Atomic spectrometry update: review of advances in atomic spectrometry and related techniques
E. Hywel
Evans
*a,
Jorge
Pisonero
b,
Clare M. M.
Smith
c and
Rex N.
Taylor
d
aThe Open University, UK. E-mail: e.h.evans@open.ac.uk
bUniversity of Oviedo, Faculty of Science, Department of Physics, c/Calvo Sotelo s/n, 33006 Oviedo, Spain
cSchool of Education, College of Social Sciences, University of Glasgow, University Avenue, Glasgow G12 8QQ, UK
dOcean and Earth Science, University of Southampton, NOC, Southampton, UK SO14 3ZH
First published on 30th April 2019
Abstract
This review of 140 references covers developments in ‘Atomic Spectrometry’ published in the twelve months from November 2017 to November 2018 inclusive. It covers atomic emission, absorption, fluorescence and mass spectrometry, but excludes material on speciation and coupled techniques which is included in a separate review. It should be read in conjunction with the previous review and the other related reviews in the series.1–6 A critical approach to the selection of material has been adopted, with only novel developments in instrumentation, techniques and methodology being included. No single area of research has generated a large number of publications this review period, with novel developments distributed over a range of fields. Most prominent perhaps, have been the novel instrumental developments in LIBS, such as the hybrid RAMAN/LIBS instruments for remote sensing and phase selective (PS)-LIBS for the analysis of nano-particles. The use of the dielectric barrier discharge (DBD), originally developed as a compact excitation/ionisation source has now found application for sample digestion, vapour generation and analyte trapping, reflecting the move towards more portable and integrated systems for field applications. The range of non-radiogenic, heavier isotopes amenable to isotope ratio analysis continues to expand, with Te now included in their number.
1 Sample introduction
1.1 Liquids
1.1.1.1 Extraction and digestion. Sanchez et al.7 developed an aerosol phase extraction method for the analysis of organic samples by ICP-OES. The method works by directing the aerosol spray generated for a solution of 0.1 mol L−1 HNO3, using a standard quartz concentric nebuliser, into a sample of biodiesel (0.5–0.9 g) in a 5 mL extraction vial. Extraction occurred at the interface between aerosol droplets and sample. The aqueous phase containing the extracted analyte was separated and determined using ICP-OES. The authors investigated a number of parameters and arrived at optimum conditions of nebuliser gas flow rate = 0.4 L min−1, nebuliser liquid flow rate = 0.3 mL min−1, extraction time = 60 s, nebuliser tip to sample surface gap = 1.5 cm. The LODs were 32, 20, 19, and 24 ng mL−1 for Ca, K, Na, and Mg, respectively. Concentrations of Ca, K, Na, and Mg contents were determined in four real samples in the range 0.5 to 13 mg kg−1, with results which were not statistically different to those achieved using microwave-based digestion.
Solid phase extraction has been around for a long time with many different variations and extraction media. One of the growth areas in recent years and been to incorporate SPE into miniaturised flow manifolds, which has now become much easier since the advent of low-cost 3D-printing technology. Su and Chen8 developed a 3D-printed demountable column holder, and minicolumns containing TiO2 NP-incorporated BV-007 resin, for the selective extraction of inorganic As and Se species from high-salt-content samples. Using this set-up they were able to distinguish between AsV, AsIII, SeVI and SeIV by pH-selective elution and determination using ICP-MS, with respective LODs of 0.004, 0.033, 0.128 and 0.061 μg L−1.
The use of a dielectric barrier discharge (DBD) for sample digestion was reported by Luo et al.9 The DBD device was made from two concentric quartz tubes, with copper inner rod and outer coil electrodes. Under optimised conditions, samples of rice powder in 30% H2O2 solution were pumped into the annular space between the two quartz tubes. Air carrier gas was also introduced to mix the sample, aid digestion and stabilise the DBD. The DBD itself was generated by application of a 15 V AC power supply at 50 W power for 40 min digestion time. LODs for Cd, Co, Cr, Mg, Mn and Zn were in the range from 0.01 to 0.35 ng g−1 using ICP-MS. Recoveries for samples of CRM GBW10043 (rice powder) were between 83 and 113%.
1.1.1.2 Elemental tagging. Elemental tagging covers a range of techniques generally targeted at the indirect quantitation of proteins, peptides and nucleic acids. This can be done by quantitation via e.g. an intrinsic hetero-atom in a protein, such as sulfur or selenium; chelation or covalent bonding of a metal tag to the target molecule and subsequent quantitation by direct calibration or ID-MS; labelling via an antigen–antibody immunoassay type system; or hybridisation of target strands of DNA or RNA with complementary labelled probes. There are also variations which combine elements of all the foregoing. The number of publications in this area peaked several years ago, but has declined in popularity now that the problems of routine implementation must be overcome.
In a paper with 93 references Cid-Barrio et al.10reviewed the present status of the various methods for the quantitation of proteins, peptides and nucleic acids using ICP-MS, itemised in the introduction to this section. They concluded that the new breed of ICP-QQQMS instruments, coupled with LC separation, simplifies quantitation without the need for species-specific standards, and that amplification methods (using NPs and other hybridisation approaches) has a major role to play. They further highlighted the advances in LA-ICP-MS for spatial mapping of metal-containing proteins in tissues, and its complementarity with techniques such as MALDI-MS.
