 2018, 151, 59–64 CrossRef CAS.
  100. P. Zhou, Z. G. Liu, X. Y. Lin, X. Liu, L. Ye, X. Y. Wang, K. Pan and Y. D. Li, Nucl. Instrum. Methods Phys. Res., Sect. B, 2018, 423, 37–41 CrossRef CAS.
  101. T. Swanston, T. L. Varney, M. Kozachuk, S. Choudhury, B. Bewer, I. Coulthard, A. Keenleyside, A. Nelson, R. R. Martin, D. R. Stenton and D. M. L. Cooper, PLoS One, 2018, 13(8) DOI:10.1371/journal.pone.0202983.
  102. G. Van der Snickt, S. Legrand, I. Slama, E. Van Zuien, G. Gruber, K. Van der Stighelen, L. Klaassen, E. Oberthaler and K. Janssens, Microchem. J., 2018, 138, 238–245 CrossRef CAS.
  103. K. A. Dooley, E. M. Gifford, A. van Loon, P. Noble, J. G. Zeibel, D. M. Conover, M. Alfeld, G. Van der Snickt, S. Legrand, K. Janssens, J. Dik and J. K. Delaney, Heritage Sci., 2018, 6, 46,  DOI:10.1186/s40494-018-0212-3.
  104. C. Defeyt, E. Herens, F. Leen, F. Vandepitte and D. Strivay, Heritage Sci., 2018, 6, 33,  DOI:10.1186/s40494-018-0198-x.
  105. H. C. dos Santos, C. Caliri, L. Pappalardo, R. Catalano, A. Orlando, F. Rizzo and F. P. Romano, Microchem. J., 2018, 140, 96–104 CrossRef CAS.
  106. P. Molaro, F. P. Romano and C. Tuniz, Astron. Nachr., 2018, 339(9–10), 718–724 CrossRef CAS.
  107. C. Seccaroni, N. Aresi, T. Frizzi, C. Anselmi and A. Sgamellotti, Rendiconti Lincei. Sci. Fis. Nat., 2018, 29(3), 499–510 CrossRef.
  108. I. Costantini, M. Veneranda, M. Irazola, J. Aramendia, K. Castro and J. M. Madariaga, Microchem. J., 2018, 138, 154–161 CrossRef CAS.
  109. C. Germinario, I. Francesco, M. Mercurio, A. Langella, D. Sali, I. Kakoulli, A. De Bonis and C. Grifa, Eur. Phys. J. Plus, 2018, 133, 159,  DOI:10.1140/epjp/i2018-12224-6.
  110. J. Zelinska, I. Kopecka, E. Svobodova, S. Milovska and V. Hurai, J. Cult. Herit., 2018, 33, 90–99 CrossRef.
  111. E. Pospisilova, K. Novotny, P. Porizka, D. Hradil, J. Hradilova, J. Kaiser and V. Kanicky, Spectrochim. Acta, Part B, 2018, 147, 100–108 CrossRef CAS.
  112. F. Salvemini, E. Barzagli, F. Grazzi, M. Picollo, A. Agostino, M. G. Roselli and M. Zoppi, Archaeol. Anthropol. Sci., 2018, 10(8), 1881–1901 CrossRef.
  113. S. Legrand, P. Ricciardi, L. Nodari and K. Janssens, Microchem. J., 2018, 138, 162–172 CrossRef CAS.
  114. L. de Viguerie, S. Rochut, M. Alfeld, P. Walter, S. Astier, V. Gontero and F. Boulc’h, Heritage Sci., 2018, 6, 11,  DOI:10.1186/s40494-018-0177-2.
  115. L. Van Loon, N. R. Banerjee, M. W. Hinds, R. Gordon, G. Bevan and R. W. Burgess, J. Anal. At. Spectrom., 2018, 33(10), 1763–1769 RSC.
  116. D. Martorelli, M. Bortolotti, L. Lutterotti, G. Pepponi and S. Gialanella, X-Ray Spectrom., 2019, 48(1), 8–20 CrossRef CAS.
  117. A. M. Gojska and E. A. Mista-Jakubowska, Nucl. Instrum. Methods Phys. Res., Sect. B, 2018, 433, 28–33 CrossRef CAS.
  118. L. Ortega-San-Martin, M. K. Sarango-Ramirez and B. C. Galarreta, X-Ray Spectrom., 2019, 48(1), 21–28 CrossRef CAS.
  119. F. Lopes, R. J. C. Silva, M. F. Araujo, V. H. Correia, L. Dias and J. Mirao, Microchem. J., 2018, 138, 438–446 CrossRef CAS.
  120. M. A. Roxburgh, S. Heeren, D. J. Huisman and B. J. H. Van Os, Archaeometry, 2019, 61(1), 55–69 CrossRef CAS.
  121. S. Porcinai and M. Ferretti, Spectrochim. Acta, Part B, 2018, 149, 184–189 CrossRef CAS.
  122. D. Magrini, D. Attanasio, S. Bracci, E. Cantisani and W. Prochaska, Archaeol. Anthropol. Sci., 2018, 10(5), 1141–1152 CrossRef.
  123. S. Ichikawa, T. Matsumoto, T. Nakamura and T. Kurisaki, X-Ray Spectrom., 2019, 48(2), 110–128 CrossRef.
  124. M. A. C. Ontiveros, E. Tsantini, L. Fantuzzi and J. Ramon, Archaeol. Anthropol. Sci., 2019, 11(2), 627–649 CrossRef.
  125. M. Alfeld, M. Mulliez, J. Devogelaere, L. de Viguerie, P. Jockey and P. Walter, Microchem. J., 2018, 141, 395–403 CrossRef CAS.
  126. M. Alfeld, S. Pedetti, P. Martinez, P. Walter and C. R. Acad, C. R. Phys., 2018, 19(7), 625–635 CrossRef CAS.
  127. T. Trojek and H. Bartova, Radiat. Phys. Chem., 2019, 155, 310–314 CrossRef CAS.
  128. C. Pelosi, G. Agresti, G. B. Gianni, S. De Angeli, P. Holmes and U. Santamaria, Eur. Phys. J. Plus, 2018, 133, 357 CrossRef.
  129. L. Ghervase, I. M. Cortea, R. Radvan, L. Ratoiu and A. Chelmus, Microchem. J., 2018, 138, 509–518 CrossRef CAS.
  130. O. Juarez-Rodriguez, D. Argote-Espino, M. Santos-Ramirez and P. Lopez-Garcia, Quat. Int., 2018, 483, 148–159 CrossRef.
  131. G. Simsek, O. Unsalan, K. Bayraktar and P. Colomban, Ceram. Int., 2019, 45(1), 595–605 CrossRef CAS.
  132. R. Montanari, M. F. Alberghina, A. C. Municchia, E. Massa, A. Pelagotti, C. Pelosi, S. Schiavone and A. Sodo, J. Cult. Herit., 2018, 32, 232–237 CrossRef.
  133. S. Zaleski, Y. Takahashi and M. Leona, Heritage Sci., 2018, 6, 32,  DOI:10.1186/s40494-018-0195-0.
  134. K. Laclavetine, C. Boust, L. Clivet, A. S. Le Ho, E. Laval, R. Mathis, M. Menu, E. Pagliano, X. Salmon, V. Selbach, C. Vrand and S. Lepape, Microchem. J., 2019, 144, 419–430 CrossRef CAS.

Footnote

Joint review coordinators.

This journal is © The Royal Society of Chemistry 2019