Atomic spectrometry update: review of advances in the analysis of metals, chemicals and functional materials

Simon Carter a, Andy Fisher b, Raquel Garcia c, Bridget Gibson d, John Marshall *e and Ian Whiteside f
aHull Research and Technology Centre, BP, Saltend, East Yorkshire, HU12 8DS, UK
bSchool of Geography, Earth and Environmental Sciences, Plymouth University, Drake Circus, Plymouth, PL4 8AA, UK
cBP FPT Technology Centre, Whitchurch Hill, Pangbourne, RG8 7QR, UK
dIntertek Sunbury Technology Centre, Shears Way, Sunbury, Middlesex, TW16 7EE, UK
eGlasgow Caledonian University, Glasgow, Scotland G4 0BA, UK. E-mail: j.marshall@gcu.ac.uk
fMiddlesborough, Cleveland, TS6 6US, UK

Received 7th September 2016

First published on 12th October 2016


Abstract

This ASU review focuses on developments in applications of atomic spectrometry to the characterisation of metals, chemicals and functional materials. While each of these application categories is very distinct in terms of the analytical challenges posed, there are a number of common themes than can be identified from an examination of the relevant literature appearing over the review period. The traditional atomic spectrometry techniques (e.g. AAS, OES, XRF, ICP-MS) are relatively mature, but reports continue to appear that seek to address perceived limitations in sensitivity in certain applications, but increasingly more frequently in relation to sample handling and preparation/extraction methodologies, validation and creation of SRMs and methods. However, it is equally clear that because of that very maturity such techniques are more often cited as analytical reference methods to support the development of other approaches (e.g. GD-OES, GD-MS, PIXE, PIGE, RBS, SEM-EDS, SIMS, TXRF, micro- and macro-XRF, XAS, XPS) that provide either direct sampling or depth and lateral elemental profiling capabilities. Consequently, a variety of techniques may now be routinely applied within an individual study to characterise samples to the extent it is hard to comment critically on the particular analytical novelty that lies at the heart of the work. It is fair to say that in some cases, the significance of the research now involves revealing the features of the sample (including examining surface modifications, coatings, thin films and multilayers, or even the characteristics of a device, functional component, or object, or complex mixture) rather than in the development of the analytical approach itself. That said, certain trends in technique development still expand the range of applications that can be addressed. For example, interest in LIBS continues to command attention and is heavily cited in most application sections of this review. The technique offers certain unique advantage for elemental analysis in rapid direct sampling, portability and operating in remote and harsh environments (including industrial production) where low level detection is not essential. Clearly sensitivity remains the Achilles' heel for LIBS but developments in measurement technique such as pulse delay are resulting in better optimised procedures. The development in laser solid sampling technology is providing benefits applicable to other techniques such as ICP-MS and newer variants such as laser ionisation MS. Indeed, lasers, flames, plasmas and other electrical discharges have been used regularly in the fabrication of samples. The atomic spectrometry techniques with which they have been associated are now employed to study such production processes in situ. The development of nanomaterials has given rise to new approaches to particle size distribution and single particle characterisation where the atomic spectrometric determination produces a size rather than a concentration. There is evidence too in the review of research work going on to understand the environmental consequences of the widespread use of new technologies using data analysis approaches to examine source, provenance or impact. Consequently, while the fundamental analytical questions: “What?” and “How much?” continue to be relevant to researchers increasingly these must now be qualified in many situations by providing answers to enquiries such as “Where?” and “How big (or small)?”.


Foreword

This is the latest review covering the topic of advances in the analysis of metals, chemicals and functional materials. It follows on from last year's review in the series.1

1 Metals

This review period has seen a very diverse range papers published covering the analysis of metals and alloys. This diversity is reflected by the range of applications in which atomic spectrometry is used and highlights the interdisciplinary importance of this topic.

There has been a trend in recent years reflecting the growing importance of micro-structural analysis and this continues to be clearly evident in this review period spanning a range of metals. In many modern high performance metals, it is often the type and abundance of particulates such as non-metallic inclusions or intermetallic compounds that determine the desired properties of the metal. As a result, many of these papers are based on a direct analysis from solid samples, which is one of the strongest themes underlying this review.

Metal surface modification and coating deposition have become significant areas of development and of considerable commercial interest. Many of the applications described supported the development of new coatings, novel surface modifications and atomic spectrometric techniques also played a valuable role in assessing in-use performance. Noteworthy papers covering this topic which contribute to the development of new materials and processes are listed in Table 1.

Table 1 Application of atomic spectrometry to the analysis of high performance metal based materials
Element Matrix Technique; atomisation; presentation Comments Reference
Al Aluminium fabrications in pressurised water reactors ICP-OES and SIMS Analytical data from a range of experiments facilitated the development of models for the rate of Al release with temperature and pH 2
B Aluminium fabrications in pressurised water reactors ICP-OES and SIMS See Al 2
H Magnesium anode ICP-OES and RBS Surface enrichment of elements was reported and a mechanistic understanding of this effect on the evolution rate of hydrogen was proposed 3
Li Magnesium–lithium alloy OES, XRD, XPS and SEM The use of atomic emission data directly from the process plasma to identify the operating conditions which provide most robust surface modification, evaluated by XRD, XPS and SEM 4
Mg Magnesium–lithium alloy OES, XRD, XPS and SEM See Li 4
Mg Magnesium implants TOF-SIMS and XPS Use of analytical data to provide insight into the structure and bonding involved in organic self-assembly layers on implants to improve biocompatibility 5
Mo Carbon Steel (galvanised) coated with a Zn/Al layered double hydroxide coating (LDHC) XRD, ICP-OES, and ATR-IR Ion-exchange mechanism for molybdate release identified using bicarbonate ions. Zn dissolution shown to be associated with Molybdate release. Surface environment proposed as a method of controlling the level of corrosion inhibition in LDHC 6
O Steel (weld joint) PIGE Sensitive, non-destructive analytical methods were used to depth profile oxygen in weld joints to a depth of 6 to 11 microns 7
Y Stainless steel (Ni-base super alloy) XRD, SRXRF Analysis of Ni/Y phases identified the gamma phase as ideal for corrosion resistance corresponding to a 0.05% alloying addition of Y 8
Zn Carbon steel (galvanised) coated with a Zn/Al layered double hydroxide coating (LDHC) XRD, ICP-OES, and ATR-IR See Mo 6
Various (3) Aerospace steels TOF-SIMS, SEM and XRF Study of thermal cycling conditions similar to those experienced in-service. Al was shown to diffuse along grain boundaries forming an oxide on the surface in addition to intergranular Al2O3. Ti and Nb inclusions were found to appear after the first oxidation cycle 9
Various Brass thin films XRD and XRF A study of the influence of Grimm type discharge argon flow rate on the sputter deposition of thins films. The surface analysis by XRF was used to assess film composition and XRD was used to investigate the structure of coatings produced 10
Various Galvanised steels SEM, GD-OES Study of corrosion resistance of galvanised coatings in alkaline solution 11
Various (4) Stainless steel (antibacterial Cu-bearing) ICP-OES, XPS The Cu2+ ions were found to be released at a rate of 0.8 ppb per cm3 per day. Other ions (Cr, Cu and Ni) were shown to be released from the metal matrix 12
Various (4) Stainless steel (ultra-high strength) XPS, AES, SEM, EDS Outer corrosion products were shown to be oxides of Fe, Co, Cr, and Mo with inner corrosion forming oxides of Cr and Mo 13


1.1 Ferrous metals. Analysis of micro-structural features in ferrous materials is of growing importance, with a particular emphasis on non-metallic inclusions such as oxides, sulphides, nitrides and carbides. These can have a critical impact on the design properties of modern high performance steels. In the development of wear resistant stainless steel, Khaki et al.14 used several spectroscopic techniques to establish the composition and location of Al2O3 inclusions within the matrix of 304 grade stainless steel. Thus EDXRF was used to identify Al2O3 particles evenly distributed within austenite and ferrite phases as determined by XRD. This structure was reported to enhance the hardness and wear resistance of this steel grade.

Detecting nano- and micro-scale particles that are not in a metal matrix is often required when investigating wear. Harrington et al.15 propose a novel approach of characterising wear particles from stainless steel hip joints generated in vivo, based on asymmetric field-flow fractionation (AFFF). By combining AFFF with UV, light scattering and ICP-MS detection, the authors were able to establish the size range of Co, Cr and Mo particles (in the range 40–150 nm) and provide an indication of the association of metal ions with transport proteins in serum. The authors claimed that this feasibility study had provided the basis for useful pathological data for in vivo investigations into the processes which lead to tissue necrosis and artificial joint failure.

In steel production, spark OES is the only technique that can provide analysis at the required level of sensitivity and in a time frame which does not hinder the steel-making processes. Process control analysis is achieved from the discharge of thousands of individual spark excitations to give a single multi-element result. The work of Janis et al.16 exploited the multi-element measurements from individual spark discharges to qualitatively identify and quantitatively measure the presence of non metallic inclusions in low carbon steels. Individual sparks which encounter inclusions generate high emission intensities from localised high concentration of elements present. Spark discharges on matrix metal generate lower intensities which represent the concentration of each element alloyed in the steel. The authors used this technique to establish the type and distribution of Al and Ca oxide and Ca sulphide based inclusions in steel samples. Good agreement with conventional SEM characterisation was reported. In addition, the authors claimed the size distribution could be measured by Pulse Discrimination Analysis (PDA) and reported the size range for these inclusions was 2 to 13 μm. Thus PDA provided a level of in-process metallurgy in parallel with bulk process control analysis and from the same analytical cycle. Although conventional SEM-based metallography provides the definitive characterisation in steel production it is slow and can only be performed on final product. However, PDA can provide in-process information on the inclusion population and is the only technique currently capable of achieving this. The component of PDA data not emanating from inclusions represents the element concentration alloyed in the matrix metal. The distribution of elements between inclusion population and matrix metal represents an additional level of information relating to the efficiency of alloying during production. This aspect of PDA is currently underexploited and should be explored further. Efforts to improve the detection sensitivity of LIBS continue with many research groups examining the laser operating parameters. Using a dual pulsed laser operating at 1064 nm, Goa et al.17 demonstrated the effect that pulse energy, inter-pulse delay and optical configuration has on sensitivity. Maximum sensitivity for Cr I (520.84 nm) and Fe I (522.72 nm) in low alloy steel achieved with both pulses operating at 100 mJ. The importance of focusing the initial ablation pulse above the sample surface was reported with the recommendation that the second analytical pulse should be focused 1 mm beyond the sample surface. The emission for Cr showed two maxima from inter-pulse delays of 6 and 15 μs achieving sensitivity enhancement factors of 43 and 49, respectively. Ahmed et al.18 considered the two main parameters influencing the laser metal interaction: laser wavelength and inter-pulse delay in double-pulse operation. Applying the optimal delay between the initial pulse at 1064 nm and the second pulse at 532 nm was shown to enhance the neutral Fe emission lines by a factor of 30 in comparison to single pulse mode. Li et al.19 investigated a spectroscopic approach to establish a basis for improving precision. A multiple-spectral line calibration (MSLC) approach was used in which LIBS intensity ratios were used to train an artificial neural network which was then applied to the analysis of steel samples. The relative performance in terms of precision achieved using this MSLC methodology was compared to that obtained from the conventional approach of internal standardisation. It was found that MSLC improved the RSDs from 11.3% and 19.5%, to 6.4% and 12.9% for Cr and Ni, respectively. Accuracy was measured as the root-mean-square error of cross validation and compared to conventional methods. An improvement in accuracy from 0.018% and 0.067% to 0.010% and 0.023% by weight was reported for Cr and Ni, respectively.

This year there are fewer papers exploring the fundamentals of laser–sample interactions as a route to achieving improved sensitivity for LIBS. This may indicate that this area of research has matured. However, an increase in LIBS applications for ferrous metals is also apparent in the papers reviewed. The basic principles of LIBS are aligned with application in standoff analysis, and therefore, are uniquely suitable for in-process applications in the harsh environment of metals production. Sun et al.20 applied LIBS directly to the analysis of molten steel via a refractory tipped tube. Emission radiation from a double-pulsed laser was collected by a Cassegrain configuration of mirrors to avoid attenuation across the wavelength range. The authors reported a major enhancement in the observed emission intensities for Cr, Mn, Ni, Si and V that was achieved by purging the refractory tipped tube with argon and attributed to improvements in spectroscopic stability. Quantitative performance for these elements was assessed using the univariate and partial least-squares models. The root-mean square error of prediction and the relative standard deviation were reported at 5 and 2–3%, respectively. In situ LIBS analysis for these elements in molten steel was reported to achieve results comparable to the corresponding plant analysis of solidified samples taken from the melt. The authors also described the quantitative capabilities for carbon analysis in molten steel. Carbon is one of a small number of elements emitting in the UV, is present in low concentrations and is critical to steel products. Thus Yao et al.21 reported that optimising the inter-pulse delay between the initial pulse at 532 nm and the second at 1064 nm produced the highest sensitivity for C detection in molten ferroalloys. Chen et al.22 highlighted that steel temperature had a considerable influence on the measurement of C when measured in molten ferroalloy using LIBS. Experimental data showed a 4% error between the samples analysed from solidified samples taken from melt, and the corresponding LIBS analysis.

Recycling scrap metal is a major part of steel-making, particularly in stainless steel production where it represents the bulk raw material input into the process. Kashiwakura et al.23 applied laser induced breakdown spectrometry to identifying the composition of individual pieces of stainless steel scrap. A range of certified reference standards were used for calibration and to identify appropriate emission lines. Emission measurements from longer gate widths and shorter delay times were recommended for good precision along with a large number of laser pulses per analysis. The authors highlighted the attributes of LIBS standoff scrap analysis as: the speed of analysis, not requiring a sub-sample and operational in air at ambient pressures. In a similar application, Sun et al.24 developed an artificial back-propagation neural network to identify the critical components within the entire raw emission spectrum that uniquely identified each of 27 grades of steel.

1.2 Non-ferrous metals. As indicated in the previous section on ferrous materials, micro-structural characterisation is of growing importance as metals are developed with advanced properties. Removal of V and Zr impurities from molten aluminium through the addition of B was studied by Khaliq et al.25 Using EDXRF and electron backscattering diffraction analysis, the authors were able to propose a mechanism for the formation of V and Zr borides from a series of high temperature experiments. The relative rates of removal of these elements were established by ICP-OES and the kinetics of the reactions defined.

The application of LIBS to the analysis of non-ferrous metals has increased in popularity. The complex nature of the laser interaction generally makes it necessary to optimise instrument operation for each sample matrix. Thus Hang et al.26 investigated the influence of the laser parameters which contribute to the matrix effect limiting detection sensitivity. A range of 23 standards of different metals were used in this study including: aluminium, copper, nickel, tungsten and zinc. The influence of laser pulse duration was investigated by applying nanosecond and femtosecond lasers to a buffer-gas assisted ionisation source, coupled to a TOF-MS detector. This allowed the relative sensitivity coefficients of each element to be calculated for each metal matrix. Combining this data set with a range of physical properties of each metal provided a data set for orthogonal partial least-squares evaluation. This revealed that the thermal properties of the metal have a strong influence on the matrix effect induced by nanosecond lasers. Additionally, thermal effects induced by femtosecond laser pulses were shown to be significantly less using S-plot evaluation. A theoretical thermodynamic model was developed around the experimental data. The authors claimed that the model could reasonably explain the processes of the matrix effect.

Improvements to sensitivity in laser induced breakdown spectrometry through the use of magnetic field containment was reported by Ding et al.27 The analysis of an aluminium-lithium alloy using Q-switched Nd:YAG laser (1064 nm) was carried out with and without magnetic containment of the plasma. Emission intensity data from Al and Li were used assess the effect of magnetic containment which was reported to increase sensitivity by a factor of 1.5 to 3 times using a 1.1 T (tesla) field strength. Enhancement to sensitivity was attributed to an increase in density of excited atoms and to increases in electron temperature and density within the plasma due to the magnetic field. Takahashi et al.28 proposed a means of achieving calibration free (CF) LIBS which avoids the need to correct for non-stoichiometric ablation. This approach was based on extending the laser pulse duration for the analysis of immersed samples under high hydrostatic pressure. Using a range of certified brass standards, the concentration of Cu, Pb and Zn were provided via the specific CF algorithm and using a laser pulse duration of 250 ns. Relative errors for Cu and Zn were reported as ±3.3% and ±6.4%, respectively. However, an unacceptably large error was reported for Pb. The authors claimed this approach improved the accuracy of CF LIBS by eliminating the need to correct for the effects of differential evaporation and ablation across the elements. It was conceded that this approach was limited to major elements and not suitable for the determination of elements in concentrations of below 10%.

The application of LIBS to aluminium scrap sorting has been demonstrated by Merk et al.29 Double pulsed laser operation was combined with detection using an Echelle spectrometer. A range of multivariate techniques were employed to maximise the use of the spectral range of the instrument. Using this combination, automated sorting of 10 aluminium grades was achieved at a rate of 25 samples per second with an accuracy of >90%.

The detection of trace metals in complex alloys presents a challenge when analysed by atomic emission because of the effect of spectral interferences. In order to quantify trace amounts of Ni in Co–Cr–Mo alloy Sakamoto et al.30 presented a method of chemically removing elements that would otherwise interfere with low level detection. Initial volatilisation of Cr in the form of chromyl chloride and the selective solvent extraction of Co and Mo into 4-methyl-2-pentanone was used in pre-treatment to remove the sample matrix, resulting in an aqueous solution containing Ni for analysis by ICP-OES. The limit of quantification for Ni using this method was reported to be 0.0006% compared with 0.01% achieved using a conventional acid dissolution method.

1.3 Metals in archaeological artefacts. The application of analytical spectroscopy to archaeological artefacts features strongly in this review period with a clear emphasis on non-invasive and micro-invasive techniques. Mista et al.31 presented the results of an interdisciplinary study carried out on a range of metallic objects from selected archaeological sites in Poland. The samples were analysed predominantly by PIXE, supplemented with SEM, EDXRF, LA-ICP-MS and thermal neutron radiography. From the range of data generated it was possible to confidently state that the artefacts were produced locally via secondary smelting processes. This work has parallels with modern metals production as much can be interpreted about processing and casting from solidified samples. Establishing provenance is of immense value to the historical record and one which relies heavily on modern analytical techniques. Lesigyarski et al.32 carried out a thorough analysis of trace elements in a 4th century Bulgarian gold wreath. The major elements (Ag, Au and Cu) were determined using ICP-OES and a further 26 trace elements were determined by ICP-MS. The data showed the gold to be of high purity in the range 97.1–99.9%. A bivariate plot of Pd and Pt concentrations showed that the gold used in this artefact came from two sources. However, the limited amount of Pt in gold sources from Bulgaria prevented a specific geographical location being identified. Instruments with isotope differentiation capabilities offer an additional insight into the provenance of raw materials used in metals production. For example, Muller et al.33 used a multi-collector ICP-MS to examine the Pb isotopes in sling shot and other lead objects from the late Roman period. The shot and some of the other artefacts found in the Menorca originated from ore mined on the Iberian mainland. Mixed relationships indicated that some artefacts were produced from recycled material.

2. Chemicals

2.1 Petrochemicals, oils and fuels. The volume of published information relating to crude oils and related petrochemical products continues to fall, possibly due to the global slump in oil price and subsequent lack of investment in research and development. In these challenging times research needs to focus on the problems the industry faces with lack of investment and cost reductions. It is surprising that authors continue to promote expensive, time consuming methods using inappropriate instruments which may be interesting academically but provide no meaningful industrial benefits. Many of these methods achieve limits of detection etc. worse than currently run routine industry standards. The focus should be on developing smart, elegant, cost effective, time saving analytical solutions. A worthwhile starting point for such developments would be to review not only the academic literature but also ASTM, IP, UOP and other industry standard methods. Those reviewing these papers for publication also need a thorough understanding of current industry standards and practices. Papers were noted in the period under review that should not have passed peer review as there was nothing new or novel beyond the industry standard method they had re-invented. The number of papers relating to coal has increased this year with a large contribution from China. The use of LIBS is currently very popular in this applications but most papers appearing were related to the characterisation of coal rather than to the development of new techniques for analysis. Applications of atomic spectrometric techniques to the characterisation of alternative fuels is also an area of growing activity in which bio fuels feature strongly. Environmental concerns and compliance with new legislation appear to be driving this field forward despite the current low oil price.
2.1.1 Petroleum products. Publication activity in this field was much reduced in comparison with previous years, but there were a small number of papers worth highlighting. For example, He et al.34 described a method for the analysis of trace elements in jet fuel by ICP-MS using emulsion breaking extraction and ICP-MS. The optimisation of nitric acid concentration, emulsifying agents, centrifugal speed and extraction time were investigated to improve the extraction efficiency. Limits of detection for Cu, Fe, Mn and Zn were reported in the range 0.028 μg L−1 for Mn to 0.116 μg L−1 for Fe. Analysis of spiked samples produced recoveries for the listed elements between 90–107% by comparison with alternative methods. Nomngongo et al.35 described an on-line hollow fibre membrane micro-extraction technique for the determination of Co, Cr, Mo, Ni, Sb and V in diesel and gasoline samples. An Al2O3–TiO2 hollow fibre membrane was synthesized and linked on-line to an ICP-MS instrument. Experimental parameters were optimised and limits of detection were achieved of 0.1–0.9 ng L−1. As always, the determination of S continues to be a hot topic and two papers were worthy of particular attention. Thus Cruz et al.36 investigated the feasibility of determination of sulfur in diesel oils by ICP-OES after microwave induced combustion using a flame retardant. Combustion systems are a suitable alternative to conventional digestion methods but for volatile samples like diesel the method is restricted to low sample weights due to the pressure generated during combustion. Glass wool was used by the authors as a flame retardant making it possible to burn up to 400 mg of diesel oil without increasing the pressure to dangerous levels. The S results obtained were compared to those from ASTM D5453-12 and agreement better than 95% was obtained. Huber et al.37 investigated chemical modifiers for S determination in diesel fuels by high resolution continuum source graphite furnace molecular absorption spectrometry. The rotational line of carbon monosulfide at 258.056 nm was used to measure the absorbance and the modifiers used were a mixture of Pd and Mg in combination with Ir. L-Cysteine aqueous standard solutions were used and the method was checked using CRM sulfur in diesel fuel (NIST 2724b) after dilution with propan-1-ol. The limit of detection achieved was 1.4 mg kg−1.
2.1.2 Oils and lubricants. The number of contributions in this field has reduced significantly compared to previous years. A few papers are of particular note. He et al.38 described extraction induced by emulsion breaking as a tool for simultaneous multi-element determination in used lubricating oils by ICP-MS. In the method 4 mL of each oil sample was mixed with 1 mL of toluene then emulsified with 1 mL of Triton X-114 acid solution. Once the extraction of the metals was complete the emulsion was broken by centrifugation for 10 min at 6000 rpm. The lower aqueous phase containing the analytes was collected for analysis by ICP-MS. Several parameters affecting the extraction efficiency of the procedure were investigated including the nature and concentration of the solvent used for sample dilution, the type and concentration of the surfactant, the concentration of HNO3, extraction time, collection time and centrifugal speed. The limits of detection for Cr, Cu, Mg, Ni, and Pb were 0.058, 0.028, 0.126, 0.078 and 0.009 μg L−1 respectively. The evaluation of six sample preparation methods for determination of trace metals in lubricating oils using ICP-OES has been described by Tekie et al.39 The methods were xylene dilution, detergent emulsion, microwave digestion, dry-ashing, wet-ashing and ultrasonic extraction. The validity of the methods studied was confirmed through the analysis of quality control samples and analyte recoveries (for Ag, Ba, Cu, Mn and Ni) ranging from 48.3 to 106% were obtained. Based on these evaluations, ultrasonic extraction was found to offer clear advantages in terms of accuracy, applicability for routine analysis, time and cost of sample preparation. Park et al.40 investigated the characterization of metal complexes in Kuwait atmospheric residues using GPC coupled with both ICP-MS and HT GC-OES. The aim of the study was to characterize the vanadium and nickel species in saturate, aromatic, resin and asphaltene fractions. It was found that most of vanadium and nickel complexes were found in the resin and asphaltene fractions while there was a very small amount of non-porphyrinic metal species in the aromatic fractions. The nickel complexes showed higher molecular weight than those of the vanadium complexes. The porphyrin units existing in the asphaltenes linked to the larger aggregates while in the resins they were associated with smaller aggregates.

The final paper to be highlighted in this section concerns the is by and investigation of the stable isotopic composition of Mo, Ni and V in crude oils by Ventura et al.41 Crude oils often have high concentrations of transition metals including Fe, Ni, V and to a lesser extent, Mo. Determining the conditions under which these metals enter into crude oil is of interest for the understanding of biogeochemical cycles and the pathways leading to oil formation. This study presents the first high precision measurements of Mo, Ni, and V stable isotopes for a set of globally distributed crude oils. Vanadium stable isotope compositions were presented for crude oils formed from different source rocks spanning the geologic ages Paleozoic to tertiary and were complemented by Ni and Mo stable isotope compositions on a subset of crude oils produced from lacustrine source rocks from the Campos Basin, Brazil. The crude oils spanned a wide range of V and Mo isotope compositions but displayed more restricted Ni stable isotope signatures. The samples were diluted in dichloromethane to produce a homogeneous sample from with aliquots were taken and digested using a microwave. A number of microwave cycles was used to ensure sample digestion and some of the aliquots were recombined to ensure enough of the analyte was in the solution for analysis. Following microwave digestion, samples were transferred to cleaned Savillex beakers and isotopic spikes added prior to ion exchange separation. The isotopic analysis was performed using MC-ICP-MS. The contrasting behaviour of these three isotope systems in this initial dataset provides guidance for future investigation to fully exploit the potential of these new isotopic tracers.


2.1.3 Coal, peat and other solid fuels. The majority of papers in this section feature LIBS particularly in relation to process and quality control. Li et al.42 described a method for quantitative C analysis in coal combining data processing and spatial confinement with LIBS. The measurement accuracy of C content by LIBS can suffer from low accuracy due to matrix effects. In this study, cylindrical cavity confinement was used with a combination model to improve the measurement accuracy of the technique in this application. The coefficient of determination, root-mean-square error of prediction, average relative error, and average absolute error for the combination model with cylindrical cavity confinement were 0.99, 1.35%, 1.66%, and 1.08%, respectively improving on measurements without cylindrical cavity confinement and are close to the 1.0% critical requirement for the Chinese national standard. Power plants need to rapidly determine coal quality to optimise the combustion process and the development of an instrument that can meet this requirement would have an immediate impact. Thus Zhang et al.43 have described the development of a coal quality analyser based on LIBS. An analyser comprising sampling equipment, LIBS analyser and control module using support vector regression combined with principal component analysis was applied to the direct analysis of coals. The instrument was calibrated using previously analysed samples. The root-mean-square error for prediction of the ash content decreased from 2.74% to 1.82%, volatile matter from, 1.69–1.22%, and calorific value from 123 MJ kg−1 to 0.85 MJ kg−1. The corresponding average relative error of the predicted samples was significantly reduced from 83% to 5.48%, 5.83–4.42%, and 5.4–3.68%, respectively. In an important development, Redoglio et al.44 presented the preliminary results of laboratory tests carried out on the analysis of moving samples of coal using laser induced breakdown spectrometry. An innovative LIBS system with a large depth of field was designed to operate on-line in a coal fired power plant. To mimic the real situation in the laboratory coal samples were sequentially positioned under the measuring head by means of a translation/rotation unit replicating the behaviour of the raw coal being transported by a conveyor belt. Experimental results showed that both carbon and hydrogen concentration and the content of some inorganic components (Al, Ca, Fe, Si) could be evaluated with good accuracy.

Achieving good accuracy in the direct analysis of solid sample such as coal is always challenging because of variations in analyte response. Thus Yao et al.45 described a method for the analysis of inorganic elements in coal using a new internal standardisation scheme utilising the atomic line of carbon at 247.86 nm and the molecular bands of CN at 388.34 nm and C-2 at 516.32 nm to normalize the lines of the inorganic elements. Twenty calibration samples and five validation samples were analysed. The results showed that the coefficients of determination R2 and the slope of the calibration with the proposed internal standardization scheme were superior to those using fixed internal standardization or no internal standard. The results suggest that the proposed new internal standardization scheme compensates for the matrix effects and the influence of the difference in the spectral response of the light collection system. Dong et al.46 developed a system for the elemental analysis of coal using tandem LIBS and LA-TOF-ICP-MS. This allowed the simultaneous determination of major and trace elements in coal samples. Calibration strategies were investigated specifically the use of univariate and multivariate data analysis on analytical performance. Partial least squares regression was shown to compensate for matrix effects in both the emission and mass spectrum data improving the analysis.

Coal is a notoriously difficult material to digest in a timely manner. Consequently, Krishna et al.47 described a new procedure for the digestion of coal samples using oxidative pyrolysis and microwave digestion. The coal samples were pyrolysed by heating to 500 °C in the presence of oxygen. Microwave digestion using an acid mixture (8 mL of either 20% HNO3 + 5% HF + 5% H2O2 or 20% HNO3 + 0.4% NH4HF2 + 5% H2O2) was then applied to the pyrolysed coal residue. Analysis was carried out by ICP-MS. Studies utilising NH4HF2 demonstrated that it can be used as a replacement to the highly toxic HF digestion method achieving a quantitative recovery of >95% for most of the elements studied. An alternative method for the analysis of S in coal samples using H2O2 and microwave digestion was described by Mketo et al.48 S recoveries of 89–101% were achieved on CRM's (SARM 18, 19 and 20) using a microwave temperature of 150 °C, an extraction time of 5 minutes and a H2O2 concentration of 3 mol L−1. Analysis was performed using ICP-OES. The limit of detection achieved was 0.014 mg kg−1. The proposed method converted all S species to sulphates, as confirmed by IC analysis. Finally, Vogt et al.49 described a method for the direct quantitative multi element analysis of coal by ETV-ICP-OES. The ETV unit was coupled to the ICP-OES using PFA transport tubing and a cold argon gas flow was used to transport the dry aerosol to the plasma. Both axial and radial ICP-OES instruments were investigated. The ETV program consisted of a relatively slow heating rate to prevent a detector overflow due to the relatively high concentrations of the analytes in the samples. Emission lines with low sensitivity and wide linear dynamic range were chosen to accommodate the high sample input to the plasma. The elements investigated (18) were Al, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Si, Ti, V and Zn. Calibration lines were achieved by using coal reference materials of different ranks from lignite to semi-anthracite. Linear calibrations over three to four orders of magnitude were obtained. Two coal reference materials NIST 1632d and NIST 1635a were used to verify the accuracy of the method. Recoveries ranged from 80–114% for NIST 1632d and from 98 to 120% for NIST 1635a. This method would appear to be a suitable, quick, cost effective alternative to the complex digestion methods commonly used for coal analysis.