Commercial development has focussed on variations of methods used originally for mass cytometry, i.e. an immunoassay method which relies on monoclonal antibodies labelled with stable heavy-metal isotopes. This method lends itself to both multiplexing (determination of several target molecules by using antibodies labelled with different metals) and amplification, the latter an important advantage for the determination of extremely low concentrations of target molecules in clinical tests. Xiao et al.11 used such a strategy for the determination of avian influenza A (H9N2) virions using ICP-MS. They used the so-called sandwich immunoassay strategy, whereby a H9N2 antibody (mAb-HA) was used to bind with H9N2 virions in a complex matrix; and Au NPs conjugated with mAb-HA were employed for the specific labelling of H9N2 virions for subsequent ICP-MS detection. Magnetic beads were first conjugated with mAB-HA and then used to bind with H9N2, which were further bound to mAB-HA labelled Au-NPs (the amplification step). The complex was magnetically isolated, then the mAB-HA-Au-NP moiety eluted with acid and determined using ICP-MS. The method was applied to samples of fresh chicken dung, with spiked recoveries in the range between 91.4 and 117% at concentrations of 8 to 100 ng mL−1. Another immunoassay method using Au-NPs was reported by Li et al.,12 but this time using a dual-amplification approach. First, samples were well-plated and coated with an alpha fetoprotein antibody (anti-AFP1), used to capture the target alpha fetoprotein (AFP), then subsequently labelled with anti-AFP2-HRP (a second antibody conjugated with horseradish peroxidase). After 1 h of incubation and removal of excess protein, a solution of biotin-tyramine in 0.01% (v/v) H2O2 was added thereby causing biotin-tyramine to deposit on the nearby proteins in the presence of anti-AFP2-HRP, i.e. the first amplification step. Addition of streptavidin (SA) labelled Au-NPs resulted in an Au-NP-SA–biotin-tyramine complex (the second amplification step) which was determined using ICP-MS. A linear range of 0.005 to 2 ng mL−1 and LOD of was 1.85 pg mL−1 AFP was achieved. The method was applied for the detection of AFP in human serum and compared to a clinical method of chemiluminescence immunoassay, with no significant difference for P = 0.1. Spiked recoveries of between 91 and 112% were obtained for samples containing ∼10 to 30 ng mL−1.
Liu et al.13 reported a slightly different approach, which they call a label-free bioassay, for the determination of DNA. The target DNA is first isolated by hybridisation with an immobilised capture DNA strand, then subjected to a hybridisation chain reaction (HCR). In HCR, the target DNA initiates the cross-opening of two DNA hairpins, H1 and H2, yielding new DNA double helices. Copper NPs were then added, which preferentially complexed with the H1/H2/target/capture DNA double helices, thereby affording both specificity and amplification when determined using ICP-MS. A dynamic range of between 20 and 1000 pM and LOD of 4 pM were obtained. Spiked recoveries for human serum samples were between 90 and 107% for 91 to 535 pM of DNA.
Metal speciation analysis of microsamples in the clinical, biological and forensic fields can be carried out by nanoHPLC with ICP-MS detection. Cheng et al.17 developed an ICHPN for sheathless nanoHPLC-ICP-MS to enhance the sensitivity and the separation efficiency of the reported method. The ICHPN consists of two concentric fused-silica capillaries with tapered tips connected via a PEEK tee, where C-18 silica particles with a size of 5 μm were packed in the tapered inner capillary based on the keystone effect. Combining a heated single pass spray chamber with a make-up gas, the ICHPN was capable of independently optimising the nebulisation efficiency and transport efficiency. The ICHPN offered high sensitivities, low LODs and good precision at nanoflow rates. Compared with commercial nebulisers, the ICHPN fabrication was simple, rapid, reproducible and inexpensive. Using the ICHPN, rapid separation of four Hg species (Hg2+ and methyl-, ethyl- and phenylmercuric chloride) within 8.0 min was achieved. LODs of 0.044–0.13 μg L−1 were obtained with precisions of peak heights and areas ranging from 1.5 to 3.5% for a 50 μg L−1 standard solution. Good agreement between the determined and certified values of Hg species in SRM 955c together with good recoveries (93–101%) validated the accuracy of the method.
ICP-MS-based analytical techniques, such as spICP-MS and scICP-MS, for NPs and cells, require highly time resolved measurements to individually analyse particles and cells as well as highly efficient and repeatable sample introduction methods. Myashita et al.21 describe a system that enables concurrent direct reading of the ion pulse current from the ICP-MS detector and the processing of measurement data permitting the required high time resolution for sp and sc analyses. ICP-MS is a promising technique for metallic NP tagged bioassays due to its high sensitivity, wide dynamic linear range, and multiplex and absolute quantification ability. sNP analysis-based ICP-MS bioassays, providing high sensitivity without sophisticated signal amplification procedures are suggested by Hu et al.22 as a new avenue for multiplex single molecule analysis with applications described.