2.1.4 Alternative fuels. Biodiesel and bio-ethanol feature strongly in the published literature under review. Duarte et al.50 described a method for the determination of Pb in biomass and products using HR-CS GF AAS. The method is applicable to biomass, bio-oil, pyrolysis aqueous phase and biomass ashes using direct solid or liquid sample analysis. Measurements were performed without a chemical modifier and calibration was carried out using aqueous standard solutions. A pyrolysis temperature of 800 °C and an atomization temperature of 2200 °C was used. The LODs reported were 0.514 μg kg−1 using the line at 217.001 nm and 6 μg kg−1 using the line at 283.306 nm. Sanchez et al.51 have described a new method for the determination of metals in bio ethanol using a heated torch integrated sample introduction system (hTISIS) to directly introduce the sample in a vaporized form for direct analysis by ICP-OES. Matrix effects caused by ethanol–water mixtures were removed by operating the hTISIS at 400 °C using flow injection. The system could also be operated in continuous mode at 200 °C and still achieved removal of interferences. Recoveries from 80% to 120% were obtained for 18 analytes. The LOD’s reported ranged from 3 ng mL−1 for Mn to 500 ng mL−1 for Ca.

A method for the determination of trace elements in ethanol fuel using ICP-MS-MS instrumentation has been described by Virgilio et al.52 The method was designed to overcome matrix induced spectral interferences on As, Cr, P, Pb, Si and V. Oxygen was used to mass shift the Cr, P and Si ions away from interferent ions by producing oxide ions that are measured by the second quadrupole at +16 AMU for Cr and P and in the case of Si the dioxide ion at +32 AMU. Limits of detection reported were 0.01 μg L−1 for As, 0.04 μg L−1 for Cr, 2 μg L−1 for P, 0.09 μg L−1 for Pb, 1 μg L−1 for Si and 0.02 μg L−1 for V. Spike recoveries for the six analytes were reported in the range 93–110%. A review, containing 176 references, of greener procedures for biodiesel quality control has been published by Amais et al.53 Environmentally friendly alternatives which have been presented for bio diesel quality control were discussed. These approaches include direct analysis, improved sample preparation by dilution or analyte extraction with nontoxic solvents, preparation of emulsions or micro-emulsions and sample mineralisation as well as strategies for the minimisation of reagent consumption and waste generation. These greener alternatives were critically reviewed, highlighting the advantages and limitations of each approach in biodiesel analysis.

2.2 Organic chemicals and solvents. In this review period a large number of papers have been published that focus primarily on applications to the analysis of organic chemicals and solvents rather than substantial analytical developments that advance the field. Consequently, a summary of those applications considered to be of potential interest is presented in Table 2.
Table 2 Application of atomic spectrometry to the analysis of organic chemicals and solvents
Element Matrix Technique; atomization; presentation Comments Reference
Al Body lotions AA; ETA; l High resolution continuum source GFAAS was employed applied to determine Al in moisturizing body lotions. The 309.271 nm line was selected for analysis and Zr as permanent modifier in order to improve atomization efficiency and reduce Al interaction with the graphite surface. A LOD of 30 ng g−1 was reported 54
Cd Cosmetics AA; F; l and s Method development and validation for Cd determination in eye shadow blush and compact powder by means of two procedures. Microwave digestion followed by LS-GFAAS determination and direct solid sampling HR–CS–GFAAS 55
Cr Cosmetics MS; ICP; l A method developed for Cr(VI) determination based on alkaline extraction and IC separation followed by DRC-IP-MD detection. A LOQ of 0.11 mg kg−1 was reported 56
Cr Cosmetics (eyeliner) OES; LIBS; s Method optimization for the determination of Cr and Pb in kohl. The detection system was optimized in terms of gate delay between laser excitation and data acquisition and optically thin plasma. The LOD reported for Cr was 2 ppm. Levels of Cr found in samples were in the range 4 to 9 ppm respectively 57
Cr Ink OES; LIBS; s LIBS combined with partial least squares regression was applied to Cr determination in ink with ZnO as adsorbent 58
Cu Antifouling paints XRF; —; s Identification of boats hull with high Cu, Sn and Zn concentrations by handheld XRF 59
Pb Cosmetics (lipstick) XRF; —; s Samples were melted with a non-ionic surfactant and yttrium as internal standard before TXRF analysis. The authors present this work as alternative to harsh digestion procedures for sample preparation in routine lead analysis in lipstick. Precision ranged from 11.38% RSD and 0.04 g g−1 was reported as limit of detection for lead 60
Pb Cosmetics (eyeliner) OES; LIBS; s See Cr. Method optimization for determination of Pb and Cd determination in kohl. Limits of detection reported for Pb was were 1 ppm. Levels of Pb found in samples were in the range for lead and 2 ppm for chromium. Levels of lead found in samples range from 8 to 15 ppm 57
Pb Cosmetics (lipsticks and hair dyes) AA; ETA; l Microwave assisted acid digestion followed by dispersive liquid–liquid micro-extraction with acetone, 1-undecanol and diethyl dithiophosphoric acid and GFAAS detection for lead determination in lipsticks and hair dyes made in different countries. Under optimized conditions, reported detection limit was 0.1 g kg−1 61
Sn Antifouling paints XRF; —; s See Cu. This is a proposed new analytical method for TBT coating identification in combination with other techniques (XRD; μ-FTIR; μ-Raman and GC-MS) 59
Zn Antifouling paints XRF; —; s See Cu 59
Various Cosmetics (facial make-up samples) MS; MIPDI; l Study of the qualitative and quantitative potential of the MIPDI as ion source for rapid analysis of preservatives in facial cream, sunscreen and moisturizer 62
AA; F; l and s
Various (11) Cosmetics WDXRF; —; s The authors developed a preparation method to produce replicate thin films of nail polish for WDXRF analysis for the determination of Al, Ca, Cl, F, Fe, K, Mg, Mn, Na, Mg, Si, Ti and V 63
AA; ETA; l
Various Detergents OES; LIBS; s Detection of detergent residues on dishware by LIBS. Ca, Na, C, H and N were found. Na was detected at 35.4 μg cm−2 64
Various Documents OES; LIBS; s Forensic analysis of black ink pens to determine variation in chemical composition of the ink and discrimination. Plasma parameters and adopted experimental condition discussed 65
Various Dyes TOF-SIMS; —; s Identification of dyes in ancient textiles by Raman spectroscopy followed by analysis of organic materials 66
Various Manuscripts XRF; —; s Application of macro XRF and optical coherence tomography for the inspection of an illuminated manuscript 67
Various Manuscripts XRF; —; s Stratigraphic analysis of paint layers. Application of macro XRF and optical coherence tomography for the inspection of an illuminated manuscript 68
OES; LIBS; s
Various (54) Paintings MS; ICP; s Multi-elemental mapping by LA-ICP-MS on small cross-sections and quantification by sum normalization of the elements as their oxides to 100 wt%. Statistical data processing protocols were also elaborated 69
Various Paintings TOF-SIMS; —; s See also ref. 70. Detection of both molecular and elemental species related to CdS pigment and binding medium alteration in paintings. Identification of degradation products was also reported. Evaluation of CXRF as in situ technique for identification of chemical composition of paint layering. Depth profiling by coincidence XRF was compared with SEM-EDX data from cross sections 71
XRF; —; s
Various Paintings pXRF, —, s See also ref. 71. Comparison of three different depth profile XRF techniques for elemental distribution in the surface layer of a painting. Detection of both molecular and elemental species related to CdS pigment and binding medium alteration in paintings. Identification of degradation products was also reported 72
TOF-SIM; —; s
Various Paintings NAAR; —; s Critical comparison of NAAR (neutron activation autoradiography) and macro-XRF capabilities for analysis of historical paintings. Comparison of three different depth profile XRF techniques for elemental distribution in the surface layer of a painting 72
XRF; —; s
Various (54) Paintings MS; ICP; s Multi-elemental mapping by LA-ICP-MS on small cross-sections and quantification by sum normalization of the elements as their oxides to 100 wt%. Statistical data processing protocols were also elaborated. Benefits and limitations of MA-XRF for the study of manuscript illuminations were discussed 69
XRF; —; s
Various (13) Paints AE; ICP; l Method developed for sample preparation of automotive paints consisting of pre-treatment with HNO3 and digestion with HCl/HF followed by ICP-OES determination of Al, As, Ba, Cd, Cu, Cr, Mn, Ni, Pb, Sn, Sr, Ti, Zn 73
Various (10) Paints SRXRF; —; l Eighteen samples of white automotive paints were analysed using SR-XRF. Elements detected included Br, Cr, Cu, Fe, Nb, Pb, Sr, Ti, Zn and Zr 74
Various Paints and inks XRF; —, s See also ref. 65. Evaluation of coincidence-XRF (CXRF) as in situ technique for identification of chemical composition of paint layering. Depth profiling by CXRF was compared with SEM-EDS data from cross sections. Forensic analysis of black ink pens to determine variation in chemical composition of the ink and discrimination. Plasma parameters and adopted experimental condition discussed 70
OES; LIBS; s
Various (10) Pharmaceuticals OES; ICP; s Determination of As, Cd, Cr, Cu, Mn, Mo, Ni, Pb, Pd, Pt, Rh, Ru and V in pharmaceutical samples by solid sampling ETV-ICP-OES. Limits of detection ranged from 0.04 to 107 μg g−1. The accuracy of the method was evaluated by ICP 75
Various Pigments XRF; —; s Macro-XRF was used for mapping elemental distribution scanning large areas and quantitative analysis of the composition of small pigments. Results from XRF were interpreted using computerized tomography 67
Various (4) Playground structures pXRF; —; s Metals determination in public playground paints in South West England by field portable XRF. High levels of toxic metals (Cd, Cr, Pb and Sb) were measured. For instance, lead was detected above 10% dry wt, exceeding contemporary and historical standards 76
Various Tax stamps (for alcoholic beverages) and ink OES; LIBS; s Identification of false stamps with a new LIBS instrument based on a Q-switched Nd:YLF microchip laser and mini spectrometer containing a Czerny-Turner polychromator and sensor array covering 200 to 850 nm spectral range 77
Various (12) Textile fibres OES; MIP; l Determination of metals (Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Tl and Zn) in cotton, acrylic, polyester, nylon, viscose and polypropylene by MIP-OES after wet digestion 78



2.2.1 Organic chemicals. The analysis of organic samples by ICP has increased over the past years. A comprehensive review by Leclercq et al.79 covers the introduction of organic and hydro-organic matrices to inductively coupled plasmas. The review, which covers both ICP-OES and ICP-MS is comprehensive containing 478 references. Theoretical considerations are explored in the first part of the review including the effects of organic matrices on ICP techniques from aerosol generation to atomization; excitation and ionization process; special distribution of carbon species and analytes in plasma, and spectroscopic and non-spectroscopic carbon-related interferences. The second part of the review is focused on practical considerations for the analysis of organic matrices, optimization and analytical strategies for analyte quantification.

The importance of halogenated compounds is becoming more prevalent in different application fields. Wang et al.80 described a novel high-sensitivity elemental ionization source compatible with available mass spectrometers for quantitative detection of organo-halogens. A helium–oxygen plasma was used for atomization followed by negative ion formation in plasma afterglow. This configuration is known as plasma-assisted reaction chemical ionization (PARCI). The effect of oxygen in the ionization process was evaluated in order to understand and optimize the ion generation process. The authors claimed that the improvement of oxygen addition to helium plasma is due to electron transfer reagent ions and minimal interactions of organo-halogen breakdown products with the plasma wall tubes. The improved PARCI system described was coupled to a GC for quantitative determination at sub-picogram levels for fluorinated, chlorinated and brominated compounds.


2.2.2 Explosives. Brown et al.81 produced a review of methods for the detection and analysis of explosives that the reader may find interesting. The review evaluates important advances in explosives detection made over the past five years. The review is split in two sections; the first covering methods based on animals, chemicals, ions and mobility devices and the second summarizing methods based on photons from X-ray and gamma rays to neutrons.

The technique of LIBS continues to be applied to the detection of explosives. Consequently, several papers in this review period focused on fundamental studies of the processes occurring within LIBS plasmas in such applications. Standoff LIBS has been applied by Rao et al.317 to record the spectra of seven energetic molecules belonging to the family of nitroimidazoles. The authors exploited the use of femtosecond (fs) and nanosecond (ns) pulses in aim to gain understanding of the interaction of fs pulses with material surface, environmental conditions (air, argon) and pulse durations. A deeper understanding of fs and ns data correlating with molecular structure and surrounding environment is fundamental in the application of LIBS for the detection of explosives and harmful materials. The authors synthesized and characterized seven nitroimidazoles in the lab, prepared as pellets with a diameter of approx. 12 mm and weight between 600 to 800 mg with a thickness of 2–3 mm. The fs LIBS spectra were analyzed for understanding the behavior of molecular (CN, C2 and NH) and atomic (C, H, N and O) emission in air and argon atmospheres. The CN emission was found to be dominant for ablations in air and C2 emissions in argon. The authors used normalized intensities to improve the correlation between atomic emission intensities and the corresponding stoichiometric values. A good correlation coefficient was reported for all ratios in argon atmosphere. The studies of this research group suggested that the atomization/fragmentation ratio could be used as a detection capability of trace explosive molecules.

Rao et al.82 used also fs LIBS in a study of even explosive molecules of nitropyrazole in three different atmospheres: ambient air, nitrogen and argon. In order to understand the plasma dynamics, the decay times of molecular and atomic emissions in the different atmospheres were determined from the spectral data. The researchers investigated correlation between decay times and molecular emission intensities with respect to the number of nitro groups, atmospheric nitrogen content and the oxygen balance of the molecules.

In a different paper Serrano et al.83 presented a fundamental study on the formation routes of CH, NH and OH radicals in fs LIBS of molecular solids. In this work the author monitored time integrated optical emissions from fs laser produced plasma of isotopically labelled urea, terephthalic acid and anthracene, in pellet form. The different routes were identified by comparison of isotopic patterns. The NH emissions were mainly contributed from native bonding, when present. Atmospheric oxygen formed OH radicals with native H atoms from the molecules. This work may be another important step towards the use of molecular emissions arising from the LIBS of organic molecules as diagnostic tool. The authors reflected on further investigations to be carried out on the progress of these formation routes depending on the ablation regime (ultrashort and short laser pulses).

The application of laser induced breakdown spectrometry and selected ion flow tube mass spectrometry (SIFT-MS) for the analysis of gaseous and volatile components of the decomposition products of explosives and ballistic propellants was carried out by Civis et al.84 The surface of the samples was irradiated to simulate an explosion on a microscopic laboratory scale. The generated gas was analyzed in real time by SIFT-MS and the concentration of the generated products determined and statistically processed by PCA.


2.2.3 Pharmaceuticals. Legislation that regulates the elemental impurities levels in pharmaceutical samples is currently undergoing revision from limits based on elemental concentration in components of drug products to limits based on element specific permitted daily exposures. This initiative is likely to have significant implications for the workload of analytical laboratories going forward, potentially requiring the development of new methods to satisfy regulations. A survey published by Li et al.85 summarizes elemental impurities concentrations in common pharmaceutical excipients and some drug substances. Closed vessel digestion followed by ICP-MS determination was carried out in 205 samples. Discussion of some of the analytical challenges encountered and some potential solutions were also presented.

A simple and fast method for the determination of Cr in empty medicine capsules was presented by Goncalves et al.86 The procedure may be considered as an alternative to current USP determination of trace impurities in drug compounds and excipients based on ICP techniques. The authors used tungsten coil atomic emission spectrometry (WC-AES) and matrix decomposition directly on the tungsten atomizer. Tungsten filaments extracted from 150 W, 15 V microscope light bulbs were used as atomizer and excitation source for AE measurements. A Czerny–Turner spectrograph and a thermoelectrically-cooled CCD detector were part of the instrumental setup. The accuracy of the method was checked by ICP-OES determination. Sample preparation consisted on 10 min vortex of 0.4 g of sample with HNO3 and H2O2. Limits of detection reported were 0.4 μg g−1, linear dynamic range between 3–100 μg L−1 and precision (RSD) given in the range 5.2 to 7.4%. The authors claimed that the system was portable and may be applied in the field for fast determinations.

The use of portable instrumentation for biopharmaceutical products has been demonstrated in a paper by Mondia et al.87 The system was used to determine trace levels from 0.5 ppm V to 100 ppm Mo in different nutrient powders in cell culture media. A hand held XRF with a Rh X-ray tube and a silicon drift detector was used for the analysis. In order to overcome Bremsstrahlung continuum effects due to backscattered X-rays, a wavelet transformation with normalization to the Compton peak intensity was proposed, removing in this way high frequency noise from the spectrum. This is the first time wavelet transformation with spectral normalization is used in pharmaceutical samples for high accuracy results. The accuracy of the method was determined by comparison with ICP-MS data. For Cu and Zn results were within 20%. Challenges related to matrix effects were compensated by analyzing samples in a finely grained powder state and sealed samples under a dry environment to minimize errors associated with increased water content. L-Glutamine powdered reference standard spiked with different concentrations of the metal solutions were used for calibration of the instrument. Salbutamol sulfate is a bronchodilator belonging to one of the largest group of inhaled asthma drugs. Nejem et al.88 presented for the first time an indirect atomic absorption method for the determination of salbutamol with no interferences from excipients. The method is based on the oxidation of Fe(II) with unreacted bromine from the bromination reaction of the drug. The resulting Fe(III) was complexed with thiocyanate in the presence of sodium chloride. The remaining Fe(II) was aspirated into an air–acetylene flame and determined by AAS. The authors also reported the validation of a kinetic method for determination of salbutamol based on the bromination of the drug by bromine generated in situ by the interaction of bromate with bromide in acidic medium. The reaction was followed spectrophotometrically as the absorbance of bromine color at 380 nm decreased with the time. Reported LOD's were given as 0.30 and 0.012 μg mL−1 for kinetic and AAS methods respectively.

A novel method for the measurement of drug concentration in a metered-dose inhaler spray using X-ray fluorescence spectrometry was described by Duke et al.89 The methodology aimed to overcome existing problems with particle filtration or laser scattering being these techniques ineffective when measuring drug concentrations in the proximity of the nozzle spray. The proposed method is based on direct measurement of drug distribution using a focused X-ray beam to stimulate X-ray fluorescence from the bromine in a solution containing 85% HFA, 15% ethanol and 1% IPBr. The technique is not restricted to IPBr since any other drug that contains atoms with suitable fluorescence energy could be targeted.

The technique of LIBS was applied to the determination of carcinogenic fluorine in cigarettes by Gondal et al.90 A laser pulse (pulse duration of 8 ns and wavelength of 266 nm) and a time-gated intensified charged coupled device camera were used. Electron density of the plasma was calculated using Boltzmann plot. The LIBS signal intensity for F detection was optimized in terms of time delay between laser excitation and spectrum acquisition and optimum laser energy, being 720 ns and 17.54 mJ per pulse respectively the optimum values. Various brands of cigarettes were analyzed for fluoride determination being 371 ppm the maximum fluoride concentration present. Other elements such as Ba, Ca, Cu, Na, and Ni were also detected.


2.2.4 Cosmetics. Concerns about the safety of cosmetic products are increasing and several countries around the world specify different regulations for cosmetic materials. Toxic elements including As, Cd, Cr, Hg, Pb and Sb in cosmetic are banned as intentional ingredients. However, they may be present as impurities as contaminants in raw materials or as by-products of manufacturing processes.

A simple analytical method for the determination of trace elements in lipsticks by ICP-OES and GFAAS was developed by Batista et al.91 Lipstick samples, intended to be used by adults and children, were digested using a hot block and a mixture of nitric acid, hydrogen peroxide and Triton X-100. ICP-OES operational conditions were optimized using a fractional factorial design studying nine variables: integration time, emission lines, sample introduction flow rate, sample flow rate during the analysis, pump stabilization time, radio frequency applied, gas flow rates (auxiliary, nebulizer and cooling). As analytical signals were recorded sequentially in axial and radial viewings, desirability function optimisation was used by the authors to establish the best instrumental conditions for the analytes (Cd, Co, Cr, Cu, Ni and Pb). The Pb was determined by GFAAS due to difficulties arising from spectral interferences in the ICP-OES analysis.

An interesting paper by Kim et al.92 described a methodology for Cd, Hg and Pb determination in baby powder and the development of a cosmetic powder CRM using double ID ICP-MS. Mercury memory effects were minimized by using a fast valve sample introduction system. The method was fully validated. Certified values for Cd, Hg and Pb were (24.8 ± 13) mg kg−1, (0.648 ± 0.065) mg kg−1 and (24.55 ± 0.31) mg kg−1 respectively. The homogeneity and stability of the sample were also evaluated according to ISO Guide 35:2006. Long and short term stability were also evaluated. It is expected that the use of adequate CRM for testing of impurities in cosmetic samples will significantly improve the quality of the results. In a similar vein, Ng et al.93 described the work undertaken to prepare and characterize a cosmetic cream sample for the assignment of certified values. Exact matching IDMS and standard additions techniques were developed for As, Hg and Pb determination in a cosmetic cream sample provided by the National Institute of Metrology (NIM, China). Samples were digested with a mixture of HNO3, HF and H2O2 on microwave system. Homogeneity, short term and long term stability studies were carried out. The Hg and Pb were determined by high accuracy exact matching IDMS. The As content was estimated using the standard addition method by measuring the intensity ratio of arsenic to gallium (internal standard).

The analysis of sunscreen presents a challenge for classical elemental techniques because of the complex matrix of these materials being a semi-solid emulsion mixture of TiO2 or ZnO nanoparticles, oil and water. In an interesting paper, Bairi et al.94 presented a technique for the quantification of Ti and Zn in commercial sunscreen using portable XRF at ppm levels with no sample preparation. To eliminate Compton effects (caused by excess of light elements in the samples) and physical matrix effects, the authors used matrix matched working standards prepared with organic matrices similar to commercial sunscreens free from any metal oxides such as TiO2 and ZnO as dispersing media. Analysis of commercial samples containing various amounts of metal oxides was carried out using correction factors developed with the working standards. The presented method showed good linearity (r2 > 0.995) for Ti in the range of 0.4–14.23 wt% and zinc in the range 0.4–14.23 wt%. The concentrations obtained by the proposed method were confirmed and validated by microwave acid digestion followed by ICP-MS determination with correlation within ±25% deviation.

Menneveux et al.95 developed a method for direct determination of Ti in sunscreens using laser induced breakdown spectrometry. A thin film of cream applied on the surface of aluminum target was indirectly ablated. Indirect ablation was proposed by the authors to overcome low efficiency and moderate temperature of the plasma when ablating liquid or soft matter. The behavior of the different Ti lines was studied for the prediction of Ti concentration in terms of spectral line identification and classification as well as management of self-absorption effects, which are unavoidable at concentrations above 1.5%. The validation of the method was carried out by analysis of sample with known concentration of Ti (low and high content) and the titration content of four unknown samples was also determined.


2.2.5 Archaeological, cultural heritage and art objects. Advances in the field of mobile instrumentation applied to art and archaeology analysis include the development of a portable X-ray diffraction and X-ray fluorescence system based on energy dispersive detection in reflection geometry.96 This new system was proposed with the aim of overcoming the existing limitations that portable XRF and XRD instruments present such as the use of low-energy X-rays, long data acquisition times and relatively heavy weights for practical use. The authors developed two instruments based on ED XRD-XRF detection. The first one was only used for laboratory tests. In the second one an X-ray tube (Ag anode) and a Si drift detector were mounted on an automated goniometer. The system was constructed as an open-work platform allowing the analysis of object with complex geometries. A powdered quartz sample was used to evaluate the performance of the proposed EDXRD portable system. In order to test the XRF performance, two certified standard glasses NIST 610 and NIST 612 were analysed. Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, Pb, Th, Rb, Sr, Y, Zr, Nb and Mo were detected at 500 ppm level and the first instrument detected trace elements at 50 ppm because the distance between the detector and sample is smaller than in the second instrument. Sensitivity was improved by using filters. A model of fresco sample with known composition of calcite, quartz and hematite was also analyzed. Results showed identification of crystalline phases in shorter time (100–600 s) than so far reported. Other applications presented in this paper included the identification of minerals in stone objects (green minerals and obsidians) for provenance analysis of archaeological artifacts, pigments, inert materials in layers of paintings and analysis of bones and teeth for paleodiet studies.

A review article by Vandenabeele and Donais97 which includes 160 references summarizes recent studies on direct analysis of cultural heritage materials and archaeometry research using mobile instrumentation. Applications, advantages and disadvantages of the different analytical techniques were presented. It was observed that Raman spectroscopy, XRF, FTIR and LIBS were the most used techniques in the field. Other less common reported spectroscopic techniques as well as combined approaches were noted.

An interesting application of LIBS for in situ analysis to identify pigments from mural paintings was used by Syvilay et al.98 The authors presented a novel strategy to overcome the variations of LIBS signal. A standard normal variate (SNV) method was applied and evaluated in detail for the first time on LIBS spectra. Parameters studied included energy of laser, shot by shot and quantification. The aim of the method was to get a quick visualization of the different layers of a stratigraphic painting by simple data representations (2D and 3D) after SNV normalization.

In the field of cultural heritage objects analysis, XRF has become a very powerful tool. But one of the limitations is the presence of absorption effects between adjacent pigment layers which are manifested by artifacts that impede a proper identification of images. In an attempt to correct for interlayer absorption effects, Wrobel et al.99 exploited a method for interlayer absorption artifact correction applicable to polychromatic excitation. The authors presented an approach based on the zeroing of the correlation coefficient between fluorescence signals from the covering and the covered layers overcoming the disadvantage of existing methods in terms of parameters chosen empirically by judging the quality of the resulting image.

A paper by Tian et al.100 evaluated the ability of microfabricated glow discharge plasma (MFGDP) as ion source for mass spectrometry imaging technique for the study of calligraphy. The MFGDP was developed by the same authors in previous work as an ion source to absorb and ionize the sample. Operating conditions were optimised for the MFGDP (sample distance from plasma, speed, and sequence) and for the ion trap as mass spectrometer conditions (capillary temperature and voltage, tube lens and multipole). Handwritten samples containing 70 μg L−1 of urea were analyzed. Although resolution was 300 μm under optimum conditions, the proposed method could distinguish between different handwriting according to the “fingerprints” of chemical substances and obtain distribution of the different nutrients in the sample. The aim of the authors for the future is to improve resolution by obtaining a more uniform plasma plume.

2.3 Inorganic chemicals, catalysts and acids. The versatility of the atomic spectrometry techniques has been highlighted this year. Papers detailing a wide range of applications from the determination of antimony and bismuth in technogenic raw materials101 to the speciation of U and Pu at Chernobyl102 and the identification of natural inorganic pigments used on 18th century Korean mural paintings.103 A number of these have been described in the other applications subheading and for completeness collected in Tables 3 and 4. Papers with similar applications have been grouped into the following topics; forensics, catalysts, fertilizers and building materials.
Table 3 Application of atomic spectrometry for the characterisation of inorganic materials
Element Matrix Technique; presentation Comments Ref.
B Weapons grade BKNO3 OES; ICP; l Discriminating elemental B from oxidized B using a simple difference in solubility 138
Co Natural, blue coloured, spinel crystals MS; ICP; s LA-ICP-MS was used to determine the concentration of Co in spinel crystals of varying shades of blue 139
Cr Synthetic emeralds μXRF; —; s Laboratory capillary μXRF used to map the 3D spatial distribution of Cr in these beryl crystals at the μm scale 140
Fe Natural, blue coloured, spinel crystals MS; ICP; s See Co ref. 139 139
Various (7) Iron supplement tablets OES; ICP; l Sample preparation was performed by acid digestion (3 mL HNO3 and 1 mL H2O2, 30% v/v.) mg L−1 were Ca 0.52, K 0.14, Mg 0.03, Mn 0.07, Na 0.40, P 0.36, Zn 0.24 141
Various Sulphuric acid MS; ICP; l Isobaric interferences from sulphur species were eliminated by mixing aliquots of sulphuric acid with barium bromide, resulting in precipitation of insoluble sulphates 142
Various Europium, yttrium and lanthanum compounds OES; ICP; l Detailed procedure for the determination of 40 trace elements with LOD from 1 μg g−1 to 1 ng g−1 143
Various Cerium matrix OES; ICP; l Spectral interferences on 28 elements were studied and an optimised method for interference-free spectral line selection from a high Ce matrix was presented 144
Various Mortars from the S. Niccolò archaeological complex, Italy XRF; —; s The study of mortars using multiple analytical techniques (OM, XRD, SEM-EDS, XRF) allowed identification of 5 principal building phases 145


Table 4 Applications of atomic spectrometry to the characterisation of ancient mortars and plasters
Element Matrix Technique; presentation Comments Ref.
Various Mortar from the Cathedral of Paderborn (Germany) XRF; —; s S-XRF, XANES and XRD combined to characterise and differentiate mortars from different construction phases 318
Various Mortar from Herculaneum, Italy XRF; —; s 33 samples of mortar taken from floors across site. Combination of elemental data with TGA·DTG and Petrographic analysis highlighted foot traffic from visitors induced decay on mortar based floors at the site 146
Various Mortar from Kyme, Turkey XRF; —; s 14 samples analysed by OM, XRF, XRD, SEM-EDX and Raman. Study discovered a new type of plaster at the site which included vegetable matter fibres in the mix 147
Various Decorated plaster from Fatih Mosque, Turkey XRF; —; s Samples were milled and pressed prior to analysis. The chemical fingerprint, in combination with FTIR, was used to identify pigment compounds used. E.g. Strontium yellow (SiCrO4) and zinc white (ZnO) 148
Various Decorated earthen plaster from Ajanta caves, India XRF; —; s Characterisation of plaster material by XRF, XRD, CHN, FTIR and SEM and subsequent identification of material origins 149
Various Decorated plaster from Villa dei Quintili, Italy XRF; —; s Handheld XRF together with portable Raman spectrometer used to identify pigment components. Approach validated with laboratory analysis using OM and SEM-EDS 150
Various Mortars from the Garum Shop at Pompeii, Italy XRF; —; s Identification of mortars used during different construction phases and/or restoration work using a combination of XRF, XRD, SEM-EDS and optical image processing 151
Various Mortars from the S. Niccolò archaeological, complex, Italy XRF; —; s The study of mortars using multiple analytical techniques (OM, XRD, SEM-EDS, XRF) allowed identification of 5 principal building phases 145



2.3.1 Forensic applications. The application of atomic spectroscopy in forensic science continues to focus on the characterisation of gunshot residues (GSR). Yáñez and colleagues104 investigated the application of a new subcritical nebulizer with online preconcentration for improving the determination of Sn by AAS. Tin occurs in GSR by abrasion of the ammunition during firing and can provide additional chemical evidence to the typical analytes Sb, Pb and Ba. Subcritical nebulisation is a sample introduction system, in which pressurized liquid carbon dioxide is used. Sample was preconcentrated on HPLC-cartridges with the help of a peristaltic pump. Complex Sn-PDC was formed online following addition of ammonium pyrrolidinedithiocarbamate prior to elution using liquid carbon dioxide. The rapid vaporization of CO2 formed a dry aerosol of gaseous metal complexes which became atomized in the flame-heated Ni-tube atomizer attached to the spectrometers burner head. The detection and quantification limits obtained were 0.008 mg L−1 and 0.024 mg L−1, a 300-fold increase compared to a standard high sensitivity nebuliser set up.

Scanning Electron Microscopy with Energy Dispersive X-ray Spectrometry (SEM-EDX) continues to be the technique of choice for GSR analysis. Nonetheless, this does not discourage proposals for alternative means of analysis. Dias et al. reported the use of PIXE and μ-PIXE for the evaluation of the Sb/Pb, Ba/Pb and Sb/Ba elemental ratios found in large (50–150 μm) GSR particles, compared to those in the pristine primer.105 Experiments were carried out employing a 2.0 MeV, 1 mm2, proton beam for PIXE and a 2.2 MeV, 2 μm2, proton beam for μ-PIXE, on samples collected on microporous tape. Although the analytical procedure employed was successful, and the results showed ratios do not correlate with those from the primer, it is unclear what the benefits are of PIXE over standard SEM-EDX. The use of LIBS for the determination of Sb, Pb and Ba in GSR following liquid extraction from a cotton stub was presented.106 Extracted solutions were transferred on to a Teflon disk for analysis and results compared to those determined by ICP-OES. The obvious appeal of LIBS includes fast analysis and high selectivity and sensitivity, with LODs for this work calculated to be 0.1–18 mg L−1. However, for this application it appears to add superfluous complexity over an established ICP-OES methodology.

For the reader with a strong stomach, there is a paper discussing the preservation of GSR in decomposed flesh and bone from marine environments.107 The team used a combination of SEM-EDX and ICP-MS to determine the rate of GSR loss in specimens from submerged, intertidal and in supralittoral zone environments.


2.3.2 Catalyst applications. The development of methodologies for the determination of platinum group metals (PGM) in automotive catalyst convertors (ACC) has become a mainstay of the catalyst section. The high cost of these metals drives continuous improvements in accuracy and precision of relatively established techniques and methodologies. Morcali et al. report the optimisation of the nickel sulphide fire assay for the determination of Pd, Pt and Rh in a range of ACC types (gasoline, diesel and diesel particulate filters).108 The group investigated the effects of varying flux materials, ratios and reaction conditions on analyte recoveries. Both ICP-MS and FAAS were used for the analysis of the fire assay beads. Reference standard NIST SRM 2557 was used to assess efficiencies and optimum recovery (at least 99.0%) was achieved with reaction of 11.5 g of flux (0.53 w/w ratio, sodium tetraborate[thin space (1/6-em)]:[thin space (1/6-em)]sodium carbonate), 1 g nickel, and 0.84 g sulfur (1.2 w/w ratio, Ni[thin space (1/6-em)]:[thin space (1/6-em)]S) per gram of sample for 90 min at 975 °C. A detailed description (Chinese) of a HCl soaking procedure prior to fusion and a tellurium co-precipitation for the determination of Pt, Pd and Rh by ICP-MS was published by Li, Liu and Fang.109 The methodology, co-verified by eight laboratories, involves soaking in 6 mol L−1 HCl and recovery of insoluble material, followed by ashing at 700 °C and fusion with sodium peroxide. The resulting solution then followed a typical tellurium co-precipitation procedure prior to analysis by ICP-MS.

Both fire assay and chemical digestion of ACC are multistep, labour intensive procedures. A simpler approach, such as a pressed powder XRF method described by Verma et al. would have obvious benefits.110 High purity alumina (0.2 g) was mixed thoroughly with microcrystalline cellulose powder (0.8 g) in a ratio of 1[thin space (1/6-em)]:[thin space (1/6-em)]4 (w/w) in a Teflon dish. A known volume of Pt-standard solution was added to the above mixture (1 g), dried under an I.R. lamp and mixed thoroughly. Pellets were prepared using an automatic press at a pressure of 10 tons. Calibration was by means of bivariate least squares fitting, with weighted regression of the residuals. Results were found to correlate well with those obtained by independent NAA and ICP-OES analysis.

Polymer electrolyte membrane fuel cells (PEMFC's) have long been considered an attractive option for energy-conversion in both mobile and stationary systems. At the core of the technology is a platinum based catalyst used to overcome the high activation barrier of the oxygen reduction reaction (ORR). However, due to the high costs associated with platinum a non-precious metal alternative catalyst is considered essential technological breakthrough. An interesting paper describing the arrangement of a modified scanning fuel cell coupled to an inductively coupled plasma mass spectrometerfor the online study of Fe–N–C oxygen reduction reaction catalyst degradation was published.111 The eluent electrolyte stream from an SFC with a V-shaped channel and 5 mm opening at the bottom of the cell for contact with the working electrode was connected to the ICP-MS. Co internal standard was mixed into the stream using a simple Y piece connector prior to introduction to the ICP-MS. A cyclic voltammogram with 1 mV s−1 and a stepwise chronopotentiometry with a 0.1 V step size from 1.5 to 0 V were applied for the high and low potential study of catalyst dissolution with continuous monitoring of 57Fe. This method offered a greater understanding of electrochemical stability of the ORR catalyst than offline measurements, such as that described by Savadogo et al. for a titanium oxy-nitride ORR catalyst.112

The use of high-space resolution soft X-ray fluorescence microspectroscopy for the study of Mn/pyrrole based ORR catalysts, prepared by electrodeposition, was reported in a series of papers lead by Bozzini and Gianoncelli.113–115 Soft X-ray fluorescence elemental mapping and micro X-ray absorption spectroscopy (μ-XAS) was performed at the TwinMic beamline of Elettra synchrotron facility (Trieste, Italy). The photon beam was focused to a microprobe using zone plate optics, and the imaging measurements were performed by simultaneous detection of transmitted and emitted (fluorescence) photons raster-scanning the sample with respect to the microprobe. XRF and μ-XAS spectra showed that the compositional and chemical-state distribution of the as-deposited of Mn was consistent in a wide range of electrodeposition current densities, while a mixture of Mn valencies, with higher oxidation states prevailed at higher current densities.

Micro-focus X-ray fluorescence and X-ray diffraction computed tomography (μ-XRF-CT, μ-XRD-CT) in combination with X-ray absorption near-edge spectroscopy (XANES) was used determined the active state of a Mo-promoted Pt/C catalyst for the liquid-phase hydrogenation of nitrobenzene.116 The measurements, performed at the Diamond Light Source (Oxfordshire, UK), are believed to be the first in situ chemical-computerised tomography studies performed on heterogeneous catalytic systems under reaction conditions in the liquid phase. A single particle was mounted in a 0.4 mm OD borosilicate capillary using quartz wool together with 10 μL nitrobenzene (22.3 mmol) in ethanol. XANES data were recorded at the Pt L3 absorption edge at beamline I18 operating with a Si(111) double crystal monochromator and Ge solid-state detector. XRF-CT data were collected using an incident X-ray energy of 20[thin space (1/6-em)]300 eV and a spot size of 2 × 2 μm (FWHM). The sample was rastered across the beam in a translate-rotate data collection scheme, with spectra collected at 5 μm intervals and a collection time of 0.3 s per pixel. XRD-CT data was collected in the same manner as the XRF-CT but with a 13[thin space (1/6-em)]000 eV incident X-ray beam, and with a collection time of 2.0 s per image. Experiments showed that the active state of the Pt was discovered to be reduced, non-crystalline, and evenly dispersed across the support surface. CT images of the Pt and Mo distribution revealed they were highly stable on the support and not prone to leaching during the reaction.

Micro-focus X-ray fluorescence computed tomography was also utilised to investigate metal poison deposition on industrially deactivated fluid catalytic cracking (FFC) catalysts.117 Single particle measurements were performed using the P06 beamline at the PETRA III synchrotron, (Hamburg, Germany). A monochromatic X-ray beam of 10.0 keV was focused to a 0.5 × 0.5 μm spot using KB-mirror optics. Multi-element 3D imaging, at submicron resolution was achieved by using a large-array Maia fluorescence detector. Results showed that significant concentrations of Fe, Ni and Ca we present in highly localised areas of the catalyst particles. Concentrations were seen to increase with catalyst life time. However, the deposition profiles did not change significantly.


2.3.3 Fertilizers. The previous year's spike in publications concerning has not continued into the current review period. There were still, however, a couple of noteworthy publications.

The determination of mercury can be notoriously difficult due to a combination of volatility during digestion and adsorption to container walls. Therefore, a simple, fast and precise, solid sampling analysis employing HR-CS GF AAS presented by Araujo et al. is obviously of interest.118 Samples were weighed directly onto a graphite platform, together with 100 μg KMnO4 chemical modifier, and inserted into a transversely-heated graphite tube specific for solid sampling. This was purged with argon and heated to 1300 °C. A simple external calibration method using commercially available stock solutions was utilised and a 4.8 ng g−1 LOQ was achieved. The accuracy of the proposed methods was confirmed by the analysis of standard reference material (SRM) of Trace Elements in Multi-Nutrient Fertilizer (SRM NIST 695).

The development of a quantitative method for the determination of phosphorous concentration in organic and inorganic fertilizers using a low cost, portable LIBS system was published.119 Spectra was collected for 26 samples, of varying composition, following preparation by means of grinding, sieving (100 mesh) and pressing into pellets at 6 × 108 N m−2 for 30 s. For each pellet, 100 spectra were collected from different positions on the sample. This was then subjected to a number of correction procedures including outlier removal, baseline correction and peak normalisation before being referenced with results obtained by ICP-OES following digestion with nitric and hydrochloric acid. Correlation between LIBS and ICP-OES was found to be R = 0.95, with an average error of 15%. Whilst this work continues to show the versatility of LIBS systems, it is difficult to envisage its use on an industrial basis for this application, particularly as ED-XRF systems become more portable and cost effective.


2.3.4 Building materials. Several papers have detailed the application of atomic spectroscopy techniques as part of multi-technique characterisation of ancient mortars and plasters. Predictably, XRF featured significantly due to its capability of minimally destructive analysis where sample quantities are limited. Although the majority of papers focus on the objects analysed, rather than development of the technique, for completeness they have been included in a separate Table 4.

Typically, XRF is the technique of choice for the bulk elemental characterisation of cements, concretes and other building materials, and it comes as no surprise that it features heavily during the review period. Applications include investigations for alternative additive and aggregates, such as steel slags and sludges,120 calcined lime sludge and silica121,122 tungsten tailing powders,123 and pumice additives in fired clay bricks.124 An interesting paper describing the development of an online XRF system for the analysis of cement raw meal was published by Jia and colleagues.125 The spectrometer was mounted on a sled, which smoothed the surface of the raw meal passing on the conveyor, thus reducing surface roughness. The system also featured a laser rangefinder to accurately measure the distance between sample and spectrometer and allowing sample path correction. The continuous determination of Ca, Cr, Fe, Pb, S and Ti was achieved with LOD's of 246, 33, 37, 47, 118 and 44 mg kg−1, respectively. By comparison with results by ICP-MS and CHNS/O combustion elemental analysis accuracy was determined to be within 12% for all elements.

The powerful combination of simultaneous multi-element analysis and a high spatial resolution of LIBS was utilised for the investigation of chloride ingress in cracked reinforced concrete.126 Identical concrete specimens were prepared and subjected to wedge splitting to induce mechanical cracks of varying width, which were subsequently wetted with NaCl solution on a weekly cycle for 36 weeks. These were cut longitudinally to the crack and placed on a translation stage perpendicular to the LIBS laser. Excitation was by means of a pulsed 1064 nm Nd:YAG laser, with 400 mJ pulses focused to 1 mm spot size and the Cl 837.6 nm emission line used for analysis. It was found that chloride ingress was affected by crack size, aggregate material and location to the concrete/rebar interface. The advantages of LIBS for concrete degradation analysis was also reviewed by Millar et al. (German).127 Again, the spatial resolution and multi-element capability were highlighted as key advantages over the conventional means of assessing contaminants contributing to the alkali–silica reaction, chloride corrosion and carbonation. A further application of LIBS was also reported detailing determination of the chemical composition of cement powders prepared by pressed pellet.128 The paper covers the design of the spectrometer, calibration and sample measurements. The accuracy and precision of results compare well with the reference analysis, XRF. However, it is in the opinion of the author that looking to replace established techniques is not playing to the strengths of LIBS, as there is no clear benefit to outweigh the added complexities.


2.3.5 Other inorganic applications. This year saw slight decrease in the volume of papers utilising LIBS. However, the versatility and breadth of application was highlighted by two papers. The first discussed an interesting, and practical, application of LIBS for the identification of contaminants found during laser cleaning of the thermal barrier coatings of turbine blades.129 During operation, surface contamination composed of calcium, magnesium, alumina, and silicates can build up on the coatings of turbine blades, which if untreated can lead to failure. Laser ablation has been demonstrated to be an effective means of removing these deposits and the addition of a spectrometer to determine the composition was a logical addition. At the other end of the spectrum, LIBS was used to determine As and Hg in the Chinese medicine An-Gong-Niu-Huang Wan.130 Blended samples were simply pressed into pellets and measured directly. Results compared well with those determined by a standard ICP-OES technique, which was significantly more time consuming. Finally, readers with an interest in the theoretical modelling and calibration of LIBS are directed to a paper by Aragón and Aguilera containing an in-depth discussion of the refinement of the curve-of-growth methodology to account for inhomogeneous plasma characteristics.131

The determination of trace contaminants in high purity materials, for use in the industries such as electronics, is critical as they can have a significant impact on their performance. The determination of Cd, Pb, and Zn in high purity tantalum pentaoxide, used in capacitors, was achieved by in situ matrix removal and ETV-ICP-MS.132 A PTFE slurry was used as a chemical modifier in ETV for converting both the tantalum and analyte elements into their fluorides, enhancing the difference in volatility between them. As a result, the tantalum matrix was removed in situ, as a more volatile TaF5, without signal loss of the analytes due to the formation of their fluorides with good thermal stability. Under optimum conditions, LODs for Cd, Pb, and Zn were 1.4, 3.2, and 6.8 ng g−1 with RSDs <6.0%. Wu and colleagues published a method for the determination of REE in neodymium oxide by ICP-QQQ-MS.133 Under optimum conditions LODs of, 40, 4 and 22 ng L−1 was achieved for Dy, Ho and Tb respectively. Spike recoveries of 0.5 μg L−1 of 14 REE were 88.6–98.6% and RSDs for 2 h signal stability of 1.3–4.1% were obtained using a high matrix introduction technique. Petrova et al. reported a procedure for the indirect determination of Cl in bismuth and bismuth oxide by FAAS.134 The solid samples were dissolved in 7 M nitric acid before a known concentration of Ag was added. Any chloride present in the material was precipitated as AgCl and removed the centrifuging at 1000 rpm for 10 min. Analysis of the remaining Ag in solution allowed calculation of Cl concentration by difference. The technique successfully recovered a range of spiked concentrations and a 10 μg g−1 LOD was achieved.

The accurate determination of Sr isotope ratios is important for a range of applications including geochronological dating and provenance of products of plant and animal origin. The ratio varies due to the radiogenic nature of the 87Sr isotope, however, analysis of this can be challenging in the presence of 87Rb. Vanhaecke and colleagues proposed a ICP-QQQ-MS method for accurate Sr isotopic analysis without prior Rb/Sr separation.135 The isobaric overlap at 87 m/c was avoided by the use of 10% CH3F in He as a reaction gas, monitoring SrF+ reaction product ions instead of Sr+ ions, whilst Rb shows no reactivity towards CH3F. The double mass selection capability of the triple quadrupole instrument prevented both spectral overlap from atomic ions at the SrF+ reaction product ions and a measurable effect from the matrix on the 87Sr/86Sr result. Vanadium isotope ratios were measured at high precision using medium resolution MC-ICP-MS protocol.136 Unlike previous low-resolution methods, the use of medium mass resolution permits separation of V isotopes from all interfering molecular species representing combinations of C, N, O, S, Cl, and Ar. The separation of interfering molecular species from the V mass spectrum reduced the reduced the sample mass requirement by approximately 90%, compared to previous methods. A combination of MC-ICP-MS and TIMS was used by Wang and colleagues to determine the absolute isotopic composition accurate atomic mass of Yb.137 The work also yielded a new ytterbium isotopic certified reference material in nitric acid solution GBW04623.

3. Functional materials

3.1 Nuclear materials. The analysis of nuclear materials has again been dominated by standoff techniques such as LIBS to minimise the workers' exposure to radiation. This is especially true for the analysis of reactor components. During this review period, there has also been a large number of papers reporting the results of inter-laboratory comparison exercises or the development of certified reference materials.
3.1.1 Reviews, inter-laboratory comparisons and certified reference materials. A number of reviews covering different aspects of the analysis of nuclear materials have been published in this review period. Two reviews/overviews covered nuclear forensics or safeguards. One entitled “nuclear forensics: what, why and how?”,152 containing 73 references, discussed how the aim of this type of work is to determine the origin of the material and to identify when it was last chemically processed or purified (i.e. its age) so that nuclear proliferation can be deterred. A wide range of techniques may be used for this purpose and a discussion was presented of how gamma spectroscopy, mass spectrometry (multi-collector ICP-MS, TIMS, etc.), Raman spectroscopy, FTIR, SEM, TEM and LIBS may be employed to ensure that maximum information is obtained. A combination of these techniques enables both structure, morphology, isotopic composition of the main component and the level of impurities to be determined. Also discussed, albeit briefly, were inter-laboratory comparisons and an outlook to the future. The other review,153 containing 146 references, was more specialised and assessed “mass spectrometric analysis for nuclear safeguards”. This review covered the application of SIMS, TIMS and ICP-MS. Each of these techniques was discussed in detail, giving examples of their use for the analysis of nuclear materials as well as environmental samples. Different measurement strategies and modifications of each technique, methods of overcoming interferences and relative advantages were all discussed. The review also contained a substantial section covering current challenges, relevant certified materials and potential improvements.

One review highlighted that, because of a paucity of relevant CRMs, ensuring valid analytical measurements of nuclear materials and of isotope analysis can be problematic.154 Experimental approaches envisaged at the European Commission Joint Research Centre – Institute for transuranium elements were assessed for overcoming this problem. Amongst the techniques discussed were alpha- and gamma-spectrometry, SF-ICP-MS and high resolution ICP-OES. In another review, containing 122 references, the state of the art in the determination of 135Cs and 137Cs in environmental samples was described.155 The origins of these isotopes, i.e. weapons testing, nuclear re-processing, nuclear fuel cycle discharges and accidents and the different techniques available for the measurements were discussed. Although ICP-MS was the focus of the review article, RIMS, TIMS, AMS and NAA were all considered. For all of the mass spectrometric methods, the separation of the analytes from the matrix and concomitant elements is required to ensure that no interferences (such as isobaric interferences from 135Ba and 137Ba) occur. Methods for the elimination of such interferences including acid digestion methods followed by ion exchange chromatographic separation, chemical separation using ammonium molybdophosphate or insoluble hexacyanoferrates or extraction chromatography were assessed. The utility of ICP-MS using a reaction cell was also considered.

Several papers concerning the development of certified reference materials have also been published including one describing the production of a highly enriched 134Ba material for use as a CRM for ID-MS measurements.156 This approach was proposed to help quantify 137Ba so that accurate age measurements using 137Cs/137Ba can be made. The processes used to prepare, separate and isolate the isotope were all given. The characterization for isotope amount ratios of three materials: CRM 112 A (uranium (normal) metal assay and isotopic standard); CRM 115 (uranium (depleted) metal assay and isotopic standard) and CRM 125 A (uranium (UO2) pellet assay, isotopic and radiochemical standard) has also been reported.157 Three different TIMS approaches were employed, including a) the total evaporation technique (measurement of major isotope ratio amounts), (b) the modified total evaporation technique (measurement of major and minor isotope ratio amounts) and (c) a conventional TIMS method was used for measuring the minor isotope ratio amounts. The uncertainty values for the measurements were calculated using the combined TIMS data sets and using the ISO guide to the expression of uncertainty in measurements. A similar approach was taken during the development of the materials IRMM-019 to IRMM-29.158 These materials are a series of uranium hexafluorides that were certified for their isotopic composition using the modified total evaporation process for TIMS. Some materials had the major isotope amount ratios (235U/238U) measured using a 233U/236U double spike. The measurements were confirmed by UF6 gas source mass spectrometry. The major isotope ratio amounts were determined with an uncertainty ranging (k = 2) from 0.015–0.03%, whereas the minor isotope ratio amounts (234U/238U and 236U/238U) had uncertainties of 0.02–3%.

Other papers to report the preparation of reference materials include one that described the synthesis of potassium plutonium sulfate159 and another that used natural apatite crystals as a potential U reference material for fission track dating by LA-ICP-MS.160 In the former paper, the material was envisaged for use analysing plutonium-based fuel samples and associated materials. Phase characterization was achieved using XRD, with the structure found to be monoclinic in nature with a space group of P21/c. A total of 26 trace impurities were determined in the material using ICP-OES and DC arc-OES. In the latter paper,160 the homogeneity of the crystals was determined using several techniques including EPMA (for the major element concentrations) whereas LA-ICP-MS and ID-ICP-MS were used for the U isotopic ratios. The ID-ICP-MS results were obtained following random selection of fragments of between 28 and 100 μg from the crystal followed by acid dissolution and spiking of enriched 235U, 230Th and 149Sm. Accuracy was ensured through the analysis of the NIST SRM 612 glass. The two crystals, labelled ‘Durango crystal’ and ‘Mud Tank crystal’ each had a volume of 1 cm3 and had a U content and of 7.5 μg g−1 ± 1.5% and 6.9 μg g−1 ± 1.4%, respectively; indicating good homogeneity. The LA-ICP-MS results were found to be less precise, but a relative precision of better than 4% was still achieved. It was concluded that the crystals were sufficiently homogeneous for use. Finally, the preparation of a multi-isotope Pu AMS standard and the preliminary results of a first inter-laboratory comparison have been reported.161 The material was made from dissolution of individual isotopes of 239Pu (IRMM-081a), 240Pu (IRMM-083), 242Pu (IRMM-043) and 244Pu (IRMM-042a) and then together forming a stock solution of composition approximately 1[thin space (1/6-em)]:[thin space (1/6-em)]1[thin space (1/6-em)]:[thin space (1/6-em)]1[thin space (1/6-em)]:[thin space (1/6-em)]0.1. The stock was used to prepare samples that were then sent to several laboratories for analysis using AMS. Results were observed to be in good agreement between laboratories and were also in agreement with the gravimetrically determined nominal values.

Several high purity 233U materials that were potentially useful as ID standards for safeguards and nuclear forensics applications were rescued from downblending.162 The materials were analysed for the U isotope amount ratios (233U/238U, 234U/238U, 235U/238U and 236U/238U) using total evaporation-TIMS. Standard quadrupole-based ICP-MS was used for extra verification. The results obtained from the two techniques were in good agreement, although the TIMS data obviously had better precision. However, the authors stated that the data from the ICP-MS instrument were of sufficiently good precision for initial screening of the purity of items during the rescue campaign.


3.1.2 Nuclear fuels. The use of X-ray fluorescence spectrometry for the analysis of nuclear fuels continues to be the subject of research. In one such study, the compositional analysis of mixed uranium–thorium oxide powders, microspheres and pellets was undertaken using TXRF.163 No dissolution was required. Instead, the sample supports were gently rubbed on the sample and this led to sufficient sample transfer to the support for the analysis to be undertaken. An alternative approach was to make a very dilute slurry of sample and then place an aliquot of this on the support. Drying this led to a thin film of sample that was also sufficient for analysis and that minimised matrix effects. The determination of U in samples where it was present at major and trace component levels were made using Th as an internal standard. The average relative precision achieved using the method was 2.6% and the U concentrations determined experimentally deviated by no more than 5% from expected values. As an extra validation step, the TXRF data were compared with those obtained using biamperometry, and good agreement was achieved. A further paper reported on the use of XRF in the determination of Pu in spent nuclear fuel.164 A modification of monochromatic WDXRF, referred to as hiRX (high resolution X-ray) was described. Spiked surrogate spent fuels were used as calibration standards and the method was applied to actual spent fuel samples, where as little as 39 ng of Pu could be detected. The precision of the method was good (2% RSD), but accuracy was variable, with values ranging from 4–27% from expected values. The LOD for Pu when using an excitation spot of 200 μm and a time of 100 s was 375 pg. The authors highlighted the speed, non-destructive nature and improved sensitivity of the method.

Finally, the application of a high resolution ICP-OES method to the determination of Pu in samples originating from the nuclear fuel cycle has been described.165 The exceptionally line-rich concomitant elements such as Am, Np, Th and U can complicate the emission spectrum and consequently much of the study focused on identifying Pu wavelengths that were not interfered with. Forty-three wavelengths were identified of which the most prominent 27 were investigated with respect to their SBR, slope (counts per mg kg−1) and line width. Use of a desolvating nebuliser was observed to improve the LOD by an order of magnitude compared with previous studies. The LOD for the most sensitive lines were reported as 2.3, 3.1 and 3.2 μg L−1 for 299.649, 299.409 and 297.251 nm, respectively. Precision using external calibration for samples containing approximately 0.45 mg kg−1 was typically better than 2%. Accuracy was ensured by using standard additions calibration and also by verification using a SF-ICP-MS instrument.


3.1.3 Nuclear forensics and safeguards. Nuclear forensics, safeguards and the analysis of environmental particles has been one of the most popular areas of research during this review period. Two review papers relevant to this section were published.152,153 These were discussed previously, in Section 3.1.1.

Automated screening of individual uranium particles was undertaken using TIMS.166 An automated particle measurement screening software that had previously been designed to work with SIMS instrumentation was utilised. The problem with SIMS analysis is that hydride-based polyatomic interferences can be problematic. The authors therefore coupled their screening methodology with TIMS, which eliminated these interferences. Consequently, those samples that gave dubious ratios when 234U and 236U were determined using SIMS, gave more accurate and precise measurements when using TIMS.

The age of individual uranium–plutonium particles with varying U/Pu ratios (1–70) were determined using ICP-MS.167 The micron-sized particles were prepared from U and Pu certified materials where the Pu material was known to have last been purified on July 14th 2008. The authors determined the purification age experimentally using 241Am/241Pu using high resolution ICP-MS equipped with a desolvation system to ensure that hydride-based interferences were minimised. After dissolution of the particles, picogram to femtogram levels of Am, Pu and U were separated using a small anion exchange column. The 241Am/241Pu were determined accurately by spiking pure 243Am into the sample solution. The experimentally derived ages were in good agreement with the expected age, with the difference being only 0.27 years. Another paper described the isotopic analysis of individual particles using single particle ICP-MS for nuclear safeguards purposes.168 In this study, erbium oxide powder dispersed in water was used as a surrogate for uranium particles. To correct for mass bias, Er solution was run before and after particle analysis. Two data processing strategies were adopted to calculate the erbium isotope ratios. One was point by point (PBP) and the other was linear regression slope (LRS). Precision for 170Er/166Er, 168Er/166Er and 167Er/166Er determined using PBP were 5.5, 4.6 and 3.9%, respectively, improving to between 0.2–4% once mass bias had been corrected for. The same precision measurements obtained using LRS were better by at least an order of magnitude, with a value of 0.3% being typical. In addition, the 162Er/166Er could also be determined, which was impossible using PBP. According to the authors, the method enabled fast screening, had sensitive detection, enabled isotopic identification, employed a simple sample preparation thereby reducing contamination and was applicable to particles over a large size range.

The use of SIMS in application to nuclear safeguards work is relatively common. The challenge in this analysis, especially when measuring the minor isotopes 234U and 236U, is the counting statistics because of the extremely low level of U present, typically 1 pg. Thus an approach based on multiple ion counting strategies for SIMS has been described in which several different instrumental configurations were compared.169 These configurations included static multi-collector, dynamic multi-collector and single collector using peak jump analysis. The precisions of the isotope ratios were measured on CRM U010 and CRM U100 for all of the configurations. The ratios and precisions for each were observed to be similar. However, the authors identified several fundamental properties of each system that affect the overall uncertainty including detector drift and aging effects.

The spatio-temporal evolution of U emission from laser induced plasmas has been studied.170 Analytes such as Pu produce very crowded spectra and when combined with line broadening phenomena induced by ambient atmospheric operation may cause problems in achieving sufficient spectral resolution may be encountered. It was reported that the effects were observed from changes in atmospheric pressure on U line intensities, SBR and linewidths in a plasma induced by a Nd:YAG laser with 6 ns pulses. Linewidths increased with increasing pressure because of Stark broadening. However, the extent of the broadening observed for U was significantly less than for other analytes such as Ca. The presence of an inert gas decreased the persistence of U in the plasma.


3.1.4 Analysis of nuclear reactor components. The literature concerning characterisation of nuclear reactor components has been dominated by reports describing the applications of laser induced breakdown spectrometry. The analysis of ITER-like walls was investigated in a number of studies. One such paper presented a comparison of data obtained for the elemental depth-profiling of the wall using LIBS with those achieved using SIMS.171 Good agreement was obtained between these techniques in this application. In addition, deuterium (D) was successfully distinguished from hydrogen (1H) by using a bundle of 50 optical emission collection fibres rather than one and by increasing the measurement delay. The LIBS derived data for D and deposited Be were also in agreement with the results found using SIMS, with the top part of tile 1 and the bottom part of tile 3 containing the largest amounts. A schematic diagram of the experimental setup was provided in the paper. In a second report, a double pulse from a Nd:YAG laser (schematic diagram of the setup provided) was used to determine the tritium (3H) content.172 In addition, three other analytes were also determined (Al, Ca and W). It was observed that the double pulse setup generated improvements in sensitivity of between two- and five-fold compared with use of a single pulse arrangement. The operating procedure was optimised and the inter-pulse delay was tested over the range 20 ns to 80 ms. A delay of 300 ns was subsequently used for the analysis. Results obtained using LIBS were in good agreement with those obtained from XRF that were derived post-mortem. The effects of a magnetic field on the LIBS signal obtained when analysing ITER-like deposits was the subject of another study.173 A significant enhancement in spectral emission was observed and greater penetration depth were obtained in the presence of a magnetic field. This was attributed to greater confinement of the plasma by the magnetic field leading to higher electron impact excitation. The LIBS measurements made in the laboratory and from the TEXTOR tokamak were in good agreement when similar conditions were used. Unsurprisingly, the authors noted that signal enhancement could be problematic when the sample was measured quantitatively in situ if standardisation was not conducted in the presence of a magnetic field.