1.2. Vapour generation
Vapour generation, where the analyte is converted to a volatile species prior to introduction into an atom/excitation/ionisation source, can be achieved in a number of ways. This can be a chemical (CVG), electrochemical (EVG) or photochemical (PVG) process. Novakova23 compared the effect of the matrix on the generation of volatile Se species, using the foregoing coupled with QF-AAS. The effects of Ag, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Sb were evaluated. Unsurprisingly, a large number of trends were observed, many of which were probably specific to the experimental set-up used. The reagent systems were: EVG, 1.0 mol L−1 HCl catholyte and 2.0 mol L−1 H2SO4 anolyte; PVG, UV radiation and 0.5 mol L−1 formic acid; and CVG, 0.5% acidified NaBH4 as the reducing agent. Overall, CVG was found to be least prone to matrix effects, EVG and PVG were similarly affected and EVG suffered the most from memory effects.Chemical vapour generation has been around for a long time. During the preceding 15 years or so the range of volatile species that can be generated has grown, from being just Hg and the hydride forming metals and metalloids to volatile species of transition metals. The focus on species has now slowed, with the focus changing to ways of miniaturising and enhancing the generation process.
The dielectric barrier discharge (DBD) has shown some promise in this regard and can be used variously as an atom/excitation/ionisation source, a means of enhancing the CVG process or as a trap. Qi et al.24 developed a DBD system for trapping volatile As species generated using HG. The DBD trap consisted of two concentric quartz tubes, the outer being wrapped with a copper mesh as the ground electrode and the inner containing a copper rod as the HV electrode, coupled to 3 × 104 Hz power supply. The HG-generated species were introduced for between 10 and 20 s, during which time a 9.2 kV DBD was generated under O2–Ar for trapping. The voltage was changed to 9.5 kV and release was performed in H2–Ar. Detection was performed using AFS, with an LDR of 0.1 to 8 μg L−1 and LOD of 1.4 ng L−1 (2.8 pg for a 2 mL sample). Zurynkova et al.25 have reported using a DBD as a trap and atomiser for volatile Sb species. Their DBD was a planar design with two copper electrodes (50 mm long; 5 mm wide; 0.15 mm thick) attached to opposite, outer surfaces of a rectangular quartz optical arm. They were covered with a layer of epoxy resin to avoid surface discharge. Trapping of stibanes, introduced after HG, was achieved in a flow of 2.0 mL min−1 O2 for between 30 and 300 s. Release and atomisation was performed by switching off the O2 flow while maintaining the HG blank flow. They compared the DBD system with a traditional QTA. Analyte was released faster using the QTA, probably due to the high temperature of the surface, with consequent lower LOD (3 pg mL−1 compared to 16 pg mL−1) for the DBD. Liu et al.26 have developed a liquid spray DBD, which was described in this review last year (X. Liu, Z. Zhu, H. Li, D. He, Y. Li, H. Zheng, Y. Gan, Y. Li, N. S. Belshaw and S. Hu, Anal. Chem., 2017, 89(12), 6827–6833). They maintain that the system has a number of advantages over comparable techniques, principally tolerance of matrix effects and operation without the need for reducing chemicals. Using AFS as the detector, they evaluated the system for a range of rice samples, with recoveries between ∼88 and 109% and with an LOD of 0.01 μg L−1 for the digested sample (0.12 μg kg−1 for the solid sample).
There have been many methods developed to trap volatile species for preconcentration purposes. Carbon nano-tubes (CNTs) are the research material du jour so it is no surprise to see them used for this purpose. Maratta Martínez et al.27 incorporated CNTs into a needle trapping device (NTD), reminiscent of SPME fibre, to trap volatile Se species. The method incorporated FI microwave digestion and the NaBH4 reduction system which took place in a capped vial. The NTD was made from a stainless steel needle (40 mm long × 0.5 mm i.d.) packed with an aqueous suspension of 4 mg of oxidised MWCNTs. The NTD was inserted into the digestion vial to absorb the Se hydrides, then removed and eluted (30 μL of 5% HNO3) into ETAAS for detection. The LOD was 0.032 μg kg−1 (preconcentration factor of 100), but with a throughput of only 5 samples per h.
Most CVG sample analysis involves aqueous solutions of sample digests, however, it can sometimes be advantageous to use non-aqueous solvents. Lei et al.28 developed a method for the non-aqueous CVG of Cd. The sample (10 mL) was mixed with dithizone, Triton X-114 and octanol, shaken, then subjected to ultrasound to effect an extraction into the micelles so formed. The organic phase was separated by centrifugation and 10 μL aliquots added to solid KBH4 in a reactor. Detection was by AFS, with an LOD of 0.004 μg L−1.
Generation of volatile transition metal species is now well established. Vyhnanovsky et al.29 investigated the mechanism of generation of volatile Pd species. They used NaBH4 as the chemical agent plus other modifiers such as sodium diethyldithiocarbamate (DDTC), which increased reaction efficiency 9-fold. Using direct analysis in real time (DART) MS, ICP-MS, AAS and EM they identified some of the volatile species and proposed a mechanism involving formation of nanoparticles and a Pd(DDTC)2 chelate.