A further application of LIBS to the in situ and the post mortem analysis of tungsten coatings exposed to Magnum PSI ELM-like plasmas has been described.174 Similar results were obtained. The surface morphology of the materials was also analysed using SEM and XRD. A paper by the same research group studied the erosion/deposition processes at the first walls of fusion reactors.175 Depth-profiling of elemental concentrations were determined and quantification was achieved using a novel data processing method. Results found compared well with those obtained using SIMS. Deuterium retention and the co-deposition of fuel with lithium on divertor tiles of the Experimental Advanced Superconducting Tokamak (EAST) was also studied using LIBS in a proof of concept study.176 Depth profiling between 0.5 and 4 μm was undertaken for the D and then the D/H ratio in the lithium-deuterium co-deposition layer was measured giving a value of 0.17 ± 0.02. Other applications of LIBS that have appeared under the year under review included the determination of Y and six REE (Eu, Gd, La, Nd, Pr and Sm) in graphite matrix pellets177 and the detection of C, Mo and Si in plasma facing materials of a fusion device.178 The latter study investigated the influence of laser spot size and laser energy on the intensity of emission for the analytes. Intensity was found to increase and then decrease towards the edge of the plasma, with a maximum intensity reached 1.5 mm from the centre.


3.1.5 Other nuclear applications. The ID-AMS determination of actinides in fluoride matrices has been investigated.179,180 The 239Pu, 240Pu and 241Am were separated from the sample matrix using an extraction chromatography column with N,N,N′,N′-tetra-n-octyldiglycolamide active groups. Analytes were extracted from the environmental samples using acid digestion and then separated from concomitant ions using the column. The full method was discussed in the paper. The final stage was to precipitate the Am and Pu using HF and 6 mg of Nd. The precipitate was washed, dried, ground, mixed with PbF2 (1[thin space (1/6-em)]:[thin space (1/6-em)]7) and then loaded into the instrument for measurement. Method validation was obtained through analysis of the reference materials IAEA 384 (Fangataufa Lagoon sediment) and IAEA 385 (Irish Sea sediment)179 or IAEA 414 (mixed fish).180

An interesting study reported the capillary electrophoresis separation coupled with SF-ICP-MS detection of various redox states of Fe (FeII and FeIII), Np (NpIV, NpV and NpVI) and Pu (PuIII, PuIV, PuV and PuVI), albeit, not simultaneously.181 The LODs reported were 10−12 M for Np and Pu, but was less impressive for the Fe (10−8 M). Separation was achieved using an acetate-based electrolyte for the Np and Pu, whereas the Fe required the addition of both EDTA and phenanthroline to separate the species. Separations for the Np and Pu species took approximately 700 s, whereas the Fe species were separated in less than 300 s. The separations were applied to the analysis of waste repository samples.

Atomic spectrometry has been used to determine the half-life of 234U.182 The accumulation of the daughter product 230Th was measured using ICP-MS and then the 234U decay constant and half-life calculated based on the 230Th/234U amount ratio. The half-life was calculated to be 244[thin space (1/6-em)]900 ± 670 years, which was in good agreement with previously reported results. According to the authors, the advantage of this methodology was that it does not require the assumption of secular equilibrium between 234U and 238U. It may also be applied to the measurement of half-lives of other long-lived radionuclides.

The determination of the relative abundances of isotopes in purified materials has been described.183 A linear accelerator was used to prepare 82Sr (and other isotopes) by irradiating a rubidium chloride target. Purification of the Sr was achieved using ion exchange chromatography. The total Sr was determined in two ways: ICP-OES and also the summation between gamma spectroscopy and ICP-MS. Agreement between the methods was reported to be within 10%. The summation method was also used to determine 82Sr (10–20.7%), 83Sr (0–0.05%), 84Sr (35–48.5%), 85Sr (16–25%), 86Sr (12.5–23%), 87Sr (0%) and 88Sr (0–10%). A method to measure 82Sr using ICP-OES was developed and validated according to regulatory guidelines. The proposed method was more rapid and simple than using the summation method.

The determination of Pu using TIMS has been the subject of investigation in two studies. In one, the PuIV was retained on superparamagnetic magnetite (Fe3O4) nanoparticles that had been made into a bead encased in a silica coating and that had been given quaternary ammonium functional groups.184 The preparation of the material was described in detail. This material was more selective for PuIV than the anion exchange resins that had been used previously and, because of its magnetic properties, was also easier to retrieve from large volumes of sample. Much of the paper was devoted to the preparation and characterisation of the materials. However, dissolver solution, soil leach liquors and spiked nitric acid were used as samples and the results obtained from the method developed were comparable to those from ID-TIMS. Similarly, analysis of the material NIST SRM 947 Pu isotopic standard using this method and solution analysis TIMS also yielded comparable results. A continuous heating TIMS method for the analysis of Pu isotopes was described in another paper.185 The effect of the heating rate of the evaporation filament on the analysis of Pu ranging from 0.1–1000 fg was tested, with results indicating that effects were minimal over the range 100–250 mA min−1. Assorted isotope ratios (238Pu/239Pu, 240Pu/239Pu, 241Pu/239Pu and 242Pu/239Pu) were measured in as little as 70 fg of SRM 947. The 240Pu/239Pu could be determined in 0.1 fg, which corresponds to a plutonium oxide particle size of 0.2 μm. The 239Pu could be detected with a sample amount of 0.03 fg, corresponding to a LOD of 0.006 fg. The differences in evaporation temperatures between 238Pu and 238U as well as 241Am and 241Pu enabled a clear distinction between them, meaning that a chemical separation was not necessary.

The determination of Al, Cr, F, Fe, Ni, Sr and Th in nuclear waste glass using LIBS was reported.186 The LIBS system comprised a Nd:YAG laser operating at 532 nm with a 6 ns pulse duration, a collimator to collect the light emitted and a spectrometer capable of separating wavelengths between 200 and 975 nm and an intensified CCD detector. Optimization of the number of laser shots, laser energy and acquisition time delay was undertaken. A multivariate partial least squares regression calibration approach was adopted that used spectral truncation to minimise problems caused by the complex emission spectrum from the sample. Standard error of prediction (SEP) values were used as figures of merit for the calibration. The average accuracy and precision were found to be 3–8% and 5–10%, respectively, for the analytes measured.

3.2 Ceramics and refractories. As discussed in previous reviews in this series, ceramics are designed to be thermally and chemically rather inert. It is therefore exceptionally difficult to digest them so that they may be analysed using liquid-based atomic spectrometric sampling techniques. Consequently, the trend towards the use of solid sampling approaches has continued in the year under review. Only a modest number of papers were published concerning analytical advances in relation to the characterisation of industrial ceramics. Significantly greater attention continues to be paid to the study of historical ceramics.
3.2.1 Industrial ceramics. Silicon carbide nanocrystals were analysed using high resolution continuum source graphite furnace atomic absorption spectrometry (HR-CS-GFAAS).187 Samples, were analysed for Al, as an impurity, and Si as the main constituent. The samples (ranging in size from 1 to 8 nm) were introduced as aqueous suspensions and calibration was against external aqueous standards. The optimal results for Si were achieved using the mixed modifier 5 μg Pd and 5 μg Mg, whereas for Al, the optimum was 10 μg of Mg only. However, the use of no modifier enabled ash temperatures of 1200 °C for Si and 1300 °C for Al and the compromise atomize temperature of 2400 °C for both analytes. The upper limit of the calibration range was 0.25 mg L−1 for Al and 2 mg L−1 for Si, indicating that significant dilution of the suspensions was required. The LODs were 0.5 and 3 μg L−1 for Al and Si, respectively.

Electrothermal vaporization (ETV)-ICP-MS was employed for the determination of analytes with different volatility in high purity zirconium dioxide by Chen et al.188 A PTFE slurry was used as a chemical modifier which served to vaporize the matrix more easily but also resulted in the analytes having similar vaporization behaviour. Under optimal conditions, the LOD were 3.4, 2.5 and 9.8 ng g−1 for Cd, Cr and Cu, respectively. Precision was reported as better than 6.2% relative and the linear calibration range spanned three orders of magnitude.


3.2.2 Historical ceramics. Like forensic samples, historic artefacts are precious in that they can provide significant amounts of contextual information beyond that of their composition alone. Consequently, their destruction should be avoided if at all possible. This means that solid sampling techniques that cause minimal damage, e.g. LA, LIBS and varying forms of XRF are usually used. Those papers that also utilize chemometric analysis of the analytical data to elucidate provenance, trade routes etc., are also discussed below. The majority of these types of papers are in archaeological-based journals and so sometimes the analytical science can be lacking in detail. Consequently, a summary of such applications are included in the accompanying table (Table 5).
Table 5 Applications of atomic spectrometry to the analysis of historical ceramics
Analyte Sample matrix Technique; atomization; presentation Comments Reference
Various Roman lead glazed pottery from Pompeii and Herculaneum MS; LA-ICP; s Multi-analytical approach taken. Optical microscopy, SEM, and μ-Raman spectroscopy also used. Two types of paste identified, but chemometric tests supported the hypothesis of one provenance (Campanian). All glazes were lead oxide plus quartz with sodium or potassium feldspars as flux as well as either Cu or Fe 191
Various Blue and white porcelain from Jingdezhen MS; LA-ICP; s Pottery sub-divided between three periods – early, middle and late Ming Dynasty. Fe/Mn were 11.9 ± 0.39, 2.31 ± 0.54 and 7.09 ± 2.07, respectively. The Co concentration for the same periods were: <100 mg kg−1, 500–600 mg kg−1 and >2500 mg kg−1. Other analytes used to create statistical database of blue and white porcelains include: B, Cr, Ho, Li, Mn, Ni, Pb, Th, U and REE 192
Various Cobalt pigment of Qinghua porcelain from Jingdezhen in Yuan Dynasty MS; LA-ICP; s Major and trace elements determined in an attempt to differentiate between different Qinghua porcelains. All blue decorations had similar high FeO and low Mn, indicating a non-Chinese source. The Cu, Ni, Pb, Sb and Zr concentrations in the Qinghua porcelains and those from Islamic blue and white wares of 13th and 14th centuries possibly provided evidence of the provenance 193
Various Indigenous lead-glazed ceramics from Northern Peru MS; LA-ICP; s NAA Pastes analysed using instrumental NAA and glaze analysed using LA-ICP-MS. Pastes had a great deal of compositional variety, but glazes had two discrete groups. The authors concluded that either several paste recipes were used or materials came from different sources, but that glaze production came from distinct sources of lead ore 194
Various Chinese cloisonne wares and painted enamels from Imperial Palace MS; LA-ICP; s Raman spectroscopy as well as LA-ICP-MS and EDXRF used to analyse samples. Red (632.8 nm) or IR laser (785 nm) used to ensure no background fluorescence and resonance effects. Cloisonne wares are mainly lead-based potash-lime silicates, whereas enamels are lead-potash silicates 195
EDXRF; —; s
Various Archaeological artifacts from Tamilnadu, India XRF; —; s Firing temperature shown by FT-IR to be <800 °C. Hierarchical cluster analysis of atomic spectrometric data used in an attempt to establish provenance 196
XRD, FT-IR, SEM-EDS
Various Dressel 2-4 amphorae XRF; —; s XRD Pottery composition compared with local (Calabria, Southern Italy) clays and sands. An add-on to the commercial Excel program called “Solver” was used to do comparison. Data indicated for the first time that these amphorae were produced locally 197
Various Gauloise 4 amphorae found in Northern Spain XRF; —; s Eight different amphorae shards analysed and analytical data treated using a hybrid clustering method combining principal component analysis (PCA) and dynamic cloud algorithms. Results were subsequently validated using factorial discriminant analysis. Five of the eight samples were made in France and had been transported to Spain 198
Various Historical enamels XRF; —; s Alpha-PIXE What was thought to be 11th and 12th century enamels were exposed as modern copies because of the high concentrations of Pb as well as As, Cr and Zn. Matrix factorization analysis of XRF data highlighted chemical associations between Cd, Se, Ba and Zn, indicating use of a modern cadmium lithophone in the red decoration 199
Various Jingdezhen and Longquan celadons EDXRF; —; s Analytical data from 40 shards from different cultural eras analysed using a relatively new statistical method called random Forests. The contents of Na2O, Fe2O3, TiO2, SiO2 and CaO enabled distinction to be made between the two kilns and between different eras. The firing technology between the kilns was very similar 200
Various 21 glazed Early Bottger red stoneware XRF; —; s Portable XRF instrument used to analyse glaze and gilding. Samples also analysed using a portable Raman spectrometer. Gilding fell into three categories: (1) pure Au, (2) Au + Hg and (3) an alloy of Cu and Zn 201
Various Neolithic pottery from North East Italy XRF; —; s XRD, optical microscopy, X-ray computed micro-tomography A multi-analytical study enabled the study and quantification of the clay material, lithic inclusions and porosity. This facilitated conclusions of manufacturing technology and provenance to be made 202
Various Imperial Longquan Celadon porcelain XRF; —; s Firing technology investigated in 85 shards of porcelain using EDXRF. The TiO2 and Fe2O3 contents in the paste differ between Hongwu and Yongle eras. K2O, Fe2O3, TiO2 all higher but CaO lower in early Ming materials compared with Southern Song Dynasty. Analytical data analysed using PCA 203
Various Glazed ceramic artifacts from Egypt OES; LIBS; s Qualitative results obtained using LIBS were confirmed using SEM-EDS and XRD. Data yielded information on manufacturing process and the raw materials 204
Various (8) Archaeological pottery and brick samples from India OES; LIBS; s Eight REE (Ce, Dy, Er, Gd, La, Nd, Pr and Sm) determined using LIBS. Insufficient sensitivity to determine heavier REE. No chemometrics used, but authors still concluded that all the clays had same provenance 205
Various Roman-Hispanic archaeological ceramics OES; LIBS; s Qualitative determination for most analytes but quantitative determination of Fe. Standard additions calibration and calibration using standards prepared in calcium carbonate, graphite and cellulose. Severe matrix effects observed with graphite and cellulose standards. Calcium carbonate standards and standard additions calibration gave comparable results and acceptable data for a CRM 206


Two reviews relevant to the topic of historical ceramics have been published during this ASU review period. The first, entitled “Using non-destructive portable X-ray fluorescence spectrometers on stone, ceramics, metals and other materials in museums: advantages and disadvantages”, contained 87 references.189 It was noted that over the last decade, these instruments have enabled the non-destructive analysis of samples in situ, on virtually any sized sample and in a very rapid manner (i.e. hundreds of samples may be analysed on a daily basis). However, it also highlighted that precision can be erratic, sensitivity can be limited and the accuracy of the data can occasionally be questionable. The limitation of performing surface analysis on a sample that could potentially be heterogeneous was also assessed. The other review was a more general one entitled “analytical chemistry in the field of cultural heritage” (377 refs).190 This review covered molecular and atomic-based techniques as well as chemometric tools for data analysis. The primary focus was on the impacts of environmental stressors, the chemical reactions the sample may undergo in its environment and remediation methodologies.

3.3 Semiconductor materials and electronic devices. Applications of atomic spectrometric techniques in the characterisation of semiconductor wafers and multilayer materials, solar cells and a range of electronic devices are described in this section of the review. A summary of other developments in this field not specifically highlighted in the review text is provided in Table 6.
Table 6 Applications of atomic spectrometry to the analysis of semiconductor materials and glasses
Element Matrix Technique Sample treatment/comments Reference
Ag Organic optoelectronic devices SIMS; —; s Characterisation of Ag diffusion in a metal–organic multilayer material deposited on an Si substrate using a 250 eV to 1 keV Cs+ primary ion beam 235
Ag and Au Mobile phone printed circuit boards AA; F; l Samples of component stripped base circuit boards were ashed and digested in acid prior to detection of precious metals for recycling purposes. Ag and Au were found in the range 0.25–0.79% and 0.009–0.017% and w/w 236
As and P Semiconductor gases MS; ICP; g Semiconductor gases (AsH3 and PH3) were converted to particulates by reaction with O2 and NH3 and then transferred to the ICP via a gas exchange device. The LODs reported for the method were 1.5 pL L−1 and 2.4 nL L−1 for AsH3 and PH3, respectively 237
Au Zinc blende semiconductor materials SIMS; —; s Study of migration and concentration profiles within Au-doped HgCdTe samples. The Au was found to be associated with Hg vacancies in the material 238
B Crystalline silicon APM and SIMS Investigation of effect of C implantation on B distribution in material using APM for 3D mapping and SIMS for depth profiling 239
B Quantum well structures SIMS; —; s Investigation of B contamination in GaInP/AIGaInP materials 240
B Boron silicate glass film SIMS; —; s Depth profiling to assess B diffusivity in glass film for potential use in n-type solar cell. Results obtained agreed with calculated model values 241
Cl Solar cell absorber thin films TOF-SIMS; —; s Three-dimensional depth profiling of Cl in polycrystalline CdTe absorber treated with CdCl2. A lateral resolution of 80 nm was achieved 242
Cr Solar cell materials X-ray fluorescence microscopy; —; s Use of synchrotron source to identify and quantify Cr precipitates in multi-crystalline silicon 243
Cr and Ni Thin film solar cells SIMS; —; s Depth profiling and quantification of impurity diffusion into, Cu(In,Ga)Se2 device layers 244
MS; ICP; —
Cu Metal oxide semiconductor XPS and SIMS Study of Cu/SiO2/Si metal–oxide-semiconductor devices with and without an MnSiO3 barrier layer fabricated in situ in an ultra-high vacuum XPS system the material interface chemistry was investigated by XPS and Cu diffusion examined using SIMS depth profiling 245
In Multiple quantum well structures SIMS; —; s Investigation of In diffusion in GaInP/AIGaInP materials 246
Li Lithium ion battery anodes SIMS; —; s Mapping of distribution and diffusion into Si anode material and particles 247
Various Automotive glass XRF; —; s and EXAFS Method described for the identification of glass manufacturer source based on quantification of Al, Ce, K and Mg by XRF and comparison of EXAFS spectra amplitude with Fourier transform intensities 248
Various (4) Battery cathodes AE; ICP; l Determination of Co, Li, Mn, and Ni in leachate from cathode materials synthesised from waste battery materials 249
Various Chalcogenide glasses TOF-SIMS; —; s Laser desorption ionisation was used to directly sample (GeSe2)(100 − x)(Sb2Se3)(x) type materials. The instrument system was used for partial structural characterisation and for evaluating H and O contamination 250
Various Electroplated Cu deposits for microchip architectures MS; LA; s A fs pulsed laser system (775 nm, <1 kHz repetition rate, <1 mJ per pulse, 15 μm i.d. spot size) was used to ablate and ionise the sample prior to detection using a miniature reflectron-type TOF-MS fitted with a microchannel plate detector. A mean depth resolution of 10 nm per laser shot was achieved for an electrodeposited Cu film layer 251
Various (4) Fibre glass OES; ICP; l Investigation of systematic leaching of fibreglass materials using H2O and HCl for Al, Ca and Na. Fibres subjected to leaching were examined by IR spectroscopy 252
Various (3) Glassy alloys of As, Ge and Se XRF; —; s Comparison of the use of mono-energetic high energy electron beam (30 keV) and synchrotron bremsstrahlung X-ray excitation. Samples (of the type Ge1−xSex, As1−xSex and Ge1−xyAsySex) were coated with a 20 nm carbon film to prevent surface charging and an area 1 mm2 was examined. Good accuracy was achieved for quantitation of main components in films up to 0.1 μm thick 253
Various High purity germanium MS; ICP; g, CS-ETAAS Matrix modification preparation step using Cl2 gas in situ to volatilise and remove Ge in an argon flow from a quartz reaction vessel which also served to reduce analyte blanks. Accuracy was assessed by use of spike recoveries. The LODs for the method were reported in the range 18 to 0.033 ng g−1 254
Various International simple glass OES; ICP; l Controlled aqueous leaching study (511 days) on alteration of borosilicate glass relevant to nuclear glass repository material exposed to chlorides of Co, Mg, No and Zn. Altered glasses were then characterised by SEM, TEM-EDX, ToF-SIMS and XRD 255
Various (3) Lithium ion battery cathodes SEM and SIMS Use of focused ion beam SEM in combination with TOF-SIMS for nanoscale chemical mapping of Co, Li, and Mn elemental distributions and identification of Li trapping sites in cathodes 256
Various Phosphate glasses OES; LIBS; s Direct determination of REEs (Sm, Tm and Yb) in doped glasses. P was used as an internal standard for calibration purposes. Good correlation was obtained with certified values 257
Various (3) Polyamide–chalcogenide films AAS, XRD and XPS Samples of Polyamide–CdSe–CdS–Ag2Se–Ag2S films were digested in conc. HNO3 and HCl and Cd, Se and Ag determined in solution by AAS. Related bulk structural compounds species were investigated using XRD and surface layers examined by XPS but presence of chalcogenide species could only be identified from AAS data 321
Various (4) Solar cell absorber materials XRF; —; s XRF measurement of Ga and In content and Ga[thin space (1/6-em)]:[thin space (1/6-em)]In ratios in Cu(In1−xGax)Se2 thin films with varying Ga content using ICP-MS validated standards for calibration. SIMS analysis was carried out using a Cs ion beam (60° angle of incidence, 5 keV, 450 nA at 10−9 torr) to measure depth profiles of Cu, In, Ga, Na and Se 322
SIMS; —; s
Various Solar cell materials MS; ICP; l Identification of metal impurities and precipitates in multi-crystalline silicon 323
Various Superconductor thin films MS; ICP; s Use of a fs laser to achieve high spatial and depth resolution in the quantitative determination of LaPdxSb2 and La2CuO4 film (10 nm) stoichiometry 324



3.3.1 Wafers, thin films and multilayer materials. Atomic spectrometry in almost all its forms continues to be an enabling technology that is crucial enabling the development of new semiconductor materials. The previously observed trend towards the use of a multiplicity of atomic and molecular techniques (often as many as 10) in characterising a newly created material continues. While a significant volume of literature in such applications has been reported in the year under review, much of it is not analytically novel, beyond the unique qualities of the materials themselves.

Advances in research into novel approaches to the characterisation of semiconductor materials is now firmly focused on addressing the technical challenges posed by ultra-thin film and multi-layered functional materials. As a consequence, atomic spectrometry techniques which can provide not only quantification but spatially resolved analysis are now predominant in this field. For example, laser induced breakdown spectrometry has been applied to the characterisation of zirconium oxide thin films (40 nm) deposited on silicon chips.207 The effect of LIBS experimental conditions such as laser energy and focus to sample distance and gate delay were investigated. It was found that the focus to sample distance had the greatest influence on plasma formation and resultant spectra produced. An RSD of the order of 1.6% was reported for the Zr peak signal. Using a single pulse and a low ablation energy the system was shown to be capable of quantitative and qualitative analysis of this type of thin film. The application of grazing-incidence XRF and NEXAFS to the depth profiling of complex nano-layer structure has been described by Pollakowski and Beckhoff.208 The combination of the two techniques was used to examine buried thin films and interfaces non-destructively. Model systems (consisting of a carbon cap layer, two titanium layers differing in their oxidation states and separated by a thin carbon layer, and a silicon substrate covered with molybdenum and a carbon layer) were used to develop a differential approach that allowed the chemical species of the titanium multilayer structures to be derived.

Secondary ion mass spectrometry is often the technique of choice for high sensitivity characterisation of complex thin film systems and reports on this type of application continue to appear in the literature. Thus an investigation of depth profiling of Ta/Si multilayer materials by TOF-SIMS has been reported by Liu et al.209 A model for depth profile reconstruction was developed and applied to already measured sputter depth profiles generated using a 1 keV energy Cs+ ion beam at an incident angle of 45°. The samples contained 10 alternating layers of Si (105 nm thick) and Ta (7.5 nm thick). The mixing roughness information depth model took into account a decrease of sputtering rate with depth, preferential sputtering of Si and a time dependent matrix effect on Si+ intensity. It was established that similar depth resolution for the Si and Ti layers and that depth resolution increased with sputter depth (4.2 to 6.8 nm for 50 s and 300 s sputtering time respectively). Using the model, it was possible to achieve a full reconstruction of the measured profiles of the Si and Ti layers, with an average error of =±5%.

The analysis of contaminated and decontaminated substrates (Si wafers and different Chemical Agent Resisting Coatings, CARC) paint system was evaluated by Landstrom et al.210 by means of LIBS and ATR-FTIR application. The paper details the study of the contamination of few organophosphates on different substrates by LIBS monitoring the intensity of P emission line and also evaluation of decontamination procedures. Also, ART-FTIR was applied to verify chemical welfare agent residues in the polymer based paint system. The team is positive about further studies of improved spectroscopic methods and expanding the contaminated model systems to include other substrates like skin, personal protective equipment, etc. and for LIBS to analyze more chemical welfare agents such as S, F and Cl.


3.3.2 Solar cells and photovoltaic materials. The literature relevant to the analysis of solar cell and photovoltaic materials is now dominated by studies of Cu(In,Ga)Se2 (CIGS) absorber material hetero-structures and thin films. Since these materials are likely to be incorporated in next generation solar devices, a follow-on review by Abou-Ras et al. comparing laser-induced breakdown spectroscopy and grazing-incidence X-ray fluorescence analysis in such applications is timely.211 This article supplements another related review in published 2011 comparing 18 other techniques for the analysis of CIGS materials [Microscopy and Microanalysis/Volume 17/Issue 05/September 2011, pp. 728–751]. The literature in the year under review in this ASU broadly reflect the range of options available for and used in such applications. For example, an investigation of analytical precision of LIBS in the characterisation of CIGS thin films has been published by In et al.212 The thin films were examined using laser energies and gate delays in the range 0.16 to 2.9 mJ and 0.12 to 3.6 μs respectively, and utilising two ablation spot sizes (42 and 104 μm). The contribution to overall RSD of the measurement from the intensified CCD detector shot noise was estimated using a stable light source for intensity calibration in order to develop a linear model that related detector noise to signal intensity. The shot noise RSD contribution was then subtracted from the overall signal RSD (or that from intensity ratios) to derive the contribution made to variability by ablation plasma fluctuation alone. It was reported that the laser plasma-induced RSD based on intensity ratio measurement was significantly affected by the choice of gate delay time and tended to increase with both gate delay time and laser fluence. Variations in plasma induced RSD found in application to the analysis of CIGS thin films were attributed to the spectral features associated with material composition.

A range of surface analysis techniques have been applied to the quantification and depth profiling of matrix elements and trace impurities in CIGs photovoltaic absorber materials.213 Sample thin films were prepared on molybdenum back contacts deposited on soda lime substrates. The bulk concentration of the matrix elements was determined by ICP-OES, XRF and EPMA. The films were further characterised using TOF-SIMS, magnetic sector SIMs, AES and APT for depth profiling. It was concluded that APT could be used to generated 3D elemental compositional maps with sub nm resolution while the high sensitivity of SIMS allowed the creation of trace element depth profiles in parallel. The application of ion beam techniques to the analysis of solar cells incorporating CIGS film absorber layer materials has been described.214 The 2 μm thin films were characterised using RBS and PIXE using helium ions to provide quantitative elemental depth profiles. The techniques were applied to both directly accessible single and double absorber layers and to absorbers buried within solar cells. The spectral data from both techniques were analysed together to produce best fit profile. The results produced from this combined approach for a number of samples were validated by use of a synchrotron sources grazing incidence XRF method and the results derived were in agreement within quoted uncertainties for the techniques.

A potentially important new method for depth profiling of photovoltaic absorbers based on the sequential combination of GD-OES and XPs has been reported.215 In this approach the GD was used to sputter through the material to reach critical buried areas of the CIGS material that could then be examined directly by high resolution XPS depth profiling. Thin film (2.5 μm) samples were prepared on molybdenum covered glass and profiled using GD-OES (4 mm diameter anode, pressure of 350 Pa, pulsed rf power source (35 W). Crater profiling by XPS was carried out using an argon ion source operating with 2 keV, 10 mA bean energy. XPS was also carried out on a CIGS sample chemically etched using HBr/Br2 acidic solutions for comparative purposes. It was found, unsurprisingly, that GD sputtering caused significant chemical and morphological changes at the crater surface. These changes were influenced by the choice of GD sputtering gas and the plasma temperature. It was reported that employing a GD with flow inversion prevented the deposition of metallic particulates in the sputter crater allowing subsequent XPS analysis close to the original CIGS composition to be conducted. It was also noted that GD-OES analysis could be successfully restarted after XPS examination, potentially allowing further access to deeper layers of the material. It was suggested that remaining issues identified related to restoring GD crater surfaces to a pristine condition could be addressed by mild, rapid chemical etching or by sputtering using a cluster ion source. An in situ temperature stage has been designed that allows direct measurements to be made by synchrotron X-ray spectromicroscopy during device processing.216 The system was applied to the characterisation of CIGS thin films during a heating regime representative of industrial fabrication conditions. The construction materials were selected to allow operation under non-oxidising atmosphere conditions (e.g. in the presence of H2Se and H2S). It was reported that the system was able to provide information on nanoscale material defects within the resolution of the technique (125 nm). A combination of Raman Spectroscopy and XRF has been applied to the non-destructive analysis of CIGS films.217 Thus a reference free XRF method was used to determine the surface and bulk elemental composition of the films. Reference Raman spectra were then generated for the relevant Cu(In1−xGax)Se2 related species. Metrological scanning force microscopy was used to calibrate the lateral dimensions of the sample in a manner traceable to international standards. This approach allowed the Raman mappings to be converted into a quantitative determination of surface coverage values, with an associated uncertainty budget. It was suggested that the method was suitable for monitoring quality control of CIGs film formation.


3.3.3 Electronic equipment and devices. There continues to be significant activity reported in the characterisation of electronic materials at the component or device level. Much of this work is related to either recycling or reuse of fabricated materials. The ever increasing usage of mobile devices for personal use has led to a great deal of research relating to battery and component materials such as electrodes and electrolytes.