There has been quite a bit of research into photochemical vapour generation over the last few years. The method is now quite well established, so recent research has focussed on novel configurations. Romanovskiy et al.30 have developed a photochemical reactor to maximise UV irradiation of the sample by containing a 15 W low-pressure mercury discharge lamp (25.6 mm o.d.) inside a hollow Teflon cylinder. The sample solution and argon carrier gas were passed through this reactor, which had an internal volume of only 4.5 mL. The LODs, in single element mode using ICP-MS, for As, Bi, Hg, Sb, Se and Te were 0.5, 13, 0.6, 0.3, 0.4 and 0.7 ng L−1 respectively. They found that substantial matrix effects were caused by mineral acids however. Zou et al.31 developed a miniaturised UV-LED photochemical reaction cell. The cell was a quartz coil (3 cm diameter) made from quartz tube (1 mm i.d., 3 mm o.d., 25 cm long), internally coated with TiO2, irradiated axially by a UV-LED (370 nm). Optimised LODs were 0.21 and 0.28 g L−1 for SeVI and SeIV respectively using AFS detection. Recoveries for CRM and spiked water samples were between 93 and 107%. The same researchers also investigated32 the effect of UV wavelength when using the same reaction coil. They used a broadband laser-driven light source and a UV lamp as irradiation sources, combined with 254 nm, 285 nm, 315 nm, 365 nm and 395 nm filters. AFS with an Ar–H2 flame was used for detection. They came to the somewhat unsurprising conclusions that shorter wavelength and higher intensity improved the intensity of the SeVI signal.
1.3 Solids
Meermann and Nischwitz33 provided a tutorial review on the use of ICP-MS based techniques for the analysis of metal-containing NPs and colloids. Chapters of the review cover the capabilities of ICP-MS for the analysis of total metal contents, the suitability of stable isotopes for NP tracking, sp-ICP-MS and fractionation/separation systems. Quality assurance considerations and future perspectives are also offered in this comprehensive report. A tutorial article providing guidelines for analysing metallic NPs and their dispersions using MinLC with diode array detection and coupled on-line to IT-SPME by Gonzalez-Fuenzalida et al.34 provided practical advice for obtaining reliable results. MinLC-DAD has the potential to estimate NP concentration and from it the average size of unknown samples by calibrating with a single standard, as well as potentially studying non-spherical particles and stability-related properties of their dispersions. While keeping the signal dependency with concentration and increasing the method sensitivity, IT-SPME-MinLC-DAD goes further allowing for the assessment of the dispersant effect and ultimately changes in the NP surroundings that range from modifications of the hydrodynamic diameter to the exposure to different reagents and matrices.An article on bioimaging in metallomics by Dressler et al.35 considered the various techniques used, namely LA-ICP-MS, SIMS, synchrotron XRF, TEM, SEM and ED-XRF. The basic principles of the techniques and their application for qualitative and quantitative imaging of elements in biological samples were described and sample preparation for bioimaging was briefly discussed.
1.3.1.1 Arc and spark. Yao et al.37 described an analytical scheme combining SIBS with particle flow for the real-time measurement of the constituents in powdered materials. The low-cost system incorporated a high voltage power supply instrument, a vibrational feeder and a spectrometer. Results obtained from the analysis of samples with varied C content, using both LIBS and PF-SIBS, were compared and improvements in RSDs, SNR and calibration were recorded with the new system.
1.3.1.2 Glow discharge. Gamez and Finch provided a review of the application of GD to surface elemental mapping.38 The review covered: GD-OES ultra-high throughput elemental mapping of thin films and combinatorial libraries using GD as an excitation source, current work on extending the lateral and depth resolution capabilities of GD-OES elemental mapping to larger samples; and the application of GD-MS to elemental mapping through a pixel-by-pixel rastering method. Xing et al.39 described an elemental imaging method based on a DBD probe as a sputtering source coupled with ICP-MS. The DBD probe is simple to construct and operates with a low discharge power of 3.75 W. To investigate the sputtering process, determination of 23Na, 27Al, 29Si, 44Ca, 55Mn and 57Fe in rock SRM GBW07108 was carried out. Elemental imaging was demonstrated using lead-based glaze ceramic with 206Pb, 207Pb and 208Pb, Chinese seal script with 202Hg and siliceous stromatolites with 27Al, 29Si, and 44Ca. The method has the capabilities of multi-elemental analysis, easy set-up and low power consumption.
Yu and co-workers described an LCGD as a micro-plasma excitation source for AES.40,41 Good analytical results were reported for the simultaneous detection of several trace metals. The instrument is small, has low power consumption, no inert gas requirement and is low cost, suggesting the potential for development as a portable instrument for in-site and real-time monitoring of metals.