The ageing of lithium ion batteries is an increasingly popular topic of investigation. Consequently, an overview of capabilities and limitations of ion beam analysis techniques to study the distributions of lithium and other elements present in the electrodes is worth reading.218 The article assessed the use of PIGE spectroscopy in the wider context of other analytical methods for characterising electrodes. In one systematic study of material degradation that will be of particular interest, batteries were cycled in normal use to different points in the lifetime cycle.219 The devices were then disassembled and the electrode removed prior to ICP-OES analysis. It was found that there was a linear increase in the bulk Li, Mn and P content of anodes with ageing time. Vertical depth profiles of these elements were obtained using GD-OES allowing the variation in surface and bulk composition to be correlated with the electrical performance of the batteries. Lithium ion battery degradation has also been studied using TXRF.220 The technique was used for the direct determination of transition metals that were electro-deposited on the battery graphite anode. It was found that TXRF yielded results that were in reasonable agreement (recoveries in the range 91–100%) with those obtained using microwave assisted digestion procedures with ICP-MS and ICP-OES detection. It was reported that in battery operating conditions exhibiting low anode levels of transition metals, TXRF provided sufficient sensitivity for the measurement.

In a new and potentially very significant development, operando X-ray absorption spectroscopy has been used in a full field microscopy mode to map lithiation in transition metal oxide cathodes.221 A new approach that reduced XAS measurement time was employed. Sample X-ray dose was reduced by using fewer spectrum energy points (12) at the absorption edge for measurement. Although this reduced overall spectral resolution, the approach was coupled with post- measurement processing involving a comparison of the measured spectrum data with high resolution XANEs reference spectra (47 energy points) for the same area of the electrode. The method was used successfully to monitor changes in oxidation state of battery electrode metals (Al, Co, Ni). In a similar vein, a new spinel based electrode material for lithium ion batteries has been characterised by fast μ-XRF.222 The electrode (of the type LiNi0.5Mn1.5O4) was mapped using medium spatial resolution (500 nm) over a millimetre range. The Ni oxidation state was mapped via acquisition of spectra in the vicinity of the Ni K absorption edge generating a charge distribution image. This allowed investigation of elemental distributions and the identification of hot spots including material erosion at higher battery recycle rates.

There have also been a number of reports concerning the characterisation of solid electrolyte interphases in lithium ion batteries. X-ray absorption spectroscopy has been used to monitor electrolyte growth on graphite and carbon coated ZnFe2O4 electrodes.223 High quality As K edge spectra were collected in fluorescence mode and the As valence states were used to monitor the formation of the solid electrolyte interphase. It was found possible to infer local As chemical structure, such as the formation of AsFN complexes using this approach. On a related topic, LIBS has been applied to three-dimensional elemental imaging of Li ion solid state electrolytes.319 Samples of electrolyte (Li7La3Zr2O12) were examined directly and spatially resolved maps of major and minor elements were produced. A fs laser sampling system was utilised that provided a sampling depth resolution of 700 nm. The data acquisition approach was also successfully applied to the generation of 2D cross sectional images and 3D atomic ratios for the analytes of interest and these were related to the effect of battery process conditions.

The disposal of electronic equipment at the end of the lifecycle is now widely recognised to generate adverse environmental impacts. However, approaches to recycling of devices are also driven by financial considerations due to the economic value of component raw materials and energy saving potential. The European Directive (RoSH 2011/65/EU) specifies that plastics containing brominated flame retardants are identified and removed from the recycling process. A combination of these factors has led to literature reports describing analytical methods to evaluate the potential for environmental impact. For example, a batch leaching test has been described and applied to the assessment of the toxicity associated with electronic motherboards.320 The devices were subjected to leaching procedures using distilled water, nitric acid, acetic acid and synthetic acid rain solution. A total of 21 elements including platinum group metals and Br in the leachates were determined by ICP-MS. The pH of the leachate solutions was found to be in the range 2.33–4.88 and the highest levels of Br were found in the acetic acid solution. Significant levels of Pt group elements were found The concentrations of Ir, Pd, Pt and Rh found were 3.45, 1.43, 1.21 and 22.19 μg L−1 respectively.

The high turnover of personal devices such as mobile phones and computers is posing a similar environmental challenge. Consequently, methodology has been described for the application of LIBS to the identification of Au in 36 broken or obsolete computer components scrappage and Ag in 13 mobile phone housings.224 Samples were cleaned to remove surface environmental contamination using a single laser pulse with an energy of 10 mJ in a 250 μm spot (5 points per sample) prior to analysis by LIBS. The laser power was then set at 75 mJ with a spot size of 75 mm for the determination of Au using 10 pulses per sampling point. In the case of the 13 mobile phone samples containing Ag, a laser power of 100 mJ and a spot size of 125 mm was used for determinations with 30 sampling pulses per point. The LIBS spectra obtained were subjected to Principal Components Analysis (PCA). Significant differences between surface and bulk concentrations of both Au and Ag were observed and in combination with other elements in the LA depth profile were related to composition of the devices (such as electromagnetic shielding in mobile phones). The presence of Au and Ag was confirmed using SEM-EDS. However, it was claimed that the LIBS methodology provided significant advantages in term of minimal sample preparation and speed of analysis. The technique was considered, somewhat optimistically, to be potentially useful in recycling processes as it was able to reveal hidden surface and bulk component structural content that cannot be easily identified for analysis by visual inspection alone. The depth profiling of metal coatings on circuit boards has been investigated directly using a novel low temperature plasma probe sampler.225 The dielectric barrier discharge was used to sputter the sample layer by layer and the resultant aerosol generated was transported in the discharge gas flow to an ICP-Ms detection system. The combined instrument was used to profile a 20 μm Au layer on a 10 μm Ni/Cu substrate within a 30 s period. The results obtained were reported to be consistent with those obtained by XPS.

Finally, in an unusual development, elemental analysis has been used to characterise a semiconductor lubricant in a hard disk storage media device.226 The sample was studied unburnished, after acetone cleaning and under argon sputtered conditions prior to measurement. X-ray photoelectron spectroscopy was used in total reflection mode to detect C, F, O and N in the upper layer of the disk. The detection of Co and Pt was only achievable in the XPS non-total reflection mode because they were constituents of a deeper layer below the surface and interfacial regions of the device.

3.4 Glasses. There have been fewer publications relating to the characterisation of glasses in the year under review, perhaps reflecting the maturity of the field. A summary of relevant analytical methods reported is provided in the accompanying table.

There is increasing interest in the application of atomic spectrometric techniques that can provide insights into the micro-structure of glasses. For example, GD-TOF-MS has been applied in the depth profiling of coated glasses.227 A pulsed r.f. source was used to sample glasses and associated thin conductive and non-conductive layers. It was established that by selection of an appropriate GD pulse interval, it was possible to discriminate by temporal measurement of the pulse profile against polyatomic spectral interferences affecting key analyte masses of interest (Ca,44 K,39 Si (ref. 28) and Ti (ref. 48)). The instrument was able to measure a full mass spectrum every 33 μs, allowing for the possibility of detecting possible contaminants in the thin coatings (such as Cd, Sn, Te and Sb). A multi-matrix calibration procedure was adopted utilising both conductive and non-conductive samples. The elemental composition and thickness of the layered materials determined using this method was reported to be in agreement with nominal values. The characterisation of the thickness of nanometric thin films of vanadium oxide deposited on glass has been investigated using a portable XRF instrument.228 The instrument employed a mini-X-ray tube source with a silver target which could be operated up to 40 kV and 100 μA. An XR-100CR Si-PIN detector fitted with a preamplifier and a thermoelectric cooling system was employed for measurements. In order to maximise signal to background ratio in the presence of the silica glass matrix substrate, a 100 μm Ag filter was employed to strongly attenuate Ag K line source excitation. It was found that analytical conditions of 28 kV maximum voltage and 15 μA maximum current were optimal for the measurement of analyte elements with Kα and Kβ energies in the 3–15 keV range. The sample was placed 2 cm from the tube and 2.5 cm from the detector. It was fond that the thickness of the V nanometric films could be linearly correlated with the attenuation of the Ca Kα line intensity derived from the underlying glass substrate.

Depth profiling of a simulated nuclear waste glass has been explored using an argon clustering source in ToF-SIMS.229 The use of argon cluster ions for sputtering has become increasingly popular in recent years because has been observed in other applications to it produce less sample damage than when using conventional Cs+ and O2+ ion sources. All three ion sources were compared directly for the characterisation of a leached simulated borosilicate nuclear waste glass (SON68) using the same IONTOF TOF-SIMS instrument. It was found that using optimal Arn+ source conditions of 20 keV, a high sputter rate and low charge accumulation was achieved that allowed an interlaced model of dual beam depth profiling (time-separated sputtering and analytical phases) to be achieved without compromising analytical performance. However, in contrast to other reports in the literature, surface roughness was reported to be about a factor of two worse for the Arn+ source than for 2.0 keV Cs+ and O2+ ion sources in the same application. Nevertheless, the principal advantage of the approach was considered to be that the time taken to achieve depth profiling was shorter using the argon cluster ion system as a result of improved sputter rate.

Atomic spectrometric techniques are not best suited to the determination of fluorine, which is of particular relevance in relation to the analysis of glasses. Traditional methods involve lengthy sample digestion procedures that are prone to analyte losses and interference effects. Given these longstanding difficulties, two very different approaches to this application described in the period under review are worth highlighting. A new methodology for the analysis of F in glasses and glazes has been published.230 The approach described was based on the use of WD-XRF to achieve a rapid and reliable control method. Thus samples were prepared in the form of beads and subjected to direct analysis. Calibration was achieved using RMs that had previously been analysed for F by potentiometry. A quantification limit for F of 0.1% w/w was reported for the method. The second paper concerns the novel use of laser ablation for sampling into a glow discharge source for separate excitation prior to MS detection.231 The ablation sampling chamber was modified to introduce two electrodes to allow a discharge to be recreated in reduced pressure argon and helium atmospheres. The analytical performance of the system was compared to that for a conventional LIBS system for the analysis of RMs, glass and fluorine pellets. The main advantages of the LA-GC-MS technique in comparison with LIBS were reported to provided low detection limits, reduced matrix effects and better linearity, particularly in respect of F analysis.

The determination of trace metals in zircon glasses by LIBS is problematic because of spectral interferences derived from the matrix element. A new approach to overcoming this problem has been described which involves the combination of LIBS with fluorescence spectroscopy.232 A Nd:YAG laser operated at 1064 nm was employed to volatilise the glass sample. The resultant plasma-induced fluorescence from trace level Sm and U present could be distinguished from the LIBS background signal thereby allowing improved quantification. Detection limits were reported of 6 ppm and 154 ppm, for Sm and U respectively. A comparison of the performance of this new technique with WD-XRF in this application might be interesting to conduct.

Once of the cited disadvantages of the use of atomic spectrometric techniques involving laser sampling of solids is that of variable signal response resulting from elemental fractionation. This variability can arise from the use of different lasers and operating conditions, including the cell used and transfer of sample to the detector. The choice of laser is one of the critical decisions to be made in terms of instrumental set up and has been the subject of much investigation in recent years. Consequently, further work has been published in the comparison of femtosecond and picosecond lasers for use in the direct analysis of glasses by ICP-MS. Thus Shaheen et al.233 have investigated elemental fractionation and instrument response for laser beams of different pulse widths. Synthetic glass (NIST SRM 610) naval brass samples (SRM 1107) were ablated at the same spot for 800–1000 pulses using the same 785 nm laser operated with pulse widths of 11 = 30 fs and 110 ps respectively. Pulse repetition rates of 5–50 Hz were used. It was reported that the intensity of ICP-MS signals was higher for the fs laser under the same laser pulse repetition rates and fluence used. This observation was attributed to differences in particle size distribution produced by the lasers, and to consequent effects arising from transport of the sample to the plasma and resultant efficiency of ionisation. The fs laser also produced larger sized craters in the sample resulting in higher signal intensity. Assessment of element ratios indicated greater elemental fractionation for the ps laser than for the fs laser and it was noted that pulse repetition rate was a contributing factor. The reproducibility of replicate measurements of signal intensity, element rations and element fractionation was reported to be better using the fs laser (3–6%) than for the ps laser (7–11%). The determination of the U isotope content of glass using a laser ablation multi-collector ICP-MS instrument has been described.234 Samples of NIST glass SRMs (610, 612, 614, 616) were ablated using a fs laser. The U content of these samples was a two component mixture of naturally occurring U and an isotopically depleted spike added when the material was prepared. It was noted that the LA-ICP-MS analysis suggested that spatial inhomogeneity for rare U isotopes existed in the NIST 616 glass SRM. The fact that the analytical results agreed well with those derived from a sample dissolution and separation method indicates that this finding is unlikely to result from any intrinsic instrumental bias.

3.5 Nanostructures. The analysis of nanomaterials has continued to be one of the most heavily researched areas in this review. This is because of the large number of applications with which they are associated. As well as this section, the readers are also directed to other sections of this review, (cosmetics, 2.2.4, catalysts 2.3.2 and polymers 3.6) where other nanomaterial papers with a slightly different or wider application focus may appear. This section of the review focuses on applications grouped around the two principal analytical methods employed: (a) asymmetric flow field flow fractionation (AF4) and (b) single particle (SP) analysis; both of which are coupled with ICP-MS. There have been other papers that have adopted different approaches, e.g. capillary electrophoresis, direct introduction of the nanomaterial through nebulizer/spray chamber assemblies, etc. Progress in each of these areas will be discussed below.

There was one review paper published covering detection, characterization and quantification of engineered nanoparticles (containing 217 references)258. The review discussed the state of the art analytical methods used for determining chemical composition, mass and number concentration, size, shape aggregation etc. Such methods included AF4, SP analysis, capillary electrophoresis and hydrodynamic chromatography; all usually coupled with ICP-MS. Also discussed were coulometry and chemical sensors selective to nanoparticles. Sample preparation methodologies were also considered.

The combination of asymmetric flow field-flow fractionation coupled with ICP-MS (also referred to as AF4 below) has been discussed in a number of publications. Many report applications in which assorted types of nanoparticle were characterized successfully in many different matrices. However, it was also reported that potential errors may occur under certain circumstances.259 Losses of Ag nanoparticles were observed during analysis using AF4-ICP-MS. Parameters that might influence such losses including focusing and cross flows as well as sample concentration, buffer composition and the membrane itself were all studied. After use, the membrane was subjected to LA-ICP-MS analysis and this indicated that Ag losses to it accounted for less than 0.6% of the total Ag, which was regarded as being negligible. This effect could be minimized using sufficiently low concentrations and optimal conditions. Analysis of the cross-flow, slot-outlet flow and purge flow also indicated that less than 0.5% of Ag was lost to each of these parameters. The recovery rate at the detector flow was nearly 90%, indicating loss somewhere in the system. Injection of an ionic Ag standard resulted in the very low recovery rate of 6%. The authors concluded that loss of Ag during the analysis of Ag nanoparticles was therefore mainly attributable to the dissolution into Ag ions. In another paper, Ag nanoparticles as well as ions were determined in spiked river waters and some consumer products.260 The protein corona that forms on the nanoparticles on exposure to bovine serum albumin was used as a nanoparticle stabilization and recovery enhancement mechanism. Speciation between nanoparticulates and ions was achieved with the addition of penicillamine as a complexing agent. The effects of nanoparticulate coating and ionization state on the quantification were also evaluated. When a 5 mL sample loop was used, a LOD of 4 ng kg−1 was obtained for the method.

The analysis of food grade SiO2 particles was considered in three separate papers. A generic sample preparation scheme for inorganic nanoparticles in a complex matrix for detection, characterization and quantification using AF4 coupled with multi-angle light scattering and ICP-MS was proposed.261 The objective was to separate the nanoparticles from the matrix without altering the particle size distribution and without loss of the analyte. Two sample preparation protocols were tested: an acid digestion and a colloidal extraction. The former gave >90% recovery of SiO2 nanoparticles from a tomato soup matrix whilst not changing the particle size distribution. The SiO2 analyte is clearly very acid resistant. There are many nanoparticles for which the method developed would not be suitable. The determination of food grade SiO2 nanoparticles (food additive E551) using a range of analytical techniques including dynamic light scattering (DLS), multi-angle light scattering (MALS), AF4, ICP-MS and TEM was described in a second paper.262 The pros and cons of each method were discussed in detail. Experimentally, the AF4 coupled with ICP-MS approach enabled reliable detection below 100 nm for 10 of the 11 samples analysed. It was also able to quantify the mass concentration in seven samples at the mg L−1 level. The third paper263 concerned the use of both MALS and ICP-MS as detectors for the AF4 separation. The AF4-ICP-MS used size calibrants, whereas this was not required for MALS. The calibration for particle size was achieved through the addition of silica nanoparticles of known size, whereas post channel addition of elemental standards enabled quantification of the silica present in the different size fractions. The AF4-MALS-ICP-MS system enabled dimensional and mass determination of silica nanoparticles over the range 20–200 nm. The method was applied to the reference material ERM-FD100 and a silica suspension.

Several papers have reported the determination of Ag nanoparticles in numerous different sample types. Chicken meat was the sample of choice for Loeschner et al. who used an enzymatic extraction protocol to separate the analyte from the sample matrix.264 The results of AF4-ICP-MS were both repeatable and reproducible in terms of mass fraction and size. Although the work was successful, the authors did point out that determining the size distribution was difficult because of the lack of certified size standards. Another example determined citrate-stabilized Ag nanoparticles in anti-microbial consumer products.265 The success of AF4-ICP-MS in quantifying on a number-based particle size distribution was assessed though TEM, centrifugation liquid sedimentation (CLS) and DLS. The different techniques had varying degrees of success, with DLS failing. The authors attributed this to sample polydispersivity. Despite the samples having unknown surface properties and not knowing which dispersing agents to use (which could adversely affect AF4), agreement between AF4-ICP-MS and TEM data were in reasonably good agreement. The determination of citrate-coated and polyvinylpyyrolidone (PVP)-coated Ag nanoparticles in water extracts from soils was examined in a third paper.266 On-line UV-Vis and off-line HR-ICP-MS was used for detection following AF4 separation. The dispersant (0.01% sodium dodecylsulfate at pH 8) was added to facilitate successful fractionation. Using that dispersant, it was possible to determine the primary size of the nanoparticles in all but one case. The exception was for PVP-coated particles when clay colloids were present. This is because the nanoparticles interacted with the clay colloids, leading to an over-estimation of their primary size. Such an interaction is clearly possible in the natural environment, leading the authors to state that the nanoparticles could then enter aquifers and surface waters. A further study assessed the behaviour of Ag nanoparticles in artificial seawater.267 Analytical techniques including AF4-ICP-MS, SP-ICP-MS and UV-Vis were used to study the agglomeration process. The presence of alginate or humic substances affected the kinetics of the agglomeration process significantly. A final paper also determined Ag nanoparticles along with Au and Pt nanoparticles in controlled experiments in which Daphnia magna were exposed.268 Care was again taken to ensure no change to particle size distribution or composition occurred during the extraction process. Accordingly, two procedures were developed. One involved tetramethylammoniumhydroxide (TMAH) being used to digest the samples and the other was a much gentler enzymolysis procedure involving trypsin. The digests from both procedures were used for the AF4-ICP-MS study. Similar results were obtained for medium sized (50 nm) particles, but the use of TMAH was shown to lead to some dissolution of very small (<5 nm) particles. The authors noted that only 1–5% of Au and Pt nanoparticles remained in solution after exposure. They concluded that significant uptake by, or adsorption to, D. magna must have occurred.

Size distribution of Au nanoparticles in dietary supplements has been studied using AF4 with UV-Vis and ICP-MS detection.269 A linear relationship between particle size and retention time was established and the procedure used to characterize unknown samples. The traditional method of TEM was employed for comparative purposes and it was found that there was less than a 5% difference between the data produced by the two methods over the particle size range 7–30 nm.

Nanoparticles are known to agglomerate in many sample types and this agglomeration can make their determination difficult. If a simple ‘total’ concentration measurement is to be made, the agglomerated nanoparticles can sink to the bottom of the sample tube and not be taken up into the nebulizer of an ICP or FAAS instrument. Even if the agglomerates are taken up by the nebulizer, they may be discriminated against by the nebulizer/spray chamber sample introduction assembly and never reach the plasma. Gross underestimates may therefore be made of real concentrations. The agglomerates can also lead to serious problems when particle size distribution measurements are to be made. Dudkiewicz et al.270 developed a uniform measurement expression for cross method comparison of nanoparticle aggregate size distributions. Effectively, numerous techniques (high vacuum SEM, liquid cell SEM, nanoparticle tracking analysis (NTA), AF4-ICP-MS, gas phase electrophoretic mobility molecular analysis (GEMMA) and CLS) were all used to obtain size distributions of the same silica sample. The size distributions from each were then compared and conclusions drawn on individual method's measurement accuracy, LOD and LOQ. Both GEMMA and AF4-ICP-MS gave comparable data. The other four techniques suffered from problems associated with high LOD (CLS, NTA and liquid cell-SEM) or sample preparation that is biased by increased retention of smaller nanoparticles (SEM). However, the development of a uniform expression of mass equivalent diameter (MED) enabled the other techniques' data to still be used and be related to each other.

Determining the speciation between Ag ions and Ag nanoparticles has long been problematic. This issue has been addressed by the employment of hollow fibre AF4 coupled with several different detectors including UV-Vis, DLS and ICP-MS.271 This new method, named HF5 by the authors, comprised a hollow fibre and a mini-column packed with Amberlyte IR120 resin to preconcentrate the Ag ions and Ag complexes. The mini-column was placed after the AF4 arrangement and before the ICP-MS instrument. Such an arrangement enabled full separation of Ag ions, the adduct of Ag with cysteine, and five sets of Ag nanoparticles (with nominal diameters of 1.4, 10, 20, 40 and 60 nm). Good agreement between data obtained using this system and those from TEM were obtained. In addition, recovery for the seven Ag species tested ranged from 70.7–108%. Although this outcome is a still little variable, it is clearly a significant step forward for in research in this area.

Single particle analysis (SP) has been one of the most rapid growing areas of research relevant to this review over the last few years. Its expansion has continued this year, but with a subtle change of emphasis. Previously, there had been many theoretical studies attempting to elucidate optimal operating conditions. In this review period, while many theoretical studies have been produced, these are still outnumbered by descriptions of technique applications.

The results of an interlaboratory comparison in which the gold nanoparticle reference materials NIST RM 8012 and NIST RM 8013 were sent to six expert laboratories were reported.272 The level of agreement in particle size measured by SP-ICP-MS and six reference techniques was good. However, the precision of the measurements between laboratories was relatively poor. Precision between different workers within the same laboratory was better. Precision was better for the material with the larger, 60 nm particles. Particle number concentration and Au mass concentration recovery were quantitative for RM 8013, but were significantly lower and with much poorer precision for RM 8012. Analysis of the operating conditions did not indicate an optimal dwell time.

Data acquisition for SP-ICP-MS can be problematic, but data evaluation can be equally troublesome. The development of a data evaluation tool as a routine technique for the calculation of particle size concentration and size distribution from the raw data of SP-ICP-MS was reported.273 The tool was evaluated using data from both a quadrupole and sector field instruments and using four types of nanoparticle. The size LOD for the quadrupole instrument were: 20 nm (Ag and Au), 50 nm (TiO2) and 200 nm (SiO2). The sector field instrument gave marginally improved LOD, for instance 10 nm for Au. Concentration-based LOD ranged from 1 ng L−1 for a 60 nm Au nanoparticle up to 0.1 μg L−1 for a 500 nm silica nanoparticle. The dynamic range was limited to only two orders of magnitude, presumably to ensure coincidental particle detection, so sample dilution was frequently necessary. Precision was <5% and <10% relative for the determination of particle size and concentration, respectively. Accuracy was described as being <10%. The whole technique was then applied to food, wastewater, culture media and biological tissues. The authors concluded that SP-ICP-MS with their evaluation tool was rapid, cost efficient and an easy to use screening technique for metal and metal oxide nanoparticles.

Single particle-ICP-MS is still not fully developed and the problems of incomplete particle vaporization and the non-linear detector response as being the major factors that cause non-linearity at high particle mass have been studied.274 The non-linear detector response in the pulse count mode arises from the overlapping of ions at the detector within the 40 ns dead time of the electron multiplier. The overlap was particularly severe if a short pulse duration of 300 μs is used. The non-linear detector response was modelled using Poisson statistics. In addition, the applicability of different external calibration methods was examined including the use of standard particles, discrete standard droplets and continuous nebulization of a standard solution. The continuous nebulization of standard solution may yield a different sensitivity to particulates and also requires a linear response. Calibration using the other two methodologies did not suffer these drawbacks.

According to one report,275 another problem identified when SP-ICP-MS is used is that it is particularly poor at measuring extremely low diameter particles (<10 nm). The size detection limit was improved in the study by resolving the ion bursts from Ag or Au nanoparticles using a 0.1 ms dwell time. The method employed, termed ‘the Fast Acquisition Speed Technique (FAST)’ was evaluated using a sector field instrument with high ion transmission efficiency. An algorithm was also developed to aid data processing. Using FAST and the algorithm, the particle size LOD was improved to 6.4 nm. Strenge and Engelhard276 also identified some limitations of SP-ICP-MS and, in an attempt to overcome them, developed a data acquisition unit capable of probing the ICP-MS instrument's detection circuitry. The unit was capable of achieving dwell times of as little as 5μs and could operate over an unlimited measurement time. Using a much higher time resolution than a typical particle related ion cloud, it was possible to minimize the possibility of particle coincidence and eliminate split particle events completely. A duty cycle of 100% of the counting electronics increased the method's accuracy further. Detection limits with regard to particle size were still approximately 10 nm. The relative merits of μs rather than ms dwell times were also discussed at length.

Numerous applications of SP-ICP-MS have also been published. For example, SP-ICP-MS has been employed to monitor TiO2, Ag and Au nanoparticles during drinking water treatment.277 Measurements of concentration, size, size distribution and dissolved metal element concentration in the waters were made. The effects of conventional drinking water treatments, e.g. lime addition, alum coagulation, filtration and disinfection, were all tested. Of the nanoparticles tested, 97 ± 3% were removed by the addition of lime and alum coagulation followed by a filtration through an activated carbon filter. Waters (source and drinking) were also collected from some treatment plants. Although the Ag and Au particles were not present in the source water, TiO2 was. The treatments used at each of the plants were capable of removal of 93% of the Ti containing particles and the dissolved Ti. Other examples of SP-ICP-MS were the determination of Ag nanoparticles from the decoration of pastry278 and Cu nanoparticles in soil.279 In the former application, TEM was used as a means of method validation. The number-based size and shape distribution of the nanoparticles released from silver pearls added to the pastry were determined. The material NM-300 K was used as a positive control to determine the uncertainty on the measurement of the shape and size of the particles.

The determination of ZnO nanoparticles in surface and waste waters has also been reported.280 To distinguish between nanoparticulate Zn and dissolved Zn2+, the authors used a mini-column of Chelex-100 to retain the ions prior to determination. In addition to obtaining a size distribution of nanoparticles, it was also possible to distinguish between labile Zn ions and the strongly bound Zn fractions. Spiked and unspiked water samples were used for the analysis. In two natural waters analysed, 93–100% of the dissolved Zn was measured. The nanoparticles present in the wastewater samples comprised small agglomerates with a size ranging from 133.6 to 216.4 nm. The last application relevant to this section is one that described the analysis of TiO2 nanoparticulates in sunscreens.281 The primary particle size, size distribution, particle concentration (particles per mL) and mass content (weight percent) of TiO2 were measured in four commercial sunscreens. Primary particle sizes ranged from 32 to 40 nm. The mass content was determined using a novel standard addition SP-ICP-MS approach in which 40 nm titania nanoparticles were added as the standard. The authors noted that results obtained were in reasonable agreement with those obtained after acid digestion. However, there was room for improvement and this was ascribed to the nanoparticle standards used for calibration not being closely matched in size to those found in the samples.

There have been reports of the use of single particle inductively coupled plasma mass spectrometry in conjunction with microdroplet generation (MDG)-ICP-MS. In one example of this approach, individual microdroplets provided by the microdroplet generator were merged with an aerosol generated by a pneumatic nebulizer and then introduced to the ICP-MS instrument.282 The MDG provided high efficiency transport of individual and discrete droplets, which can be used as a means of calibration for SP-ICP-MS. The main advantages of the system were described as being the fast processing of large sample volumes, fast exchanges of different sample matrices and the calibration of the nanoparticle signal using traceable elemental standards. Bulk analysis of the nanoparticle solution allowed transport efficiency determination without the requirement of any additional information from reference nanoparticles. Standard Ag nanoparticles were analysed and had diameters of 60.41 nm and 80.0 ± 1.4 nm which are in good agreement with values obtained from the supplier (60.4 ± 6.6 nm and 79.7 ± 5.4 nm). In a second approach standard SP-ICP-MS was compared with MDG-ICP-MS for the determination of particle number concentration of Ag and Au particulate suspensions in either ultrapure water or citrate solution.283 Transport efficiencies for the nebulized sample were calculated using the waste collection method and were 11–14% for Ag and 9–11% for Au. Transport efficiency for the MDG was 100%. The SP-ICP-MS yielded results that were 20–40% of expected values whereas the MDG results were closer to 80%. The authors noted the importance of nanoparticle reference materials if the accurate determination of particle number is required.

Interestingly, despite the fact that SP-ICP-MS is not yet fully developed, it has already been used as a reference method for new techniques. A new method for the characterization of silica nanoparticles was based on a polymerase chain reaction (PCR) binary yes/no measurement arrangement, binomial statistics and DNA comprising the silica nanoparticles.284 Individual tagged particles over the size range 60–250 nm could be detected and counted in drinking water using a standard PCR device within 1.5 hours. The SP-ICP-MS was used as validation which might be a step too far at the current stage of development given the foregoing discussion in this section of the ASU. Nevertheless, in the absence of alternative reference approaches, this development does at least indicate that SP-ICP-MS is becoming established as a valuable technique in this field. At present the alternative method they have developed appears not to be able to measure smaller nanoparticles or other nanoparticles types, (e.g. Ag, Au, CeO2, etc.). However, it is clearly another step forward. The use of SP-ICP-MS as a reference technique has been described in the context of the development of SALD (substrate assisted laser desorption) of sample directly from a suitable absorbing plastic surface using a commercial ablation cell.285 A frequency quintupled Nd:YAG laser (213 nm) operating at a low laser fluence was used to ablate Au nanoparticles individually to an ICP-MS instrument. Operating conditions such as laser fluence, laser beam scan rate and carrier gas flow rate were all optimized to ensure the greatest analyte transport efficiency to the plasma and to avoid Au nanoparticle disintegration within the laser irradiation. A well-characterized reference material containing Au nanoparticles of diameter 56 nm was analysed; obtaining a transport efficiency of only 61%. The technique was also tested on a commercially available sample of Au nanoparticles of diameter 86 nm.