Of the various ionisation sources used for MS, MP-GD and BGA-LI sources have shown the greatest potential for direct quantitative elemental analysis of solids without the need for standardisation. The analytical potential of these two ion sources has been evaluated by coupling them to orthogonal TOF-MS.42 The calibration is straightforward if a spectrum contains little interference and elemental peak currents are proportional to their concentrations. Two series of metal standards were applied for the evaluation. Spectra with little interference could be acquired by both techniques. The interferences contribute only a very small portion to the total ion current for MP-GD-MS and BGA-LI-MS; therefore, their influence on the quantitative result can be ignored. Metal elements can be determined with reasonable accuracy. However, gaps exist for non-metal elements due to their high ionisation potentials or gas species interference. Of the two techniques, BGA-LI-MS provided the more accurate quantitative results, due to its higher plasma temperature.
A pulsed-ECAD system was developed as a radiation source for AES.43 The time-resolved emission spectra of the pulsed-ECAD were obtained at various frequencies, and their evolution behaviours during the modulation period were found to exhibit a strong dependence on the modulation frequency. The temporal behaviour of the spectral intensities of K, Li, Mg, Na, Rb and Sr as well as the atomic and molecular species emissions originating from water and air were characterised from the plasma emission. Matrix effects in the system were also studied.44
1.3.2.1 Laser ablation. The dynamics of aerosol particles formed during nanosecond LA of glass and steel samples were studied using LA-ICP-MS.45 To follow the evolution of particle size distribution with high time resolution during the LA process, two fast response aerosol spectrometers were used. It was found that the ablation process was influenced mostly by the material itself as well as the ablation mode. Hola and co-workers reported the use of NPs applied to the surface of some solids to increase signals in ICP-MS.46 Drops containing Ag and/or Au NPs were deposited on metallic and ceramic/glass samples. The LA-ICP-MS signals were enhanced for metallic samples modified with NPs in comparison to signals produced at the plain, untreated surface by over 2 orders of magnitude. No enhancement was achieved for nonconductive samples. The enhancement was limited to the peripheral annular region of the dried droplet area where NPs were concentrated due to the ‘coffee stain’ effect. A more uniform material rearrangement was observed over the NP-treated surface compared with the ablated plain target. However, besides a smoother crater bottom, no other evidence of an NP-enhancing effect was noticed, although an increased ablation rate had been anticipated. LODs dropped by 1 order of magnitude for the minor elements in the presence of NPs. Observed phenomena depended only on the NP surface concentration but not on the material or size of the NPs. An electron microprobe study of the collected ablation aerosol has shown that aerosol particles consisting of target material were aggregated around the NPs. The hypothesis is that such aggregates exhibit better transport and vaporisation efficiency, thus enhancing signals for metallic samples.
Helium is often used as an aerosol carrier gas in 193 nm ArF excimer LA-ICP-MS analysis because it increases the signal intensity compared with that obtained using Ar. Luo et al.47 studied the influence of both carrier gases on signal intensities using a local aerosol extraction strategy and a cylindrical ablation cell. The experimental results showed that the sampling position in a common ablation cell strongly affected the signal enhancement factors of refractory lithophile elements when using He instead of Ar as the carrier gas. The signal enhancement factor was about 2–3 fold in the centre position of the cylindrical ablation cell, which had an ablation location-related carrier gas flow rate of 1.5 m s−1. Enhancement of 3–4 times was obtained at the edge position with an ablation location-related gas flow rate of 0.2 m s−1. To gain information on the mechanisms involved in these signal improvements, a small amount of water vapour was added into the plasma. This increased signal sensitivity by a factor of 3 using Ar as the carrier gas and by a factor of 1.7 using He, resulting in similar signal intensities being obtained in a wet plasma regardless of carrier gas used. These results demonstrate that the difference of elemental signal intensities obtained using He or Ar as the carrier gas can be dramatically alleviated under wet plasma conditions. These results also indicate that the enhancement in sensitivity using He as the carrier gas is not only because of the enhanced transport efficiency of small particles, but also due to the more effective vaporisation of the aerosol particles in the ICP. Under wet plasma conditions or with a high ablation location-related gas flow rate, U–Pb age dating of zircon could be obtained with similar accuracy using Ar instead of He as the carrier gas.
2 Instrumentation, fundamentals and chemometrics
2.1 Instrumentation
Instrumentation for ICP-OES is well established and groundbreaking developments are rare. The ICP has remained largely unchanged since the 1970s; modifications to the original torch design being more cosmetic than anything else. So it will be interesting to see how the new conical ICP torch, reported by Alavi et al.,48 fares. The authors claimed a ∼70% reduction in Ar use, 4× the power density, 1000 to 1700 K higher rotational temperature and a 5-fold increase in ne compared to current torches. They found also that the new design was more robust based on the Mg II/Mg I ratio criterion and suffered from fewer interferences due to easily ionisable elements. LODs were comparable with traditional torches.In another ICP development, Giersz et al.49 reported a microwave driven ICP, which utilised various couplers and field shapers to deliver longitudinal Ez and radial Er field components concentrated at the inner wall of the torch, thus generating an annular microwave ICP. This was operated with between 1 and 2 L min−1 Ar at 300 W power, and could accept the aerosol from nebulised samples (70 mg min−1). LODs obtained using a portable OES instrument were between 0.006 and 0.035 mg L−1. Another microwave ICP was developed by Schild et al.50 which was sustained with N2 and coupled to TOFMS. They cited cost restraints as the motivation for its development. They used a commercially available magnetron to cut down the cost of the power electronics. LODs were similar to Ar ICP-TOFMS and the main advantage of this configuration was the ‘cleaner’ spectrum, particularly above 60 m/z (presumably due to lower Tion in a source dominated by N2 and molecular ions thereof). This may well prove not to be true in all circumstances where a matrix is present, but it was possible to determine As at <100 ng L−1 in 1% NaCl solution.