As set out in the foregoing, although flow field-flow fractionation- (AF4) and single particle-ICP-MS were the most common atomic spectrometric methods for nanoparticle characterization, other methodologies have also been used. As discussed previously, the determination of nanoparticles in water samples can be problematic because of agglomeration. This leads to significant underestimation of nanoparticle concentration. Methods to try and overcome this problem during the determination of both rutile and anatase TiO2 nanoparticles have been considered.286 Several different approaches were tested including ultrasonic agitation immediately prior to sample analysis and chemical dispersion using different dispersants, or a combination of both. The chemical dispersants tested included Triton X-100, ammonium polymethacrylate and polyethyleneimine. The efficiency of the dispersion was measured using the zeta potential and through the determination of Ti using ICP-MS after acid digestion of the samples. Having optimized their protocol using stabilized samples in a pure water matrix, river and wastewater samples were spiked with nanoparticles and the optimal method was used in characterising these matrices. Zeta potential measurements indicated a very different dispersal and this was attributed to different ionic strength and the presence of organic (humic) substances. Unfortunately, these findings will not have come as a surprise to many workers in the field.

Slurry nebulization has been evaluated as a means of introducing multi-walled carbon nanotubes to ICP-OES for the determination of Fe.287 These workers also resorted to use of a dispersant (1% Triton X-100) and ultrasonication immediately prior to analysis to ensure homogeneity. The precision obtained using this approach was reported to be always better than 1.5% relative. Although some analytical assumptions were made, e.g. any Fe leached into solution of the slurry gave the same response as the Fe remaining in the nanotube, it does appear that a rapid, successful method has been developed.

The use of coupled capillary electrophoresis with ICP-MS (CE-ICP-MS) for the analysis of nanoparticles has been reported. In one study, Ag+ and Ag nanoparticles were separated in an attempt to determine shelf life and the effect of storage conditions on products.288 The addition of 2-mercaptopropionylglycine to the background electrolyte facilitated the separation of the Ag+ whilst maintaining its oxidation state. The LOD reported were 0.03 mg kg−1 for Ag+ and 0.05 mg kg−1 for Ag nanoparticles. Several nanoparticle coating types, e.g. citrate, lipoic acid, PVP and bovine serum albumin (BSA) were determined successfully. Particularly good recoveries (>93%) were observed for Ag+ and for particles coated with BSA. The method developed was applied to the analysis of six commercially available dietary supplements, with the sum of the Ag+ and Ag nanoparticles being in good agreement with total Ag determined using ICP-MS after acid dissolution. In a separate investigation, ICP-MS was employed as an alternative detector to the standard UV-Vis method because of the poor sensitivity exhibited by the latter approach.289 Using CE-ICP-MS, Au nanoparticles could be detected with good stability and linearity down to a LOD of 2 × 10−15 M. They applied their method in research examining the interaction between the Au nanoparticles and the main blood transporting protein, HSA.

The use of ETV-ICP-OES for the determination of Cl in nanopowder samples290 and of impurities in Ag nanoparticles291 has been reported. In the first example, a small amount of nano-material was weighed accurately into a tungsten boat furnace and a modifier solution of aqueous or alcoholic potassium hydroxide added. The ETV device was attached to the ICP-OES instrument and the temperature program started. The analyte was transported to the plasma in a stream of argon and hydrogen. Calibration was carried out using external aqueous standards analysed the same way. Since the analyte was separated from the sample matrix, few interferences were observed. In addition, because the sample was added as a dry powder, the plasma operated under dry conditions, enabling the discharge energy to be focused on exciting the analyte. Consequently, the LOD for Cl was very low (170 ng g−1) when 60 mg of sample was used. The precision reported for the measurement (n = 16) for 100 ng of Cl was 8.7% relative. The method was applied to several sample types including copper, gold, iron(III) oxide and silver nanoparticles. The other paper291 reported the use of a similar device for the determination of P, S and Si in silver nanoparticles. The authors stated that since the whole sample was vaporized into the plasma, there was no need for sample weighing because the analyte signals could be ratioed against the Ag matrix signal. An additional advantage was that no additional sample pretreatment was required. Sample throughput was 35 h−1 and LODs were given as 15, 4.2 and 62 μg g−1 for Si, P and S, respectively.

An ultra-sensitive method of speciating Ag+ and Ag nanoparticles was reported.292 Mixing cadmium telluride nano-crystals with the sample caused the Ag+ ions in solution to bombard and explode the nanocrystals resulting in the formation of a 40-fold excess of Cd2+ in less than a minute. This released Cd was then reduced to a volatile species using sodium tetrahydroborate and then the vapour produced, detected using either AFS or ICP-MS allowing the indirect determination of Ag+ ions. Given the enhancement obtained and the fact that vapour generation also enhances sensitivity, the LOD obtained when using ICP-MS was 0.0003 μg L−1; approximately 100 times better than normal. The bombardment and explosion reaction did not occur for Ag nanoparticles thereby facilitating the measurement of ionic species. The procedure was rapid, had high sensitivity, was simple and did not use any organic chemicals. Precision was reported to be better than 2.5% relative at a concentration of 0.5 μg L−1, regardless of which detector was used.

A novel method of Au particle characterization employing thin layer chromatography (TLC)-LA-ICP-MS was reported.293 Ionic Au was separated from Au nanoparticles by using TLC with a mobile phase of acetyl acetone/butyl alcohol/triethylamine (6[thin space (1/6-em)]:[thin space (1/6-em)]3[thin space (1/6-em)]:[thin space (1/6-em)]1, v/v). The Au in each band could then be quantified using LA-ICP-MS. In addition, by changing the mobile phase to phosphate buffer (0.2 M, pH 6–8)/Triton X-114 (0.4%)/and EDTA (10 mM), different sized Au nanoparticles could be separated. The separation of nanoparticles showed good reproducibility with retardation increasing linearly with decreasing size. The LODs were in the tens of pg range and the relative precisions reported for the measurement of 30 ng of Au nanoparticle were 6.3%, 5.9% and 8.3% for 13, 34 and 47 nm particles, respectively.

Another method capable of distinguishing between nanoparticles and dissolved ions is size exclusion chromatography (SEC)-ICP-MS.294 Quantum dots have some of the smallest particle sizes (2–10 nm) of all nanoparticles and may therefore leach metal ions into waters more readily. Samples of cadmium selenide/zinc sulfide quantum dots were analysed and the associated ions leached from them detected. The SEC columns were selected to have the smallest pore size available and an eluent composition was chosen that prevented losses of ions to the polymer surface. Consequently, the mobile phase used both ammonium lauryl sulfate and EDTA. The LODs reported were between 0.2 and 2 μg L−1 for Cd2+ and Zn2+ for the cation and particulate phases and the linear range spanned 2–3 orders of magnitude. The authors also extended the study to Au nanoparticles (5, 10, 20 and 50 nm) and Au3+. These were also separated successfully, demonstrating the method's general applicability. The data obtained using SEC-ICP-MS were comparable to those obtained using centrifuge ultra-filtration.

The use of methods capable of characterizing nanoparticles in the solid dilution form, directly were described in two papers. The first of these used grazing emission X-ray fluorescence (GEXRF).295 The particulates were deposited on a flat surface and the instrumental setup was able to determine the composition, shape and average size of the nanoparticles. The authors attributed the success of this approach to the lack of scanning required in their setup. An additional advantage of the method was that the data were obtained in a very short time period, hence minimizing the exposure of the sample to radiation. The use of a variant of LIBS during the flame synthesis of titanium dioxide nanoparticles and also been reported.296 Excitation from the third harmonic of a Nd:YAG laser (354.71 nm) broke down the flame-synthesized TiO2 particle in situ, and then subsequently resonantly excited the electrons leading to a characteristic emission of Ti at 497.534 nm. Although short-lived, the emission at this wavelength reached a maximum quicker, leading to a short-lived emission that was more intense than other emission signals. A low intensity laser excitation was required (30 mJ per pulse) so only the nanoparticle phase was broken down, forming nano-plasmas. This led to the authors naming the technique “phase selective” LIBS.

3.6 Polymers and composites. In this review period, activities relating to the analysis of polymers and composites have fallen into two categories: (a); the leaching of metals from food packaging materials and (b) the development of new analytical techniques. As always, there is a necessity to ensure that valid analytical data are being obtained and so there have also been a few studies concerning the development or re-testing of CRMs and reports on the results of inter-laboratory comparisons.

Two papers have reported the preparation or analysis of a CRM. The effects of long term X-ray irradiation on Cr and Hg in a polypropylene disk (NMIJ CRM 8136-a) were reported.297 Measurements using an EDXRF instrument over 430 h revealed that the Cr/Pb decreased whereas the Hg/Pb stayed constant. This implied that there was a loss of the Cr, with time. The Cr had been added as an organic compound during preparation of the CRM and it was thought that the phenomenon may be related with this. Measurements over 120 h using a WDXRF instrument demonstrated a similar trend. The second paper discussed the preparation of candidate reference materials for the determination of P-containing flame retardants in styrene-based polymers.298 Since P-containing flame retardants are now preferred to the brominated versions, validation materials are required for their determination. Accordingly, materials containing resorcinol-bis-(diphenylphosphate), bisphenol A bis(diphenyl phosphate), triphenyl phosphate and triphenyl phosphine oxide were prepared. The polymer materials prepared containing the retardants were: polycarbonate and acrylonitrile-co-butadiene-co-styrene, and blends of polystyrene with polyphenylene oxide. As well as the usual homogeneity and thermal stability tests, the materials were also analysed using ICP-OES, NMR and FTIR to determine the concentration of the flame retardants.

The results of inter-laboratory comparisons for analytes in food contact polymers have been published in two papers. In the first, 18 laboratories analysed three test solutions that were extracts from polyethylene terephthalate for their Ge and Sb content.299 A range of analytical techniques (GFAAS, ICP-OES and ICP-MS) were used by the different laboratories during the study. For the GFAAS and ICP-OES results, the ‘trueness’ (closeness to the known answer), repeatability and reproducibility were given in the ranges 98–107%, 1.7–7.5% and 2.0–18.8% respectively. This was regarded as being acceptable for the testing specifications. The results from some labs using ICP-MS were higher for Sb than the amount that had been added. The authors stated that this was because the Sb became adsorbed to glassware in the standards at lower concentration and that, therefore, strict control of the concentrations used was necessary. Despite this, the ICP-MS values for the trueness, repeatability and reproducibility were 99–106%, 0.7–2.2% and 2.2–10.5%. In a very similar study, extract solutions from food contact rubber products were tested for their Zn content.300 Again, 18 laboratories used the same range of detection techniques to determine the Zn in water and in 4% acetic acid solution. The same analytical performance metrics (trueness, repeatability and reproducibility) yielded values of 97–103%, 0.7–4.9% and 1.7–8.9% respectively, which was again deemed fit for purpose.

A review of Sb and phthalate esters in polyethylene terephthalate bottled drinking waters containing 125 references was prepared.301 The review commented on the source of the contamination, the analytical methods used for the determination and then discussed the effects of storage time, exposure to heat and light, sample pH and the volume of the container. It was commented that the determination of the phthalate esters can be confounded by laboratory cross-contamination. Both unsurprisingly and yet reassuringly, it was concluded that drinking water stored in PET bottles does not possess genotoxic or estrogenic activity.

The speciation of Sb in leaching solutions from plastics has been reported.302 A dispersive liquid–liquid microextraction using the chelating reagent 1,2,6-hexanetriol trithioglycolate was employed to combine with SbIII so that it could pass into the organic phase. The SbIII was then determined in this phase using GFAAS. The reagent does not combine with SbV, so this was determined by subtraction from total Sb after the SbV had been reduced to SbIII by the addition of L-cysteine. Parameters such as pH, reagent concentration, volumes and types of dispersive solvents were all optimized. Under optimal conditions, the calibration was found to be linear from 0.26–3.2 μg L−1 with a LOD reported of 27 ng L−1. An enrichment factor of 26 was obtained and precision was given as 6.8% relative at a level of 0.52 μg L−1 SbIII.

The release of silver nanoparticles from plastic food packaging into food simulants has been considered in two publications.303,304 Both papers used a setup that was in accordance with the European Commission Directive (EU 10/2011). In the first example,303 ultra-pure water, 10% ethanol and 3% acetic acid were used as simulants and were used for 10 days at 40 °C. The amount of Ag leached into the simulants was determined using ICP-MS. The size of the particles was determined using both TEM-EDS and single particle ICP-MS. The total mass and median size of released Ag particles was highest in the 3% acetic acid simulant for three of the four food container brands tested. Total Ag ranged from 13 to 42 μg g−1 and was highest in the 3% acetic acid simulant for all four brands. Over the 10 day test period, up to 3.1 ng cm−2 Ag was released from the containers, leading the authors to conclude that Ag is especially leachable from these containers into acidic foods. The other study investigated Ag leaching from low density polyethylene food packaging.304 A range of temperatures and timing conditions were employed. The effects of microwave heating were also tested. It was reported that Ag levels were found to be significantly higher using microwave heating than for the same temperature and time in a conventional oven. Measurement of leached Ag was achieved using ICP-OES and confirmation that nanoparticulate Ag was present was obtained using SEM.

New methods for the determination of elements in polymers have appeared in the literature in the year under review. Many of these have focused on determination of the analytes in the solid material directly to avoid high temperature or pressure digestion/dissolution procedures. It is worth noting in this context that XRF has for many decades been employed for such applications and can routinely achieve LODs in the low μg g−1 range for many elements. However, there are few reports of the use of this well established technique appearing in the literature. In this context it is a little surprising, given the practical problems involved in accurately weighing out mg levels of sample, that solid sampling GFAAS was one of the most common techniques reported in the last year for direct analysis of plastics. This approach was used for the determination of Sb in PET containers,305 Pb in plastic toys306 and Pb in plastic food packaging.307 Thus de Jesus et al.305 obtained total Sb contents of between 194 and 323 mg kg−1 with a precision of typically better than 10% RSD. Leach tests were also conducted in this work using 3% acetic acid, red wine and soft drink as extraction media. It was reported that leached Sb was < LOD (1.0 μg L−1), even after 10 days of contact. The other two applications reported involved the weighing of sub-mg levels of sample into a high resolution, continuum source GFAAS instrument. In the first of these Pb was determined in plastic food packaging.307 A mixed magnesium nitrate–palladium nitrate modifier was used. The Pb content found in the packaging ranged from 16 to 793 μg kg−1. Some samples were also analysed using ICP-MS to ensure valid data were being produced. Results obtained using the two techniques were found to be in good agreement. A LOD of 4.9 μg kg−1 was achieved using the solid sampling GFAAS method. Relative precision was reported in the range 2.7–18.8%, which was marginally worse than that obtained for ICP-MS (2.1–13.3%). In the second application, Pb in toys was determined by weighing between 0.05 and 0.7 mg of toy material directly into the atomizer.306 The Pb was determined at 217 nm and use of a mixed Pd–Mg modifier enabled char and atomization temperatures of 1000 and 2200 °C to be utilised. Method validation was demonstrated by successful analysis of the CRM ERM-EC680K. The use of gas stop conditions during atomization yielded LOD of 0.037 mg kg−1. The use of gas flow conditions, to assist in the removal of the matrix from the atomiser was found, unsurprisingly, to affect the sensitivity of the method and an LOD of 0.93 mg kg−1 was reported. The amount of Pb found in the toys ranged from 0.06 to 9.12 mg kg−1.

A method has been described for solid sampling of plastics prior to analysis by ETV-ICP-OES.308 Thus Cd, Cr, Cu, Fe and Sb were determined in different types of plastic using dichlorodifluoromethane as a gaseous halogenation modifier. The presence of this modifier improved sensitivity and decreased memory effects significantly. Calibration was achieved using external standards and standard additions, where aqueous standards were added directly to the sample boats. The absolute LODs obtained using the method ranged from 0.1 ng (for Cd) to 9 ng (for Fe) when using a 5 mg sample mass. The LODs achieved were sufficiently low to monitor these elements according to the European Directive for the Safety of Toys. The advantages of the proposed method included rapid sample throughput (20 h−1), low sample consumption, good accuracy and good precision. For method validation, samples were analysed using ICP-MS following a digestion. In addition, the plastic reference material BAM-H010 was also analysed for Cd, Cr and Pb.

Both Br and Sn have been determined in plastics using LA-ICP-MS.309 Calibration standards were prepared using the fused-disk method and the different laser operating parameters (energy, pulse rate, scan rate and spot size) were optimized using a central composite experimental design. Detection limits were given as 10 and 40 mg kg−1 for Br and Sn, respectively although, confusingly, the paper's abstract quoted these values as 1000 and 1600 mg kg−1. Relative precision data (n = 3) for the reference material ERM EC6812K were given as 9% and 6% and results were 770 ± 70 mg kg−1 and 86 ± 6 mg kg−1 for Br and Sn, respectively, which were in good agreement with certified values.

Negative ionization and positive ionization in radiofrequency pulsed glow discharge TOF-MS were compared during the determination of Br-, Cl-, F- and P-containing materials used in the polymer industry.310 Testing was carried out for these elemental constituents in PTFE, tetrabromobisphenol A, tris-2-chloroethyl-phosphate and four brominated flame retardants. The discharge gases used were argon and argon containing 4% oxygen. The negative ionization mode yielded higher sensitivity when compared with the positive mode. It was noted that the sensitivity appeared to be directly proportional to the electron affinity of the analyte. In negative ion mode, it was also possible for molecular information to be obtained. This was especially useful for the four similar brominated flame retardants. The presence of oxygen in the discharge gas caused severe problems which at the point of publication had not been addressed.

Chlorinated and brominated flame retardants have been used in polymer foams for many years and their presence in these building materials must be identified in order for them to be re-cycled. The standard method employs gas chromatography with either mass spectrometry or flame ionization detection. These approaches are time-consuming because of the extensive sample preparation required. Consequently, methods for rapid and direct atomic spectrometric measurement have been proposed based on PIXE311 and portable XRF.312 In the first application, PIXE was used to determine the halogens in 215 polyurethane foam samples. Data obtained using PIXE were compared with those from GC-MS for some of the samples, with excellent agreement obtained in these cases. The method could be completed in a fraction of the time and at much lower cost than the traditional method. In the second application, the brominated flame retardant hexabromocyclododecane (which has recently been added to the persistent organic pollutant list) or an alternative polymeric brominated flame retardant were determined by XRF in expanded and extruded polystyrene foam.312 Since the hexabromocyclododecane has now been banned but the polymeric material has not (yet), a rapid screening method is required to distinguish between the two. The portable XRF instrument was used to analyse 27 samples and was able to correctly identify all those that contained the banned substance. Relative precision for quantitative measurements was better than 14% and results obtained were in good agreement with those obtained using GC-FID.

A particularly novel application was described by Kumar et al.313 in which laser-induced breakdown spectrometry was used to measure the salt build-up on off-shore wind turbine blades remotely. A method for monitoring of the accretion of salt on blades is required to inform actions needed to minimize the risk of lightning strikes. A photometric device comprising a translational stage and an optical fibre was designed that enabled measurements to be made from between 1 and 100 m away. At the time of publication, the method was capable of identifying and quantifying the deposits up to a distance of 40 m. The instrumental setup was described in detail, with helpful schematic diagrams given. The salt content was determined by measurement of Na, using the conventional emission wavelength of 589 nm. Obviously Cl, the other elemental constituent of salt, could not be detected using this LIBS approach because of its relatively high first ionization energy.

In one of the few reports not involving solid sampling approaches, Kolasa et al. described a method for the determination of trace heavy elements (Cd, Cr, Hg and Pb) in polyethylene packaging materials following microwave assisted digestion of the samples.314 This paper is worth highlighting because of the novel approach used in the development of the sample pre-treatment procedure. Samples were first analysed using SEM-EDS to give a total concentration of each analyte. The microwave digestion program was iteratively modified until similar analytical results were obtained using FAAS and a Hg-specific instrument. The authors stated that once developed, the method was quick and simple, but it a little surprising that the sensitivity of the method proposed is sufficient for the detection of the normally encountered levels of these elements in polyethylene.

The effects of flame treatment on the surface characteristics of four injection moulded, automotive grade polypropylene samples were investigated.315 Changes to the O surface concentration were determined using XPS and was found to increase as a function of flame treatment. The extent of this O concentration increase was dependent on the type of polypropylene, with the glass-filled sample exhibiting less of an increase than a carbon pigmented and talc filled sample. Depth profiling indicated that modification of the surface to a depth of 7 nm occurred for one pass of flame treatment, but this increased to 15 nm when seven passes were made. The XPS analysis also indicated that initial attack of the polymer occurred at the pendant methyl group.

Finally, the potential of LIBS for the detection of tire tread particles was studied by Prochazka et al.316 One of the applications of real time and in situ detection of tire tread particles is the identification of optically imperceptible braking tracks at locations of road accidents. Thus LIBS was employed to identify Zn (added as zinc oxide) added into tire treads as an agent simplifying process of vulcanization. Measurement parameters including incident laser energy, gate width and gate delay were optimised. The accuracy of the approach was assessed by using ICP-MS and ICP-OES as reference techniques for the determination of Zn. The ultimate aim of the research was to develop a device for automated identification of braking tracks.

Glossary of terms

2DTwo dimensional
3DThree dimensional
AASAtomic absorption spectrometry
AESAuger electron spectrometry
AFFFAsymmetric field flow fractionation
AF4Asymmetric flow-field flow fractionation
AFSAtomic fluorescence spectrometry
AFMAtomic force microscopy
AMSAccelerator mass spectrometry
APMAtom probe microscopy
APTAtom probe tomography
ASTMAmerican Society for Testing of Materials
ATRAttenuated total reflection
BCRCommunity Bureau of Reference
CCDCharge coupled device
CECapillary electrophoresis
CRMCertified reference material
CPFAASCollinear photofragmentation atomic absorption spectrometry
CSContinuum source
CTComputerised tomography
CVCold vapour
CXRFCoincidence X-ray fluorescence
DADiscriminant analysis
DLSDynamic light scattering
DLTVDiode laser thermal vaporisation
DRCDynamic reaction cell
DSCDifferential scanning calorimetry
EBSElastic back scattering spectroscopy
EDAXEnergy dispersive X-ray analysis
EDSEnergy dispersive spectrometry
EDTAEthylenediamine tetraacetic acid
EDXRDEnergy dispersive X-ray diffraction
EDXRFEnergy dispersive X-ray fluorescence
EPMAElectron probe microanalysis
ERDAElastic recoil detection analysis
ESI-MSElectrospray ionisation mass spectrometry
ETAASElectrothermal atomic absorption spectrometry
ETVElectrothermal vaporisation
EXAFSExtended X-ray absorption fine structure
FAASFlame atomic absorption spectrometry
FFFField flow fractionation
FIFlow injection
FI-CVGFlow injection chemical vapour generation
FTIRFourier transform infrared
FWHMFull width at half maximum
GA-XRDGrazing incidence X-ray diffraction
GCGas chromatography
GD-MSGlow discharge mass spectrometry
GD-OESGlow discharge optical emission spectrometry
GI-SAXSGrazing incidence small angle X-ray scattering
GI-XRDGrazing incidence X-ray diffraction
GI-XRFGrazing incidence X-ray fluorescence
HGHydride generation
HPLCHigh performance liquid chromatography
HR-CS-AASHigh resolution continuum source atomic absorption spectrometry
hTISISHeated torch integrated sample introduction system
IAEAInternational Atomic Energy Agency
IBAIon beam analysis
ICPInductively coupled plasma
ICP-MSInductively coupled plasma mass spectrometry
ICP-OESInductively coupled plasma optical emission spectrometry
ICP-QMSInductively coupled plasma quadrupole mass spectrometry
ICP-TOF-MSInductively coupled plasma time-of-flight mass spectrometry
IDIsotope dilution
IL-DLLMEIonic liquid-dispersive liquid–liquid microextraction
IPInstitute of Petroleum
IRMSIsotope ration mass spectrometry
ISOInternational Organisation for Standardisation
LALaser ablation
LASILLaser ablation of sample in liquid
LCLiquid chromatography
LEISLow energy ion scattering
LIBSLaser induced breakdown spectrometry
LIFLaser induced fluorescence
LIPSLaser induced plasma spectroscopy
LODLimit of detection
LOQLimit of quantification
LTELocal thermal equilibrium
MALDI-TOFMatrix-assisted laser desorption ionisation time-of-flight
MCMulticollector
MEISMedium energy light scattering
MHCDMicro hollow glow discharge
MIPMicrowave induced plasma
MIP-AESMicrowave plasma atomic emission spectrometry
MSMass spectrometry
MCR-ALSMulti curve resolution-alternating least squares
MWTNMicrowave thermal nebuliser
NAANeutron activation analysis
NAARNeutron activation autoradiography
Nd:YAGNeodymium doped-yttrium aluminium garnet
Nd:YLFNeodymium doped-yttrium lithium fluoride
NDNeutron diffraction
NISTNational Institute of Standards and Technology
NMRNuclear magnetic resonance
NRANuclear reaction analysis
OESOptical emission spectrometry
PARCIPlasma assisted reaction chemical ionisation
PCAPrincipal components analysis
PDAPhase-Doppler anemometry
PGAAPrompt gamma neutron activation analysis
PGMPlatinum group metals
PIGEParticle induced gamma ray emission
PIXEParticle-induced X-ray emission
PSDAParticle size distribution analysis
PLSPartial least squares
PLS-DAPartial least squares discriminant analysis
ppbParts per billion
ppmParts per million
PVGPhotochemical vapour generation
RBSRutherford backscattering spectrometry
RDARegularised discriminant analysis
REERare earth elements
rfRadiofrequency
RIMSResonance ionisation mass spectrometry
RSDRelative standard deviation
SEMScanning electron microscopy
SEM-EDSScanning electron microscopy-energy dispersive spectrometry
SFSector field
SIFT-MSSelected ion flow tube mass spectrometry
SIMCASoft independent modelling of class analogy
SIMSSecondary ion mass spectrometry
SPSingle particle
SRSynchrotron radiation
SRMStandard reference material
SRSSynchrotron radiation source
SXRFSynchrotron X-ray fluorescence
STXMScanning transmission X-ray microscopy
TETrace element
TEMTransmission electron microscopy
TGAThermogravimetic analysis
TIMSThermal ionisation mass spectrometry
TLCThin layer chromatography
TPRTemperature programmed reduction
TXRFTotal reflection X-ray fluorescence
UOPUniversal Oil Products standards
USGSUnited States Geological Survey
UV-VisUltraviolet-visible
VOCVolatile organic carbon
VUVVacuum ultraviolet
WDXRFWavelength dispersive X-ray fluorescence
WC-AESTungsten coil atomic emission spectrometry
XAFSX-ray absorption fine structure spectrometry
XANESX-ray absorption near-edge structure
XASX-ray absorption spectroscopy
XPSX-ray photoelectron spectroscopy
XRDX-ray diffraction
XRFX-ray fluorescence
XRPDX-ray powder diffraction
XRRX-ray reflectometry