Miniaturisation of instrumentation has received much attention over recent years. Zou et al.51 have reviewed (142 references) progress since 2000 in miniaturisation for AFS detection. They covered radiation and atom sources, detection and sample introduction systems, with a final section on portable instruments for field deployment. One of their conclusions was that electrically heated atomisers will probably replace flames and plasmas when battery technology advances to a sufficient level of development. This may then reduce the requirement for cumbersome sample pretreatment to produce a vapour phase analyte for introduction into the atom source. This last point was addressed by Kiss and Gaspar,52 who developed a microfluidic FAES system which included a thermospray/microburner system powered by a propane/butane gas lighter! LODs were 2.8, 0.68, 0.30, 0.66, and 1.1 mg L−1 for Li, Na, K, Rb, and Cs, respectively. They rightly point out that the system was limited by the low temperature of the flame, but suggested that it could be replaced by a more efficient excitation source. One such source which has recently received much attention is the DBD, often coupled with a vapour generation system in miniaturised devices. Several reports have appeared again this year, but there seem to be no real advances on previous research.
On a completely different theme, Kuwahara et al.53 developed a diode laser absorption system in conjunction with an arc-jet plasma wind tunnel. This was made from a high-temperature DC arc, formed from a thoriated tungsten cathode and a water-cooled copper anode, for atomisation of samples, then an expansion nozzle into a low-pressure jet. The laser beam was scanned 3 mm downstream of the nozzle exit with an incident angle of 80° with respect to the flow axis in order to measure both the Doppler shift and spectral width simultaneously. Xenon was injected into the argon plasma and the transition to 823.16 nm from a metastable state was used for detection. The LOD for Xe was estimated to be 140 ppm at a Xe flow rate of 3.7 × 105 g s−1.
2.2 Fundamentals
Weiss et al.55 studied the emission spectra of Ti I and Ti II in a Grimm GD in Ar and Ne, using transition rate diagrams. Excitation of Ti I levels in both discharges (in Ar and Ne) was found to be similar, and they identified Ar+–Ti charge transfer as a major mechanism for the excitation of Ti II in Ar. For Ti II levels up to an energy of ≈13 eV, they also found that cascade excitation was important in both Ar and Ne discharges. Shen et al.56 used RIMS to identify 417 high-lying excited even-parity levels of Nd I in the range from 32![[thin space (1/6-em)]](https://www.rsc.org/images/entities/char_2009.gif)
100 to 35300 cm−1 of Nd I. Out of these, 172 levels were assigned unique J values based on the J-momentum selection rule. Further additions to the trove of fundamental data have been made by the group including Li et al.57 (radiative lifetimes of 17 levels in Y I) and Wang et al.58 (radiative lifetimes of 5 levels in Be I).
Bond dissociation energies are useful to know e.g. when investigating molecular ion interferences in ICP-MS. Sevy et al.59 measured bond dissociation energies for HfC (4.4263 eV), NbC (5.6204 eV), TaC (4.9753 eV), ThC (5.0603 eV), TiC (3.8574 eV) and ZrC (4.89210 eV) using two-photon ionisation TOF-MS. Their method was predicated on assumption that the sharp predissociation threshold occurred at the thermochemical bond dissociation energy near the ground separated atom limit. By combining the D0 values with the ionisation energies of metal carbides and their related metals, they calculated the D0 values for the ionised species of Nb+–C = 5.390(4) eV, Ti+–C = 4.089(4) eV and V+–C = 3.724(3) eV.
2.2.2.1 Plasmas. There have been considerable advances in the understanding of ionisation processes in ICP-MS in recent years. One of the most useful tools that has been used to gain these insights is single particle analysis. Fuchs et al.60 studied the formation of Au+ ions by introducing 13 narrowly distributed citrate-capped AuNPs, with well-defined diameters from 15.4 to 100.1 nm. They also computationally modelled the transport, vaporisation and ionisation of the nanoparticles in the ICP and compared these to the experimental data. Their main aim was to obtain statistically reliable data for the intensity and duration of the ion clouds formed from particles with well-defined size characteristics. For example, 300 s measurements at 50 μS dwell times resulted in 3.5 × 106 data points containing ∼2500 single-particle events. A Java application was used to identify the start of a single-particle event then summed all the following events to calculate the total summed intensity per particle event, maximum intensity, and signal duration. These features were transferred into frequency distributions, Gaussian functions were fitted, if possible, and mean values were plotted versus particle diameter. The summed intensity increased from 10 to 1661 counts and the maximum intensity from 6 to 309 counts for AuNPs with diameters from 15.4 to 83.2 nm. The signal duration increased from 322 to 1007 μs upon increasing AuNP diameter. A comparison with simulated data revealed that the plasma temperature, and therefore the point of ionisation of the particles, was the same for all diameters. However, the maximum number density and extent of the Au+ ion cloud, depended on particle diameter.