References

  1. S. Carter, A. Fisher, R. Garcia, B. Gibson, S. Lancaster, J. Marshallf and I. Whiteside, J. Anal. At. Spectrom., 2015, 30(11), 2249–2294 RSC.
  2. M. Edwards, J. Semmler, D. Guzonas, H. Q. Chen, A. Toor and S. Hoendermis, Nucl. Eng. Des., 2015, 288, 163–174 CrossRef CAS.
  3. T. Cain, S. B. Madden, N. Birbilis and J. R. Scully, J. Electrochem. Soc., 2015, 162(6), C228–C237 CrossRef CAS.
  4. Z. P. Yao, Q. X. Xia, H. Wei, D. Q. Li, Q. Sun and Z. H. Jiang, RSC Adv., 2015, 5(84), 68806–68814 RSC.
  5. M. S. Killian, S. Seiler, V. Wagener, R. Hahn, C. Ebensperger, B. Meyer and P. Schmuki, ACS Appl. Mater. Interfaces, 2015, 7(17), 9006–9014 CAS.
  6. V. Shkirskiy, P. Keil, H. Hintze-Bruening, F. Leroux, P. Vialat, G. Lefevre, K. Ogle and P. Volovitch, ACS Appl. Mater. Interfaces, 2015, 7(45), 25180–25192 CAS.
  7. L. Csedreki and R. Huszank, Nucl. Instrum. Methods Phys. Res., Sect. B, 2015, 348, 165–169 CrossRef CAS.
  8. X. L. Li, S. M. He, X. T. Zhou, Z. J. Li, Y. Zou, A. G. Li and X. H. Yu, Nucl. Sci. Tech., 2015, 26(3), 7 Search PubMed.
  9. S. Adamiak, N. Berchenko, W. Bochnowski, A. Dziedzic, M. Trzyna, S. Fadeyev and J. Cebulski, Thin Solid Films, 2015, 591, 311–315 CrossRef CAS.
  10. A. A. Shaltout and O. H. Abdelkader, Vacuum, 2015, 121, 105–112 CrossRef CAS.
  11. R. B. Figueira, C. J. R. Silva and E. V. Pereira, Surf. Coat. Technol., 2015, 265, 191–204 CrossRef CAS.
  12. L. Ren, J. Chong, A. Loya, Q. Kang, J. L. Stair, L. Nan and G. Ren, Mater. Technol., 2015, 30(B2), B86–B89 CAS.
  13. H. Y. Li, C. F. Dong, K. Xiao, X. G. Li and P. Zhong, Int. J. Electrochem. Sci., 2015, 10(12), 10173–10187 CAS.
  14. J. Feizabadi, J. V. Khaki, M. H. Sabzevar, M. Sharifitabar and S. A. Sani, Mater. Des., 2015, 84, 325–330 CrossRef CAS.
  15. K. Loeschner, C. F. Harrington, J. L. Kearney, D. J. Langton and E. H. Larsen, Anal. Bioanal. Chem., 2015, 407(16), 4541–4554 CrossRef CAS PubMed.
  16. D. Janis, A. Karasev and P. G. Jonsson, ISIJ Int., 2015, 55(10), 2173–2181 CrossRef CAS.
  17. C. Song, X. Gao and Y. Shao, Optik, 2016, 127(8), 3979–3983 CrossRef CAS.
  18. R. Ahmed, J. Iqbal and M. A. Baig, Laser Phys. Lett., 2015, 12(6), 6 Search PubMed.
  19. K. H. Li, L. B. Guo, C. M. Li, X. Y. Li, M. Shen, Z. Zheng, Y. Yu, R. F. Hao, Z. Q. Hao, Q. D. Zeng, Y. F. Lu and X. Y. Zeng, J. Anal. At. Spectrom., 2015, 30(7), 1623–1628 RSC.
  20. L. X. Sun, H. B. Yu, Z. B. Cong, Y. Xin, Y. Li and L. F. Qi, Spectrochim. Acta, Part B, 2015, 112, 40–48 CrossRef CAS.
  21. X. M. Lin, H. Li and Q. H. Yao, Plasma Sci. Technol., 2015, 17(11), 953–957 CrossRef.
  22. X. M. Lin, P. H. Chang, G. H. Chen, J. J. Lin, R. X. Liu and H. Yang, Plasma Sci. Technol., 2015, 17(11), 933–937 CrossRef.
  23. S. Kashiwakura and K. Wagatsuma, ISIJ Int., 2016, 55(11), 2391–2396 CrossRef.
  24. H. Y. Kong, L. X. Sun, J. T. Hu, Y. Xin and Z. B. Cong, Plasma Sci. Technol., 2015, 17(11), 964–970 CrossRef.
  25. A. Khaliq, M. A. Rhamdhani, G. A. Brooks and J. Grandfield, Metall. Mater. Trans. B, 2016, 47(1), 595–607 CrossRef CAS.
  26. S. D. Zhang, B. C. Zhang, W. Hang and B. L. Huang, Spectrochim. Acta, Part B, 2015, 107, 17–24 CrossRef CAS.
  27. P. Liu, R. Hai, D. Wu, Q. M. Xiao, L. Y. Sun and H. B. Ding, Plasma Sci. Technol., 2015, 17(8), 687–692 CrossRef.
  28. T. Takahashi, B. Thornton, K. Ohki and T. Sakka, Spectrochim. Acta, Part B, 2015, 111, 8–14 CrossRef CAS.
  29. S. Merk, C. Scholz, S. Florek and D. Mory, Spectrochim. Acta, Part B, 2015, 112, 10–15 CrossRef CAS.
  30. F. Sakamoto, T. Ashino and K. Wagatsuma, Bunseki Kagaku, 2015, 64(9), 689–693 CrossRef CAS.
  31. E. A. Mista, A. Stonert, A. Korman, J. J. Milczarek, I. Fijal-Kirejczyk, P. Kalbarczyk and A. Wisniewska, Acta Phys. Pol., A, 2015, 128(5), 815–817 CrossRef CAS.
  32. D. Lesigyarski, B. Zlateva, V. Lyubomirova, T. Stoyanov and I. Kuleff, ArcheoSciences, 2015, 39, 149–156 CrossRef.
  33. R. Muller, G. P. Brey, H. M. Seitz and S. Klein, Archaeol. Anthropol. Sci., 2015, 7(4), 473–485 CrossRef.
  34. Y. M. He, Z. X. Ling, Y. Zhou, F. Ahmad and F. F. Zhao, Spectrosc. Lett., 2016, 49(1), 37–43 CrossRef CAS.
  35. P. N. Nomngongo and J. C. Ngila, RSC Adv., 2015, 5(89), 72500–72507 RSC.
  36. S. M. Cruz, P. Tirk, F. M. Dalla Nora, L. Schmidt, H. Wiltsche, C. A. Bizzi, G. Knapp and E. M. M. Flores, Fuel, 2015, 160, 108–113 CrossRef CAS.
  37. C. S. Huber, M. G. R. Vale, B. Welz, J. B. Andrade and M. B. Dessuy, Spectrochim. Acta, Part B, 2015, 108, 68–74 CrossRef CAS.
  38. Y. M. He, F. F. Zhao, Y. Zhou, F. Ahmad and Z. X. Ling, Anal. Methods, 2016, 7(11), 4493–4501 RSC.
  39. H. A. Tekie, R. I. McCrindle, P. Marais and A. A. Ambushe, S. Afr. J. Chem., 2015, 68, 76–84 CrossRef CAS.
  40. J. I. Park, A. Al-Mutairi, A. M. J. Marafie, S. H. Yoon, I. Mochida and X. L. Ma, J. Ind. Eng. Chem., 2016, 34, 204–212 CrossRef CAS.
  41. G. T. Ventura, L. Gall, C. Siebert, J. Prytulak, P. Szatmari, M. Hurlimann and A. N. Halliday, Appl. Geochem., 2015, 59, 104–117 CrossRef CAS.
  42. X. W. Li, H. L. Yin, Z. Wang, Y. T. Fu, Z. Li and W. D. Ni, Spectrochim. Acta, Part B, 2015, 111, 102–107 CrossRef CAS.
  43. L. Zhang, Y. Gong, Y. F. Li, X. Wang, J. J. Fan, L. Dong, W. G. Ma, W. B. Yin and S. T. Jia, Spectrochim. Acta, Part B, 2015, 113, 167–173 CrossRef CAS.
  44. D. Redoglio, E. Golinelli, S. Musazzi, U. Perini and F. Barberis, Spectrochim. Acta, Part B, 2016, 116, 46–50 CrossRef CAS.
  45. S. C. Yao, J. L. Xu, K. J. Bai and J. D. Lu, Plasma Sci. Technol., 2015, 17(11), 938–943 CrossRef.
  46. M. R. Dong, D. Oropeza, J. Chirinos, J. J. Gonzalez, J. D. Lu, X. L. Mao and R. E. Russo, Spectrochim. Acta, Part B, 2015, 109, 44–50 CrossRef CAS.
  47. M. V. B. Krishna, K. Chandrasekaran, S. Chakravarthy and D. Karunasagar, Fuel, 2015, 158, 770–778 CrossRef.
  48. N. Mketo, P. N. Nomngongo and J. C. Ngila, RSC Adv., 2015, 5(49), 38931–38938 RSC.
  49. T. Vogt, D. Bauer, M. Neuroth and M. Ottto, Fuel, 2015, 152, 96–102 CrossRef CAS.
  50. A. T. Duarte, A. R. Borges, A. V. Zmozinski, M. B. Dessuy, B. Welz, J. B. de Andrade and M. G. R. Vale, Talanta, 2016, 146, 166–174 CrossRef CAS PubMed.
  51. C. Sanchez, C. P. Lienemann and J. L. Todoli, Spectrochim. Acta, Part B, 2016, 115, 16–22 CrossRef CAS.
  52. A. Virgilio, R. S. Amais, D. Schiavo and J. A. Nobrega, Energy Fuels, 2016, 29(7), 4339–4344 CrossRef.
  53. R. S. Amais, L. S. G. Teixeira and F. R. P. Rocha, Anal. Methods, 2015, 7(11), 4396–4418 RSC.
  54. I. N. B. Castilho, D. P. C. de Quadros, R. Mior, B. Welz, E. Carasek and D. L. G. Borges, Anal. Methods, 2015, 7(22), 9636–9640 RSC.
  55. A. I. Barros, K. Miranda, E. C. Ferreira and J. A. G. Neto, At. Spectrosc., 2015, 36(2), 102–107 CAS.
  56. F. Petrucci and O. Senofonte, Anal. Methods, 2015, 7(12), 5269–5274 RSC.
  57. M. A. Gondal, M. A. Dastageer, F. F. Al-Adel, A. A. Naqvi and Y. B. Habibullah, Opt. Laser Technol., 2015, 75, 99–104 CrossRef CAS.
  58. J. Wei, T. L. Zhang, J. Dung, L. W. Sheng, H. S. Tang, X. F. Yang and H. Li, Chem. Res. Chin. Univ., 2015, 31(6), 909–913 CrossRef CAS.
  59. E. Ytreberg, L. Lundgren, M. A. Bighiu and B. Eklund, Talanta, 2015, 143, 121–126 CrossRef CAS PubMed.
  60. E. Da Silva, A. M. David and A. Pejovic-Milic, X-Ray Spectrometry, 2015, 44(6), 451–457 CrossRef CAS.
  61. K. Sharafi, N. Fattahi, M. Pirsaheb, H. Yarmohamadi and M. F. Davil, Int. J. Cosmet. Sci., 2015, 37(5), 489–495 CrossRef CAS PubMed.
  62. Z. J. Zhao and Y. X. Duan, RSC Adv., 2015, 5(51), 40636–40646 RSC.
  63. A. C. McWilliams, A. Martin, M. A. Levine, K. E. Levine, L. Felder, D. J. Young and J. M. Harrington, Anal. Lett., 2015, 48(13), 2122–2135 CrossRef CAS.
  64. X. D. Zhao, D. M. Dong, W. G. Zheng, L. Z. Jiao and P. C. Han, RSC Adv., 2015, 5(108), 89164–89170 RSC.
  65. N. Elsherbiny and O. A. Nassef, Sci. Justice, 2015, 55(4), 254–263 CrossRef PubMed.
  66. J. Lee, M. J. Kim, E. van Elslande, P. Walter and Y. Lee, J. Nanosci. Nanotechnol., 2015, 15(11), 8701–8705 CrossRef CAS PubMed.
  67. P. Targowski, M. Pronobis-Gajdzis, A. Surmak, M. Iwanicka, E. A. Kaszewska and M. Sylwestrzak, Stud. Conserv., 2015, 60, S167–S177 CrossRef CAS.
  68. M. F. Alberghina, R. Barraco, M. Brai, D. Fontana and L. Tranchina, Period. Mineral., 2015, 84(3), 569–589 Search PubMed.
  69. S. Panighello, A. Kavcic, K. Vogel-Mikus, N. H. Tennent, A. Wallert, S. B. Hocevar and J. T. van Elteren, Microchem. J., 2016, 125, 105–115 CrossRef CAS.
  70. I. Reiche, K. Muller, E. Mysak, M. Eveno and B. Mottin, Appl. Phys. A: Mater. Sci. Process., 2015, 121(3), 903–913 CrossRef CAS.
  71. Z. E. Voras, K. deGhetaldi, M. B. Wiggins, B. Buckley, B. Baade, J. L. Mass and T. P. Beebe, Appl. Phys. A: Mater. Sci. Process., 2015, 121(3), 1015–1030 CrossRef CAS PubMed.
  72. T. Trojek and D. Trojkova, Radiat. Phys. Chem., 2015, 116, 321–325 CrossRef CAS.
  73. F. L. F. Silva, T. A. O. Duarte, L. S. Melo, L. P. D. Ribeiro, S. T. Gouveia, G. S. Lopes and W. O. Matos, Talanta, 2016, 146, 188–194 CrossRef CAS PubMed.
  74. K. Ishii, T. Takekawa, Y. Ohmae, Y. Nishiwaki and K. Gamoh, Bunseki Kagaku, 2015, 64(12), 867–874 CrossRef CAS.
  75. S. Kaczala, A. B. Costa, E. L. Posselt, J. S. Barin, E. M. M. Flores and V. L. Dressler, J. Braz. Chem. Soc., 2015, 26(3), 475–483 CAS.
  76. A. Turner, E. R. Kearl and K. R. Solman, Sci. Total Environ., 2016, 544, 460–466 CrossRef CAS PubMed.
  77. F. B. Gonzaga, W. F. D. Rocha and D. N. Correa, Spectrochim. Acta, Part B, 2015, 109, 24–30 CrossRef CAS.
  78. S. Sungur and F. Gulmez, J. Spectrosc., 2015, 2015, 640271 Search PubMed.
  79. A. Leclercq, A. Nonell, J. L. T. Torro, C. Bresson, L. Vio, T. Vercouter and F. Chartier, Anal. Chim. Acta, 2015, 885, 33–56 CrossRef CAS PubMed.
  80. H. P. Wang, C. S. Minardi, H. Badiei, K. Kahen and K. Jorabchi, Analyst, 2015, 140(24), 8177–8185 RSC.
  81. K. E. Brown, M. T. Greenfield, S. D. McGrane and D. S. Moore, Anal. Bioanal. Chem., 2016, 408(1), 35–47 CrossRef CAS PubMed.
  82. E. N. Rao, S. Sunku and S. V. Rao, Appl. Spectrosc., 2015, 69(11), 1342–1354 CrossRef CAS PubMed.
  83. J. Serrano, J. Moros and J. J. Laserna, J. Anal. At. Spectrom., 2015, 30(11), 2343–2352 RSC.
  84. S. Civis, M. Civis, K. Sovova, K. Dryahina, J. Kubista, P. Skrehot, P. Spanel and M. Kyncl, Anal. Methods, 2016, 8(5), 1145–1150 Search PubMed.
  85. G. Li, D. Schoneker, K. L. Ulman, J. J. Sturm, L. M. Thackery and J. F. Kauffman, J. Pharm. Sci., 2015, 104(12), 4197–4206 CrossRef CAS PubMed.
  86. D. A. Goncalves, J. Y. Gu, M. C. dos Santos, B. T. Jones and G. L. Donati, J. Anal. At. Spectrom., 2015, 30(6), 1395–1399 RSC.
  87. J. P. Mondia, F. Goh, P. A. Bryngelson, J. M. MacPhee, A. S. Ali, A. Weiskopf and M. Lanan, Anal. Methods, 2015, 7(8), 3545–3550 RSC.
  88. R. M. Nejem, M. M. Issa, M. H. Al-Kholy, A. A. Saleh, A. Abu Shanab, R. I. S. van Staden and H. Y. Aboul-Enein, RSC Adv., 2015, 5(70), 57164–57170 RSC.
  89. D. J. Duke, A. L. Kastengren, N. Mason-Smith, Y. Chen, P. M. Young, D. Traini, D. Lewis, D. Edgington-Mitchell and D. Honnery, Pharm. Res., 2016, 33(4), 816–825 CrossRef CAS PubMed.
  90. M. A. Gondal, Y. B. Habibullah, L. E. Oloore and M. A. Iqbal, Appl. Opt., 2015, 54(17), 5560–5567 CrossRef PubMed.
  91. E. F. Batista, A. D. Augusto and E. R. Pereira, Talanta, 2016, 150, 206–212 CrossRef CAS PubMed.
  92. S. H. Kim, Y. Lim, E. Hwang and Y. H. Yim, Anal. Methods, 2016, 8(4), 796–804 RSC.
  93. S. Y. Ng, F. Dewi, J. Wang, L. P. Sim, R. Y. C. Shin and T. K. Lee, Int. J. Mass Spectrom., 2015, 389, 59–65 CrossRef CAS.
  94. V. G. Bairi, J. H. Lim, I. R. Quevedo, T. K. Mudalige and S. W. Linder, Spectrochim. Acta, Part B, 2016, 116, 21–27 CrossRef CAS PubMed.
  95. J. Menneveux, F. Wang, S. Lu, X. S. Bai, V. Motto-Ros, N. Gilon, Y. P. Chen and J. Yu, Spectrochim. Acta, Part B, 2015, 109, 9–15 CrossRef CAS.
  96. A. M. Cuevas, F. Bernardini, A. Gianoncelli and C. Tuniz, X-Ray Spectrom., 2015, 44(3), 105–115 CrossRef.
  97. P. Vandenabeele and M. K. Donais, Appl. Spectrosc., 2016, 70(1), 27–41 CrossRef CAS PubMed.
  98. D. Syvilay, N. Wilkie-Chancellier, B. Trichereau, A. Texier, L. Martinez, S. Serfaty and V. Detalle, Spectrochim. Acta, Part B, 2015, 114, 38–45 CrossRef CAS.
  99. P. M. Wrobel, P. Fraczek and M. Lankosz, Anal. Chem., 2016, 88(3), 1661–1666 CrossRef CAS PubMed.
  100. C. Y. Tian, X. L. Ding, J. W. Yin and Y. X. Duan, Chin. J. Anal. Chem., 2016, 44(1), 8–12 CAS.
  101. O. A. Dal'nova, A. P. Dmitrieva and Y. A. Karpov, Inorg. Mater., 2015, 51(14), 1416–1419 CrossRef.
  102. O. N. Batuk, S. D. Conradson, O. N. Aleksandrova, H. Boukhalfa, B. E. Burakov, D. L. Clark, K. R. Czerwinski, A. R. Felmy, J. S. Lezama-Pacheco, S. N. Kalmykov, D. A. Moore, B. F. Myasoedov, D. T. Reed, D. D. Reilly, R. C. Roback, I. E. Vlasova, S. M. Webb and M. P. Wilkerson, Environ. Sci. Technol., 2015, 49(11), 6474–6484 CrossRef CAS PubMed.
  103. J. W. Ha and S. J. Lee, J. Ind. Eng. Chem., 2015, 28, 328–333 CrossRef CAS.
  104. F. Cid, P. Kochifas, H. D. Mansilla, P. Santander, J. Yáñez and D. Amarasiriwardena, Microchem. J., 2016, 125, 29–33 CrossRef CAS.
  105. A. Duarte, L. M. Silva, C. T. de Souza, E. M. Stori, L. A. Boufleur, L. Amaral and J. F. Dias, Nucl. Instrum. Methods Phys. Res., Sect. B, 2015, 348, 170–173 CrossRef CAS.
  106. A. Tarifa and J. R. Almirall, Sci. Justice, 2015, 55(3), 168–175 CrossRef PubMed.
  107. A. C. Lindstrom, J. Hoogewerff, J. Athens, Z. Obertova, W. Duncan, N. Waddell and J. Kieser, Forensic Sci. Int., 2015, 253, 103–111 CrossRef CAS PubMed.
  108. M. H. Morcali, S. Akman and O. Yucel, Chem. Eng. Commun., 2015, 202(9), 1145–1154 CrossRef CAS.
  109. J. Li, Y. Liu and M. D. Fang, Rare Met. Mater. Eng., 2015, 44(4), 871–874 Search PubMed.
  110. P. S. R. Devi, A. C. Trupti, A. Nicy, A. A. Dalvi, K. K. Swain, D. N. Wagh and R. Verma, Anal. Methods, 2015, 7(12), 5345–5351 RSC.
  111. C. H. Choi, C. Baldizzone, J. P. Grote, A. K. Schuppert, F. Jaouen and K. J. J. Mayrhofer, Angew. Chem., Int. Ed., 2015, 54(43), 12753–12757 CrossRef CAS PubMed.
  112. A. Seifitokaldani, O. Savadogo and M. Perrier, Int. J. Hydrogen Energy, 2015, 40(33), 10427–10438 CrossRef CAS.
  113. B. Bozzini, P. Bocchetta, B. Aleman, M. Amati, A. Gianoncelli, L. Gregoratti, H. Sezen, A. Taurino and M. Kiskinova, J. Mater. Chem. A, 2015, 3(37), 19155–19167 CAS.
  114. B. Bozzini, P. Bocchetta and A. Gianoncelli, Energies, 2015, 8(8), 8145–8164 CrossRef CAS.
  115. A. Gianoncelli, I. Sgura, P. Bocchetta, D. Lacitignola and B. Bozzini, X-Ray Spectrom., 2015, 44(4), 263–275 CrossRef CAS.
  116. S. W. T. Price, K. Geraki, K. Ignatyev, P. T. Witte, A. M. Beale and J. F. W. Mosselmans, Angew. Chem., Int. Ed., 2015, 54(34), 9886–9889 CrossRef CAS PubMed.
  117. S. Kalirai, U. Boesenberg, G. Falkenberg, F. Meirer and B. M. Weckhuysen, ChemCatChem, 2015, 7(22), 3674–3682 CrossRef CAS PubMed.
  118. S. D. Souza, L. L. Francois, A. R. Borges, M. G. R. Vale and R. G. O. Araujo, Spectrochim. Acta, Part B, 2015, 114, 58–64 CrossRef.
  119. B. S. Marangoni, K. S. G. Silva, G. Nicolodelli, G. S. Senesi, J. S. Cabral, P. R. Villas-Boas, C. S. Silva, P. C. Teixeira, A. R. A. Nogueira, V. M. Benites and D. Milori, Anal. Methods, 2016, 8(1), 78–82 RSC.
  120. N. H. Roslan, M. Ismail, Z. Abdul-Majid, S. Ghoreishiamiri and B. Muhammad, Construct. Build. Mater., 2016, 104, 16–24 CrossRef.
  121. S. Maheswaran, S. Kalaiselvam, S. Karthikeyan, C. Kokila and G. S. Palani, Cem. Concr. Compos., 2016, 66, 57–65 CrossRef CAS.
  122. M. A. Sanjuan, C. Argiz, J. C. Galvez and A. Moragues, Construct. Build. Mater., 2015, 96, 55–64 CrossRef.
  123. K. Peng, H. M. Yang and J. Ouyang, Powder Technol., 2015, 286, 678–683 CrossRef CAS.
  124. O. Gencel, Energ. Build., 2015, 102, 217–224 CrossRef.
  125. Q. Shan, X. L. Zhang, Y. Zhang, W. B. Jia, Y. S. Ling, D. Q. Hei and S. N. Chu, Spectrosc. Lett., 2015, 49(3), 188–193 Search PubMed.
  126. B. Savija, E. Schlangen, J. Pacheco, S. Millar, T. Eichler and G. Wilsch, J. Adv. Concr. Technol., 2014, 12(10), 425–442 CrossRef.
  127. S. Millar, G. Wilsch, T. Eichler, C. Gottlieb and H. Wiggenhauser, Beton- Stahlbetonbau, 2015, 110(8), 501–U510 CrossRef.
  128. J. J. Fan, L. Zhang, X. Wang, Y. F. Li, Y. Gong, L. Dong, W. G. Ma, W. B. Yin, Z. Wang, Z. Li, X. J. Zhang and S. T. Jia, Plasma Sci. Technol., 2015, 17(11), 897–903 CrossRef.
  129. H. N. Kim, M. P. Hawron, W. Hassan, E. H. Jordan and M. W. Renfro, Surf. Coat. Technol., 2015, 270, 86–94 CrossRef CAS.
  130. X. N. Liu, Q. Ma, S. S. Liu, X. Y. Shi, Q. Zhang, Z. S. Wu and Y. J. Qiao, Spectrochim. Acta, Part A, 2015, 151, 547–552 CrossRef CAS PubMed.
  131. C. Aragón and J. A. Aguilera, Spectrochim. Acta, Part B, 2015, 110, 124–133 CrossRef.
  132. S. Z. Chen, S. P. Zhu and D. B. Lu, At. Spectrosc., 2015, 36(5), 196–201 CAS.
  133. W. M. Wu, H. L. Liu and T. F. Zheng, Chin. J. Anal. Chem., 2015, 43(5), 697–702 CAS.
  134. N. I. Petrova, D. Y. Troitskii, I. I. Novoselov and A. I. Saprykin, Inorg. Mater., 2015, 51(6), 559–562 CrossRef CAS.
  135. E. Bolea-Fernandez, L. Balcaen, M. Resano and F. Vanhaecke, J. Anal. At. Spectrom., 2016, 31(1), 303–310 RSC.
  136. S. G. Nielsen, J. D. Owens and T. J. Horner, J. Anal. At. Spectrom., 2016, 31(2), 531–536 RSC.
  137. J. Wang, T. X. Ren, H. Lu, T. Zhou and Y. J. Zhou, J. Anal. At. Spectrom., 2015, 30(6), 1377–1385 RSC.
  138. D. Papenmeier, Propellants, Explos., Pyrotech., 2015, 40(6), 927–930 CrossRef CAS.
  139. V. D'Ippolito, G. B. Andreozzi, U. Halenius, H. Skogby, K. Hametner and D. Gunther, Phys. Chem. Miner., 2015, 42(6), 431–439 CrossRef.
  140. A. Liedl, C. Polese, D. Hampai, G. Della Ventura, S. B. Dabagov, A. Marcelli, F. Bellatreccia and A. Cavallo, X-Ray Spectrom., 2015, 44(4), 201–203 CrossRef CAS.
  141. U. A. Barbosa, I. F. dos Santos, S. L. C. Ferreira and A. M. P. dos Santos, RSC Adv., 2015, 5(67), 54046–54052 RSC.
  142. L. Husakova, I. Urbanova, T. Sidova and T. Mikysek, Anal. Methods, 2015, 7(12), 5019–5027 RSC.
  143. A. R. Tsygankova, O. V. Lundovskaya and A. I. Saprykin, J. Anal. Chem., 2016, 71(2), 179–184 CrossRef CAS.
  144. Y. Airan, A. Sengupta, S. K. Thulasidas and V. Natarajan, At. Spectrosc., 2015, 36(5), 221–235 CAS.
  145. N. Chiarelli, D. Miriello, G. Bianchi, G. Fichera, M. Giamello and I. T. Memmi, Construct. Build. Mater., 2015, 96, 442–460 CrossRef.
  146. G. Leone, A. De Vita, A. Magnani and C. Rossi, Thermochim. Acta, 2016, 624, 86–94 CrossRef CAS.
  147. D. Miriello, F. Antonelli, C. Apollaro, A. Bloise, N. Bruno, M. Catalano, S. Columbu, G. M. Crisci, R. De Luca, M. Lezzerini, S. Mancuso and A. La Marca, Period. Mineral., 2015, 84(3), 497–517 Search PubMed.
  148. T. Akyuz, S. Akyuz and A. Gulec, Spectrochim. Acta, Part A, 2015, 149, 744–750 CrossRef CAS PubMed.
  149. M. Singh and B. R. Arbad, Construct. Build. Mater., 2015, 82, 142–154 CrossRef.
  150. V. Crupi, G. Galli, M. F. La Russa, F. Longo, G. Maisano, D. Majolino, M. Malagodi, A. Pezzino, M. Ricca, B. Rossi, S. A. Ruffolo and V. Venuti, Appl. Surf. Sci., 2015, 349, 924–930 CrossRef CAS.
  151. R. De Luca, D. Miriello, A. Pecci, S. Dominguez-Bella, D. Bernal-Casasola, D. Cottica, A. Bloise and G. M. Crisci, Geoarchaeology, 2015, 30(4), 330–351 CrossRef.
  152. S. K. Aggarwal, Curr. Sci., 2016, 110(5), 782–791 Search PubMed.
  153. S. Boulyga, S. Konegger-Kappel, S. Richter and L. Sangely, J. Anal. At. Spectrom., 2015, 30(7), 1469–1489 RSC.
  154. M. Krachler, R. Alvarez-Sarandes and S. Van Winckel, J. Radioanal. Nucl. Chem., 2015, 304(3), 1201–1209 CrossRef CAS PubMed.
  155. B. C. Russell, I. W. Croudace and P. E. Warwick, Anal. Chim. Acta, 2015, 890, 7–20 CrossRef CAS PubMed.
  156. J. J. Horkley, K. P. Carney, E. M. Gantz, J. E. Davies, R. R. Lewis, J. P. Crow, C. A. Poole, T. S. Grimes and J. J. Giglio, J. Radioanal. Nucl. Chem., 2015, 305(1), 267–275 CrossRef CAS.
  157. K. J. Mathew, R. M. Essex, C. Gradle and U. Narayanan, J. Radioanal. Nucl. Chem., 2015, 305(1), 277–282 CrossRef CAS.
  158. S. Mialle, S. Richter, C. Hennessy, J. Truyens, U. Jacobsson and Y. Aregbe, J. Radioanal. Nucl. Chem., 2015, 305(1), 255–266 CrossRef CAS.
  159. A. Kumar, A. Sengupta, N. D. Dahale, S. K. Thulasidas, M. Charyulu and V. Natarajan, J. Radioanal. Nucl. Chem., 2015, 306(2), 555–561 CrossRef CAS.
  160. C. J. Soares, R. Mertz-Kraus, S. Guedes, D. F. Stockli and T. Zack, Geostand. Geoanal. Res., 2015, 39(3), 305–313 CrossRef CAS.
  161. B. A. Dittmann, T. J. Dunai, A. Dewald, S. Heinze, C. Feuerstein, E. Strub, L. K. Fifield, M. B. Froehlich, S. G. Tims, A. Wallner and M. Christl, Nucl. Instrum. Methods Phys. Res., Sect. B, 2015, 361, 327–331 CrossRef CAS.
  162. K. J. Mathew, R. D. Canaan, C. Hexel, J. Giaquinto and A. M. Krichinsky, Int. J. Mass Spectrom., 2015, 389, 47–53 CrossRef CAS.
  163. S. Dhara, P. Prabhat and N. L. Misra, Anal. Chem., 2015, 87(20), 10262–10267 CrossRef CAS PubMed.
  164. K. G. McIntosh, S. D. Reilly and G. J. Havrilla, Spectrochim. Acta, Part B, 2015, 110, 91–95 CrossRef CAS.
  165. M. Krachler and R. Alvarez-Sarandes, J. Anal. At. Spectrom., 2015, 30(7), 1655–1662 RSC.
  166. F. Esaka, D. Suzuki, T. Yomogida and M. Magara, Anal. Methods, 2016, 8(7), 1543–1548 RSC.
  167. Y. Miyamoto, D. Suzuki, F. Esaka and M. Magara, Anal. Bioanal. Chem., 2015, 407(23), 7165–7173 CrossRef CAS PubMed.
  168. Y. Y. Su, W. Wang, Z. M. Li, H. Deng, G. Q. Zhou, J. Xu and X. J. Ren, J. Anal. At. Spectrom., 2015, 30(5), 1184–1190 RSC.