Lesniewski et al.61 investigated the mechanism of Cl−formation in an atmospheric pressure afterglow reaction tube, coupled with ICP-MS, developed to facilitate high sensitivity detection of Cl−. The system works by bolting a 50 mm reaction tube to the front of the ICP torch box and aligning with the MS sampling orifice so that the carrier gas from the ICP passes into the reaction tube. They previously found that the introduction of sodium salts and methanol into the ICP improved sensitivity and wanted to investigate this further. They found that the Cl− signal became compound-independent at a carrier gas flow rate of 2.2 L min−1 and that the torch box exhaust flow rate had a large effect on Cl− sensitivity, probably because it affected sampling efficiency and ion-neutral reactions in the afterglow. Additionally it was reported that [NaClHCO2]− and [NaClNO2]− clusters, formed in the reaction tube, were important for Cl− detection from chlorinated compounds introduced into the ICP in conjunction with methanol and Na salts.
Zheng et al.62 studied the spatial and temporal dynamics of a pulsed, electrical spark microplasma used for spectrochemical analysis of aerosols. Two, 500 μm o.d. coaxial electrodes were separated by 5 mm. The W anode had a corona generated at its sharp tip, and the Pt cathode had a relatively flat tip to provide a surface for dry particle deposition. Aerosol particles of black carbon were collected on the cathode for 2 min, followed by pulsing of the microplasma. Peak emission intensities occurred between 0.5 and 1.3 mm above the cathode surface, with C I and C II emission peaking at 11 and 6 μs respectively. The Texc and ne values were estimated to be 23000 K, and 1.6 × 1017 cm−3 respectively.
Tan reported63 on development progress of a free software package called OPSIAL (Optical Plasma Spectral Calculation and Parameters Retrieval), which utilises a line-by-line radiative transfer algorithm to calculate optical plasma spectra. LTE, Doppler and collision broadening are the only line broadening mechanisms assumed to occur, so that lineshape is approximated by the Voigt function. The software also includes a ‘work in progress’ algorithm which identifies elemental spectral features – i.e. atomic emission lines – but needs further ‘training’ to make it comprehensive.
2.2.3 Interferences
Most researchers spend a great deal of effort trying to eliminate interferences, but there are instances when they can come in useful. For example, Jamari et al.65 used the polyatomic ions MF+to determine F, which ordinarily has too high an ionisation energy to be determined using ICP-MS. They used MS/MS with reaction cell capability to generate the MF+ ions using metals with high a MF+ bond dissociation energy compared to the complementary MO+ species. It was also necessary to choose elements with a low second ionisation energy, because the authors speculated that the MF+ ions were formed by interaction between F− and Ba2+. The highest sensitivity was exhibited by BaF+, with sub-ppm detection possible, but also with severe matrix effects.Another way to turn polyatomic ion interferences to advantage was described by Williams et al.66 who used the N2+/OH− emission intensity ratio as a diagnostic tool for identifying the best instrumental operating conditions in MIP-OES, and compared it to the widely used Mg II/Mg I ratio. They found that the N2+/OH− ratio was more sensitive to changes in instrument operating conditions, and had the advantage that no additional solution preparation step was required. The method was used to reduce some matrix effects by optimising conditions so that the plasma was as similar as possible when introducing standard solutions and samples. However, this was not sufficient in the presence of severe matrix effects; a better method being the use of signals for CN, N2, N2+ or OH species for signal correction.
2.3 Chemometrics
Alternative calibration strategies are included under this heading because they often involve the application of multivariate techniques. However, non-statistical methods are often used, and have the merit of simplicity. For example, Williams and Donati67 reported an interesting calibration strategy for ICP-MS-MS which made use of the ability to generate several chemical species of an element. Rather than use several standard solutions for a single m/z, only one two calibration solutions were used: S1, a 1:1 mixture of sample and standard solution; and S2, the same 1:1 volume ratio of sample and blank. The clever bit was to use several chemical species of a monoisotopic element for calibration (i.e. multiple oxide and ammonia species generated in a reaction cell) and to plot the signal intensities in S1 (x-axis) against S2 (y-axis) such that each point in the calibration plot corresponded to a different analyte species. An advantage of this approach was matrix matching, because both S1 and S2 contained the same amount of sample, but the method was faster than standard additions (though slower than external calibration). The method was validated by the determination of As, Co and Mn in CRMs tomato leaves (NIST 1573a) and bovine liver (NIST 1577b), with no significant differences found (Student’s t-test, 95% confidence level, n = 3). In a separate paper,68 the same group used a similar approach (probably the original piece of research), but using multiple isotopes of the same element rather than multiple species. The method was used for the determination of Ba, Cd, Se, Sn, and Zn in seven CRMs with different matrices (e.g., plant materials, flours, and water), with variable results – but no worse than other calibration methods.
Baghdadi et al.69 used a ‘total sum model’ for calibration in ICP-AES using two approaches: a classical weighted mean approach and the ‘excess variance approach’. Essentially, the calibration methods made use of multiple analyte lines and variances of the calibration curves to make a more robust calibration.