  169. P. M. L. Hedberg, P. Peres, F. Fernandes and L. Renaud, J. Anal. At. Spectrom., 2015, 30(12), 2516–2524 RSC.
  170. S. S. Harilal, P. M. Diwakar, N. L. LaHaye and M. C. Phillips, Spectrochim. Acta, Part B, 2015, 111, 1–7 CrossRef CAS.
  171. J. Karhunen, A. Hakola, J. Likonen, A. Lissovski, M. Laan, P. Paris and J. E. Contributors, J. Nucl. Mater., 2015, 463, 931–935 CrossRef CAS.
  172. S. Almaviva, L. Caneve, F. Colao, P. Gasior, M. Kubkowska, M. Lepek and G. Maddaluno, Fusion Eng. Des., 2015, 96–97, 848–851 CrossRef CAS.
  173. Q. Xiao, R. Hai, H. Ding, A. Huber, V. Philipps, N. Gierse and G. Sergienko, J. Nucl. Mater., 2015, 463, 911–914 CrossRef CAS.
  174. K. Piip, G. De Temmerman, H. J. van der Meiden, A. Lissovski, J. Karhunen, M. Aints, A. Hakola, P. Paris, M. Laan, J. Likonen, I. Jogi, J. Kozlova and H. Mandar, J. Nucl. Mater., 2015, 463, 919–922 CrossRef CAS.
  175. P. Paris, K. Piip, A. Hakola, M. Laan, M. Aints, S. Koivuranta, J. Likonen, A. Lissovski, M. Mayer, R. Neu, V. Rohde, K. Sugiyama and A. U. Team, Fusion Eng. Des., 2015, 98–99, 1349–1352 CrossRef CAS.
  176. C. Li, D. Y. Zhao, Z. H. Hu, X. W. Wu, G. N. Luo, J. S. Hu and H. B. Ding, J. Nucl. Mater., 2015, 463, 915–918 CrossRef CAS.
  177. M. Martin, R. C. Martin, S. Allman, D. Brice, A. Wymore and N. Andre, Spectrochim. Acta, Part B, 2015, 114, 65–73 CrossRef CAS.
  178. C. Li, D. Y. Zhao, X. W. Wu and H. B. Ding, Plasma Sci. Technol., 2015, 17(8), 638–643 CrossRef.
  179. R. J. Cornett, Z. H. Kazi, X. L. Zhao, M. G. Chartrand, R. J. Charles and W. E. Kieser, Nucl. Instrum. Methods Phys. Res., Sect. B, 2015, 361, 317–321 CrossRef CAS.
  180. Z. H. Kazi, R. J. Cornett, X. L. Zhao and W. E. Kieser, J. Anal. At. Spectrom., 2015, 30(10), 2235–2240 RSC.
  181. C. H. Graser, N. L. Banik, K. A. Bender, M. Lagos, C. M. Marquardt, R. Marsac, V. Montoya and H. Geckeis, Anal. Chem., 2015, 87(19), 9786–9794 CrossRef CAS PubMed.
  182. Z. Varga, A. Nicholl, M. Wallenius and K. Mayer, Anal. Chem., 2016, 88(5), 2763–2769 CrossRef CAS PubMed.
  183. J. M. Fitzsimmons, D. G. Medvedev and L. F. Mausner, J. Anal. At. Spectrom., 2016, 31(2), 458–463 RSC.
  184. S. Paul, A. K. Pandey, R. V. Shah, D. Alamelu and S. K. Aggarwal, RSC Adv., 2016, 6(4), 3326–3334 RSC.
  185. C. G. Lee, D. Suzuki, F. Esaka, M. Magara and K. Song, Talanta, 2015, 141, 92–96 CrossRef CAS PubMed.
  186. M. Singh, V. Karki, R. K. Mishra, A. Kumar, C. P. Kaushik, X. L. Mao, R. E. Russo and A. Sarkar, J. Anal. At. Spectrom., 2015, 30(12), 2507–2515 RSC.
  187. G. Dravecz, L. Bencs, D. Beke and A. Gali, Talanta, 2016, 147, 271–275 CrossRef CAS PubMed.
  188. S. Z. Chen, J. F. Li, D. B. Lu and S. P. Zhu, At. Spectrosc., 2016, 37(1), 13–18 CAS.
  189. R. H. Tykot, Appl. Spectrosc., 2016, 70(1), 42–56 CrossRef CAS PubMed.
  190. J. M. Madariaga, Anal. Methods, 2015, 7(12), 4848–4876 RSC.
  191. L. C. Giannossa, D. Fico, A. Pennetta, A. Mangone, R. Laviano and G. E. De Benedetto, Chem. Pap., 2015, 69(8), 1033–1043 CAS.
  192. Z. Bao, H. L. Yuan, R. Wen and K. Y. Chen, Anal. Methods, 2015, 7(12), 5034–5040 RSC.
  193. T. Q. Zhu, X. Ding, C. M. Kusimba and Z. Y. Feng, Ceram. Int., 2015, 41(8), 9878–9884 CrossRef CAS.
  194. P. VanValkenburgh, S. J. Kelloway, L. Dussubieux, J. Quilter and M. D. Glascock, J. Archaeol. Sci., 2015, 61, 172–185 CrossRef CAS.
  195. Y. Su, L. Qu, H. Y. Duan, N. Tarcea, A. G. Shen, J. Popp and J. M. Hu, Spectrochim. Acta, Part A, 2016, 153, 165–170 CrossRef CAS PubMed.
  196. D. Seetha and G. Velraj, Spectrochim. Acta, Part A, 2015, 149, 59–68 CrossRef CAS PubMed.
  197. D. Miriello, A. Bloise, R. De Luca, C. Apollaro, G. M. Crisci, S. Medaglia and A. T. Grasso, Appl. Phys. A: Mater. Sci. Process., 2015, 119(4), 1595–1608 CrossRef CAS.
  198. T. Delbey, A. Quevedo and F. Laubenheimer, ArcheoSciences, 2015, 39, 185–199 CrossRef.
  199. H. C. Santos, C. Caliri, L. Pappalardo, R. Catalano, A. Orlando, F. Rizzo and F. P. Romano, Microchem. J., 2016, 124, 241–246 CrossRef CAS.
  200. Z. Y. He, M. L. Zhang and H. Z. Zhang, Ceram. Int., 2016, 42(4), 5123–5129 CrossRef CAS.
  201. G. Simsek, P. Colomban, F. Casadio, L. Bellot-Gurlet, G. Zelleke, K. T. Faber, V. Milande and L. Tilliard, J. Am. Ceram. Soc., 2015, 98(10), 3006–3013 CrossRef CAS.
  202. F. Bernardini, A. Vecchiet, A. De Min, D. Lenaz, A. M. Cuevas, A. Gianoncelli, D. Dreossi, C. Tuniz and M. M. Kokelj, Microchem. J., 2016, 124, 600–607 CrossRef CAS.
  203. L. Li, L. T. Yan, S. L. Feng, Q. Xu, L. Liu, Y. Huang and X. Q. Feng, Archaeometry, 2015, 57(6), 966–976 CrossRef CAS.
  204. F. Madkour, H. Imam, K. Elsayed and G. Meheina, Period. Mineral., 2015, 84(1), 107–121 Search PubMed.
  205. S. S. Rai, N. K. Rai, A. K. Rai and U. C. Chattopadhyaya, Spectrosc. Lett., 2015, 49(2), 57–62 CrossRef.
  206. J. Anzano, S. Sanguesa, J. Casas-Gonzalez, M. A. Magallon, M. Escudero, J. Anwar and U. Shafique, Anal. Lett., 2015, 48(10), 1638–1643 CrossRef CAS.
  207. Y. X. Sun, S. L. Zhong, F. K. Shan, Y. Lu, X. Sun, Z. Liu and P. P. Sheng, Appl. Opt., 2015, 54(15), 4812–4819 CrossRef CAS PubMed.
  208. B. Pollakowski and B. Beckhoff, Anal. Chem., 2015, 87(15), 7705–7711 CrossRef CAS PubMed.
  209. Y. Liu, S. Hofmann, J. Y. Wang and B. R. Chakraborty, Thin Solid Films, 2015, 591, 60–65 CrossRef CAS.
  210. L. Landstrom, L. Orebrand, K. Svensson and P. O. Andersson, J. Anal. At. Spectrom., 2015, 30(12), 2394–2402 RSC.
  211. D. Abou-Ras, R. Caballero, C. Streeck, B. Beckhoff, J. H. In and S. Jeong, Microsc. Microanal., 2015, 21(6), 1644–1648 CrossRef CAS PubMed.
  212. J. H. In, C. K. Kim and S. Jeong, J. Anal. At. Spectrom., 2015, 30(10), 2107–2119 RSC.
  213. M. J. Kim, J. Lee, S. H. Kim, H. Kim, K. B. Lee and Y. Lee, J. Nanosci. Nanotechnol., 2015, 15(10), 7722–7726 CrossRef PubMed.
  214. A. G. Karydas, C. Streeck, I. B. Radovic, C. Kaufmann, T. Rissom, B. Beckhoff, M. Jaksic and N. P. Barradas, Appl. Surf. Sci., 2015, 356, 631–638 CrossRef CAS.
  215. D. Mercier, M. Bouttemy, J. Vigneron, P. Chapon and A. Etcheberry, Appl. Surf. Sci., 2015, 347, 799–807 CrossRef CAS.
  216. R. Chakraborty, J. Serdy, B. West, M. Stuckelberger, B. Lai, J. Maser, M. I. Bertoni, M. L. Culpepper and T. Buonassisi, Rev. Sci. Instrum., 2015, 86(11), 6 Search PubMed.
  217. S. Zakel, B. Pollakowski, C. Streeck, S. Wundrack, A. Weber, S. Brunken, R. Mainz, B. Beckhoff and R. Stosch, Appl. Spectrosc., 2016, 70(2), 279–288 CrossRef CAS PubMed.
  218. R. Gonzalez-Arrabal, M. Panizo-Laiz, K. Fujita, K. Mima, A. Yamazaki, T. Kamiya, Y. Orikasa, Y. Uchimoto, H. Sawada, C. Okuda, Y. Kato and J. M. Perlado, J. Power Sources, 2015, 299, 587–595 CrossRef CAS.
  219. T. Waldmann, N. Ghanbari, M. Kasper and M. Wohlfahrt-Mehrens, J. Electrochem. Soc., 2015, 162(8), A1500–A1505 CrossRef CAS.
  220. M. Evertz, C. Lurenbaum, B. Vortmann, M. Winter and S. Nowak, Spectrochim. Acta Part B, 2015, 112, 34–39 CrossRef CAS.
  221. L. Nowack, D. Grolimund, V. Samson, F. Marone and V. Wood, Sci. Rep., 2016, 6, 9 Search PubMed.
  222. U. Boesenberg, M. Falk, C. G. Ryan, R. Kirkham, M. Menzel, J. Janek, M. Froba, G. Falkenberg and U. E. A. Fittschen, Chem. Mater., 2015, 27(7), 2525–2531 CrossRef CAS.
  223. S. J. Rezvani, M. Ciambezi, R. Gunnella, M. Minicucci, M. A. Munoz, F. Nobili, M. Pasqualini, S. Passerini, C. Schreiner, A. Trapananti, A. Witkowska and A. Di Cicco, J. Phys. Chem. C, 2016, 120(8), 4287–4295 CAS.
  224. F. W. B. Aquino, J. M. Santos, R. R. V. Carvalho, J. A. O. Coelho and E. R. Pereira, RSC Adv., 2015, 5(82), 67001–67010 RSC.
  225. M. Yang, M. Li, J. Xue, X. Zhao, X. Huang, L. Feng and Z. Xing, Chin. J. Anal. Chem., 2015, 43(5), 709–713 CAS.
  226. A. Alshehabi, N. Sasaki and J. Kawai, Spectrochim. Acta, Part B, 2015, 114, 34–37 CrossRef CAS.
  227. M. Bouza, R. Pereiro, N. Bordel, A. Sanz-Medel and B. Fernandez, J. Anal. At. Spectrom., 2015, 30(5), 1108–1116 RSC.
  228. F. Lopes, L. H. C. Amorin, L. D. S. Martins, A. Urbano, C. R. Appoloni and R. Cesareo, J. Spectrosc., 2016, 2016, 9509043 Search PubMed.
  229. Z. Y. Wang, B. W. Liu, E. W. Zhao, K. Jin, Y. G. Du, J. J. Neeway, J. V. Ryan, D. H. Hu, K. H. L. Zhang, M. N. Hong, S. Le Guernic, S. Thevuthasan, F. Y. Wang and Z. H. Zhu, J. Am. Soc. Mass Spectrom., 2015, 26(8), 1283–1290 CrossRef CAS PubMed.
  230. M. F. Gazulla, M. Rodrigo, M. Orduna and M. J. Ventura, Glass Technol.: Eur. J. Glass Sci. Technol., Part A, 2015, 56(3), 95–101 CrossRef.
  231. C. G. de Vega, C. A. Llamas, N. Bordel, R. Pereiro and A. Sanz-Medel, Anal. Chim. Acta, 2015, 877, 33–40 CrossRef PubMed.
  232. L. Liu, S. Li, X. Huang, Y. Lu, K. Chen, R. Pik, L. Jiang, J. F. Silvain and Y. F. Lu, J. Anal. At. Spectrom., 2015, 30(5), 1128–1132 RSC.
  233. M. E. Shaheen, J. E. Gagnon and B. J. Fryer, Spectrochim. Acta, Part B, 2015, 107, 97–109 CrossRef CAS.
  234. A. M. Duffin, K. W. Springer, J. D. Ward, K. D. Jarman, J. W. Robinson, M. C. Endres, G. L. Hart, J. J. Gonzalez, D. Oropeza, R. E. Russo, D. G. Willingham, B. E. Naes, A. J. Fahey and G. C. Eiden, J. Anal. At. Spectrom., 2015, 30(5), 1100–1107 RSC.
  235. P. Philipp, K. Q. Ngo, J. Kieffer and T. Wirtz, J. Phys. Chem. C, 2015, 119(41), 23334–23341 CAS.
  236. M. C. Vats and S. K. Singh, Waste Manag., 2015, 45, 280–288 CrossRef CAS PubMed.
  237. M. Ohata, H. Sakurai, K. Nishiguchi, K. Utani and D. Gunther, Anal. Chim. Acta, 2015, 891, 73–78 CrossRef CAS PubMed.
  238. Q. Z. Sun, J. R. Yang, Y. F. Wei, J. Zhang and R. Y. Sun, J. Electron. Mater., 2015, 44(8), 2773–2778 CrossRef CAS.
  239. Y. Shimizu, H. Takamizawa, K. Inoue, F. Yano, S. Kudo, A. Nishida, T. Toyama and Y. Nagai, Jpn. J. Appl. Phys., 2016, 55(2), 5 CrossRef.
  240. A. Tukiainen, J. Likonen, L. Toikkanen and T. Leinonen, J. Cryst. Growth, 2015, 425, 60–63 CrossRef CAS.
  241. I. Kurachi and K. Yoshioka, Jpn. J. Appl. Phys., 2015, 54(9), 5 CrossRef.
  242. S. P. Harvey, G. Teeter, H. Moutinho and M. M. Al-Jassim, Prog. Photovoltaics, 2015, 23(7), 838–846 CAS.
  243. M. A. Jensen, J. Hofstetter, A. E. Morishige, G. Coletti, B. Lai, D. P. Fenning and T. Buonassisi, Appl. Phys. Lett., 2015, 106(20), 5 CrossRef.
  244. F. Pianezzi, S. Nishiwaki, L. Kranz, C. M. Sutter-Fella, P. Reinhard, B. Bissig, H. Hagendorfer, S. Buecheler and A. N. Tiwari, Prog. Photovoltaics, 2015, 23(7), 892–900 CAS.
  245. C. Byrne, B. Brennan, A. P. McCoy, J. Bogan, A. Brady and G. Hughes, ACS Appl. Mater. Interfaces, 2016, 8(4), 2470–2477 CAS.
  246. H. L. Dong, J. Sun, S. F. Ma, J. Liang and B. S. Xu, RSC Adv., 2015, 5(92), 75211–75217 RSC.
  247. A. Bordes, E. De Vito, C. Haon, A. Boulineau, A. Montani and P. Marcus, Chem. Mater., 2016, 28(5), 1566–1573 CrossRef CAS.
  248. A. Funatsuki, M. Takaoka, K. Shiota, D. Kokusu and Y. Suzuki, Anal. Sci., 2016, 32(2), 207–213 CrossRef CAS PubMed.
  249. L. Yao, Y. Feng and G. X. Xi, RSC Adv., 2015, 5(55), 44107–44114 RSC.
  250. K. Sutorova, L. Prokes, V. Nazabal, M. Bouska, J. Havel and P. Nemec, J. Am. Ceram. Soc., 2015, 98(12), 4107–4110 CrossRef CAS.
  251. A. Riedo, V. Grimaudo, P. Moreno-Garcia, M. B. Neuland, M. Tulej, P. Wurz and P. Broekmann, J. Anal. At. Spectrom., 2015, 30(12), 2371–2374 RSC.
  252. L. G. Simonova, E. A. Paukshtis, L. S. Dovlitova, E. M. Sadovskaya and B. S. Bal'zhinimaev, Russ. J. Inorg. Chem., 2015, 60(9), 1052–1058 CrossRef CAS.
  253. E. I. Terukov, P. P. Seregin, A. V. Marchenko, D. V. Zhilina and K. U. Bobokhuzhaev, Semiconductors, 2015, 49(10), 1352–1356 CrossRef CAS.
  254. A. R. Meruva, S. Raparthi and S. J. Kumar, Talanta, 2016, 146, 259–265 CrossRef CAS PubMed.
  255. H. Arena, N. Godon, D. Rebiscoul, R. Podor, E. Garces, M. Cabie and J. P. Mestre, J. Nucl. Mater., 2016, 470, 55–67 CrossRef CAS.
  256. T. Sui, B. H. Song, J. Dluhos, L. Lu and A. M. Korsunsky, Nano Energy, 2015, 17, 254–260 CrossRef CAS.
  257. P. Devangad, V. K. Unnikrishnan, R. Nayak, M. M. Tamboli, K. M. M. Shameem, C. Santhosh, G. A. Kumar and D. K. Sardar, Opt. Mater., 2016, 52, 32–37 CrossRef CAS.
  258. F. Laborda, E. Bolea, G. Cepria, M. T. Gomez, M. S. Jimenez, J. Perez-Arantegui and J. R. Castillo, Anal. Chim. Acta, 2016, 904, 10–32 CrossRef CAS PubMed.
  259. C. A. Sotebier, F. S. Bierkandt, S. Rades, N. Jakubowski, U. Panne and S. M. Weidner, J. Anal. At. Spectrom., 2015, 30(10), 2214–2222 RSC.
  260. T. K. Mudalige, H. O. Qu and S. W. Linder, Anal. Chem., 2015, 87(14), 7395–7401 CrossRef CAS PubMed.
  261. S. Wagner, S. Legros, K. Loeschner, J. Liu, J. Navratilova, R. Grombe, T. P. J. Linsinger, E. H. Larsen, F. von der Kammer and T. Hofmann, J. Anal. At. Spectrom., 2015, 30(6), 1286–1296 RSC.
  262. F. Barahona, I. Ojea-Jimenez, O. Geiss, D. Gilliland and J. Barrero-Moreno, J. Chromatogr., 2016, 1432, 92–100 CrossRef CAS PubMed.
  263. F. Aureli, M. D'Amato, A. Raggi and F. Cubadda, J. Anal. At. Spectrom., 2015, 30(6), 1266–1273 RSC.
  264. K. Loeschner, J. Navratilova, R. Grombe, T. P. J. Linsinger, C. Kobler, K. Molhave and E. H. Larsen, Food Chem., 2015, 181, 78–84 CrossRef CAS PubMed.
  265. C. Cascio, O. Geiss, F. Franchini, I. Ojea-Jimenez, F. Rossi, D. Gilliland and L. Calzolai, J. Anal. At. Spectrom., 2015, 30(6), 1255–1265 RSC.
  266. G. F. Koopmans, T. Hiemstra, I. C. Regelink, B. Molleman and R. N. J. Comans, J. Chromatogr., 2015, 1392, 100–109 CrossRef CAS PubMed.
  267. D. C. Antonio, C. Cascio, Z. Jaksic, D. Jurasin, D. M. Lyons, A. J. A. Nogueira, F. Rossi and L. Calzolai, Mar. Environ. Res., 2015, 111, 162–169 CrossRef CAS PubMed.
  268. P. Krystek, S. Brandsma, P. Leonards and J. de Boer, Talanta, 2016, 147, 289–295 CrossRef CAS PubMed.
  269. T. K. Mudalige, H. O. Qu and S. W. Linder, J. Chromatogr., 2015, 1420, 92–97 CrossRef CAS PubMed.
  270. A. Dudkiewicz, S. Wagner, A. Lehner, Q. Chaudhry, S. Pietravalle, K. Tiede, A. B. A. Boxall, G. Allmaier, D. Tiede, R. Grombe, F. von der Kammer, T. Hofmann and K. Molhave, Analyst, 2015, 140(15), 5257–5267 RSC.
  271. Z. Q. Tan, J. F. Liu, X. R. Guo, Y. G. Yin, S. K. Byeon, M. H. Moon and G. B. Jiang, Anal. Chem., 2015, 87(16), 8441–8447 CrossRef CAS PubMed.
  272. A. R. M. Bustos, E. J. Petersen, A. Possolo and M. R. Winchester, Anal. Chem., 2015, 87(17), 8809–8817 CrossRef PubMed.
  273. R. Peters, Z. Herrera-Rivera, A. Undas, M. van der Lee, H. Marvin, H. Bouwmeester and S. Weigel, J. Anal. At. Spectrom., 2015, 30(6), 1274–1285 RSC.
  274. W. W. Lee and W. T. Chan, J. Anal. At. Spectrom., 2015, 30(6), 1245–1254 RSC.
  275. J. Tuoriniemi, G. Cornelis and M. Hassellov, J. Anal. At. Spectrom., 2015, 30(8), 1723–1729 RSC.
  276. I. Strenge and C. Engelhard, J. Anal. At. Spectrom., 2015, 31(1), 135–144 RSC.
  277. A. R. Donovan, C. D. Adams, Y. F. Ma, C. Stephan, T. Eichholz and H. L. Shi, Chemosphere, 2016, 144, 148–153 CrossRef CAS PubMed.
  278. E. Verleysen, E. Van Doren, N. Waegeneers, P. J. De Temmerman, M. A. D. Francisco and J. Mast, J. Agric. Food Chem., 2015, 63(13), 3570–3578 CrossRef CAS PubMed.
  279. J. Navratilova, A. Praetorius, A. Gondikas, W. Fabienke, F. von der Kammer and T. Hofmann, Int. J. Environ. Res. Public Health, 2015, 12(12), 15756–15768 CrossRef CAS PubMed.
  280. M. Hadioui, V. Merdzan and K. J. Wilkinson, Environ. Sci. Technol., 2015, 49(10), 6141–6148 CrossRef CAS PubMed.
  281. Y. B. Dan, H. L. Shi, C. Stephan and X. H. Liang, Microchem. J., 2015, 122, 119–126 CrossRef CAS.
  282. B. Ramkorun-Schmidt, S. A. Pergantis, D. Esteban-Fernandez, N. Jakubowski and D. Gunther, Anal. Chem., 2015, 87(17), 8687–8694 CrossRef CAS PubMed.
  283. S. Gschwind, M. D. A. Montes and D. Gunther, Anal. Bioanal. Chem., 2015, 407(14), 4035–4044 CrossRef CAS PubMed.
  284. D. Paunescu, C. A. Mora, L. Querci, R. Heckel, M. Puddu, B. Hattendorf, D. Gunther and R. N. Grass, ACS Nano, 2015, 9(10), 9564–9572 CrossRef CAS PubMed.
  285. I. Benesova, K. Dlabkova, F. Zelenak, T. Vaculovic, V. Kanicky and J. Preisler, Anal. Chem., 2016, 88(5), 2576–2582 CrossRef CAS PubMed.
  286. J. Vidmar, R. Milacic, V. Golja, S. Novak and J. Scancar, Anal. Methods, 2016, 8(5), 1194–1201 RSC.
  287. J. Bok-Badura, A. Jakobik-Kolon, M. Turek, S. Boncel and K. Karon, RSC Adv., 2015, 5(123), 101634–101640 RSC.
  288. H. O. Qu, T. K. Mudalige and S. W. Linder, J. Chromatogr., 2016, 1429, 348–353 CrossRef CAS PubMed.
  289. M. Matczuk, S. S. Aleksenko, F. M. Matysik, M. Jarosz and A. R. Timerbaev, Electrophoresis, 2015, 36(9–10), 1158–1163 CrossRef CAS PubMed.
  290. K. Nakata, B. Hashimoto, H. Uchihara, Y. Okamoto, S. Ishizaka and T. Fujiwara, Talanta, 2015, 138, 279–284 CrossRef CAS PubMed.
  291. K. Nakata, Y. Okamoto, S. Ishizaka and T. Fujiwara, Talanta, 2016, 150, 434–439 CrossRef CAS PubMed.
  292. K. Huang, K. L. Xu, J. Tang, L. Yang, J. R. Zhou, X. D. Hou and C. B. Zheng, Anal. Chem., 2015, 87(13), 6584–6591 CrossRef CAS PubMed.
  293. N. Yan, Z. L. Zhu, L. L. Jin, W. Guo, Y. Q. Gan and S. H. Hu, Anal. Chem., 2015, 87(12), 6079–6087 CrossRef CAS PubMed.
  294. P. Paydary and P. Larese-Casanova, Int. J. Environ. Anal. Chem., 2015, 95(15), 1450–1470 CrossRef CAS.
  295. Y. Kayser, J. Sa and J. Szlachetko, Nanoscale, 2015, 7(20), 9320–9330 RSC.
  296. G. Xiong, S. Q. Li, Y. Y. Zhang, S. G. Buckley and S. D. Tse, J. Anal. At. Spectrom., 2016, 31(2), 482–491 RSC.
  297. M. Ohata and T. Kidokoro, Anal. Sci., 2015, 31(8), 855–858 CrossRef CAS PubMed.
  298. T. Roth, R. U. Bertran, A. Latza, K. Andorfer-Lang, C. Hugelschaffer, M. Pohlein, R. Puchta, C. Placht, H. Maid, W. Bauer and R. van Eldik, Anal. Bioanal. Chem., 2015, 407(11), 3023–3034 CrossRef CAS PubMed.
  299. R. Murakami, M. Mutsuga, T. Abe, Y. Abe, I. Ohsaka, H. Ohno, Y. Ohno, A. Ozaki, Y. Kakihara, H. Kawasaki, H. Kobayashi, H. Shibata, K. Shirono, H. Sekido, H. Sonobe, N. Takasaka, Y. Tajima, A. Tanaka, H. Tanaka, C. Nomuka, N. Haneishi, A. Hikida, T. Miura, K. Watanabe and H. Akiyama, Food Hyg. Saf. Sci., 2015, 56(2), 57–67 CrossRef CAS PubMed.
  300. H. Shibata, M. Mutsuga, Y. Abe, S. Itou, I. Ohsaka, H. Ohno, Y. Ohno, A. Ozaki, Y. Kakihara, H. Kobayashi, K. Shirono, H. Sekido, H. Sonobe, N. Takasaka, Y. Tajima, A. Tanaka, H. Tanaka, T. Nakanishi, C. Nomura, N. Haneishi, A. Hikida, T. Miura, M. Yamaguchi, K. Watanabe and H. Akiyama, Food Hyg. Saf. Sci., 2015, 56(3), 123–131 CrossRef CAS PubMed.
  301. V. G. Mihucz and G. Zaray, Appl. Spectrosc. Rev., 2016, 51(3), 163–189 CrossRef CAS.
  302. L. Y. Fang, L. Wang, J. G. Li and Q. L. Gao, Anal. Lett., 2015, 48(12), 1954–1964 CrossRef CAS.
  303. A. Mackevica, M. E. Olsson and S. F. Hansen, J. Nanopart. Res., 2016, 18(1), 11 CrossRef.
  304. J. C. Hannon, J. P. Kerry, M. Cruz-Romero, S. Azlin-Hasim, M. Morris and E. Cummins, Food Addit. Contam., Part A, 2016, 33(1), 167–178 CAS.
  305. A. de Jesus, M. B. Dessuy, C. S. Huber, A. V. Zmozinski, A. T. Duarte, M. G. R. Vale and J. B. Andrade, Microchem. J., 2016, 124, 222–227 CrossRef CAS.
  306. N. Ozbek, G. S. Ustabasi and S. Akman, J. Anal. At. Spectrom., 2015, 30(8), 1782–1786 RSC.
  307. T. V. Silvaa, K. Miranda, E. C. Ferreira, M. C. Santos, J. A. G. Neto and F. Barbosa, At. Spectrosc., 2015, 36(4), 182–186 Search PubMed.
  308. F. Borno, S. Richter, D. Deiting, N. Jakubowski and U. Panne, J. Anal. At. Spectrom., 2015, 30(5), 1064–1071 RSC.
  309. B. Izgi and M. Kayar, Talanta, 2015, 139, 117–122 CrossRef CAS PubMed.
  310. L. Lobo, B. Fernandez, R. Muniz, R. Pereiro and A. Sanz-Medel, J. Anal. At. Spectrom., 2016, 31(1), 212–219 RSC.
  311. A. M. Maley, K. A. Falk, L. Hoover, E. B. Earlywine, M. D. Seymour, P. A. DeYoung, A. Blum, H. M. Stapleton and G. F. Peaslee, Nucl. Instrum. Methods Phys. Res., Sect. B, 2015, 358, 21–25 CrossRef CAS.
  312. M. Schlummer, J. Vogelsang, D. Fiedler, L. Gruber and G. Wolz, Waste Manag. Res., 2015, 33(7), 662–670 CrossRef PubMed.
  313. V. S. Kumar, N. J. Vasa and R. Sarathi, J. Phys. D: Appl. Phys., 2015, 48(43), 10 Search PubMed.
  314. D. Kolasa, A. Bajszczak, A. Lukomska, J. Dlubak, Z. Rogulski, S. Kowalska and A. Czerwinski, Polimery, 2016, 61(2), 98–105 CrossRef.
  315. D. F. Williams, M. L. Abel, E. Grant, J. Hrachoya and J. F. Watts, Int. J. Adhes. Adhes., 2015, 63, 26–33 CrossRef CAS.
  316. D. Prochazka, M. Bilik, P. Prochazkova, J. Klus, P. Porizka, J. Novotny, K. Novotny, B. Ticova, A. Bradac, M. Semela and J. Kaiser, Spectrochim. Acta, Part B, 2015, 108, 1–7 CrossRef CAS.
  317. E. N. Rao, P. Mathi, S. Abdul Kalam, S. Reedhar, A. K. Singh, B. N. Jagatap and S. V. Rao, J. Anal. At. Spectrom., 2016, 31, 737–750 RSC.
  318. J. Hormes, A. Diekamp, W. Klysubun, G. L. Bovenkamp and N. Borste, Microchemical Journal, 2016, 125, 190–195 CrossRef CAS.
  319. H. M. Hou, L. Cheng, T. Richardson, G. Y. Chen, M. Doeff, R. Zheng, R. Russo and V. Zorba, J. Anal. At. Spectrom., 2015, 30(11), 2295–2302 RSC.
  320. C. Almeida, M. Grosselli, P. Gonzalez, D. Martinez and R. Gil, Chemosphere, 2016, 114, 1–6 CrossRef PubMed.
  321. V. Krylova, S. Zalenkiene, N. Dukstiene and J. Baltrusaitis, Applied Surface Science, 2015, 351, 203–208 CrossRef CAS.
  322. B. Peace, J. Claypoole, N. Sun, D. Dwyer, M. D. Eisaman, P. Haldar and H. Efstathiadis, J. Alloy. Compd., 2016, 657, 873–877 CrossRef CAS.
  323. J. Schon, F. Schindler, W. Kwapil, M. Knorlein, P. Krenckel, S. Riepe, W. Warta and M. C. Schubert, Sol. Energy Mater. Sol. Cells, 2015, 142, 107–115 CrossRef.
  324. N. L. LaHaye, J. Kurian, P. K. Diwakar, L. Alff and S. S. Harilal, Sci. Rep., 2015, 5, 13121 CrossRef CAS PubMed.

Footnote

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