Cherviakouski70 published an alternative method for the correction of interferences caused by doubly charged ions in ICP-MS. Mathematically straightforward, it was based on measuring isotope signals in two modes: standard mode and using a collision cell for kinetic energy discrimination (KED). The two modes were used to calculate coefficients α and β. α was the coefficient of variation of the signal of analyte isotope in a transition from standard mode to KED mode, whereas β was the coefficient of variation of the signal of doubly charged ions in a transition from standard to KED mode. It is not entirely apparent from the paper how this works, but the authors claimed that α and β depended on the physical properties of ions and working mode of the collision cell. Hence, by selecting a corresponding working mode of the cell at which the value β – α attained a maximum, the error of calculation of the signal of the isotope to be determined could be reduced.
Shi71 used push-broom hyperspectral imaging (Pb-HSI) and sub-pixel shifting (SPS) to acquire spectral data from a DBD. In regular imaging the sampling distance is limited by the pixel size, but in SPS a smaller sampling distance compared to the pixel size results in a convoluted signal which is used to reconstruct a higher resolution spectrum. They characterised the effects of noise on the raw images and compared several noise altering schemes. Geometric super-resolved plasma OES images were obtained. They proposed to use the optimised SPS method to extract radially resolved maps from line-of-sight images, obtained in plasma-OES. This should result in higher resolution and an increased number of data points for compared to an Abel inversion.
3 Laser-based atomic spectrometry
Key fundamental studies and instrumental developments in laser-based atomic spectrometry are highlighted in this section. Atomic spectrometry techniques where the laser is used as either an intense energy source or a source of precise wavelength (e.g. LIBS and LAAS) are considered. However, studies related to LA-ICP-MS/AES, and to the use of lasers for fundamental studies of the properties of atoms or for thin film deposition are not reviewed.3.1 Laser induced breakdown spectroscopy (LIBS)
This section describes the latest instrumental developments and fundamental studies related to LIBS, but it does not cover detailed applications. Recent reviews include a concise overview of industrial applications,72 and the analysis of plant materials using LIBS and XRF.73 LIBS is highlighted as one of the most widespread techniques where a laser is used as an energy source to induce an optical plasma.Progress toward a technological standardisation is a common wish in the LIBS community. Several attempts at interlaboratory comparisons (using a set of certified replicas of homogeneous and stable samples) were conducted during 2008 in relation to the 5th international LIBS Conference (Berlin, Germany, 2008) and the LIBS’ 2016 conference (Chamonix Mont-Blanc, France). Results proved difficult to be interpret due to the large number of variable factors between participants. An approach to this was proposed by Motto-Ros et al.,74 to eliminate all experimental factors and only assess the contribution of the data treatment. A series of raw LIBS spectra were recorded using a single LIBS system, and the data shared to determine if the same conclusions were obtained by different analysts. Significant differences in outcomes were evident, highlighting that data processing strongly influenced predicted values of concentration, in addition to the effects of experimental conditions. Recommendations included the use of quadratic regression models and peak-area rather than peak-height measurements. The authors concluded that proper LIBS analytical performance could be obtained when data processing is conducted optimally, with equivalent performance compared to XRF and ICP-OES. A review of the methods of signal enhancement in LIBS was presented by Li et al.75 Different experimental setups and conditions were suggested for double-pulse excitation, spatial or magnetic confinement, spark discharge, etc. Additionally, several parameters such as plasma volume and emission intensity were evaluated and mechanisms of each enhancement method were discussed.
The basic concepts and applications of calibration, multivariate analysis (PCR, PLS and ANN) were described by Takahashi et al.76 Self-absorption of lines and matrix effects are known to cause non-linearity of the regression model, and different methods are proposed to correct these effects. Statistical methods were suggested to better identify correlations between the features of the spectra and analyte concentrations, particularly in the case of dealing with complex matrices, such as soils and rocks. The authors recommended the use of common figures of merit that express the overall normalised accuracy, such as the normalised root mean square errors (NRMSEs), when comparing accuracy between different setups and analytical methods.
Advances in data pre-processing, visualisation, dimensionality reduction, model building, classification, quantification and non-conventional multivariate mapping were reviewed by Porizka et al.77 in the context of approaches to utilise PCA and other multivariate data analysis algorithms in LIBS data processing. Software packages which implement multivariate methods are now readily available for LIBS applications, however, they can be considered as ‘black boxes’ with the algorithms hidden to the user. Safi et al.78 critically described the dangers of this ‘black box’ approach in LIBS multivariate analysis, and made suggestion on how to address it by using chemical–physical knowledge, which is at the base of any LIBS quantitative analysis.
A comprehensive overview of the current status of optical spectroscopy tools used with LIBS for isotopic analysis was performed by Harilal et al.79 Isotopic analysis is usually performed using mass spectrometry, however, rapid, in-field and non-contact isotopic analysis of solid materials requires the use of other complementary techniques based on optical spectroscopy, including LIBS. A key challenge is to detect the small isotope splitting seen in optical transitions of atoms and molecules with sufficient sensitivity for minor isotopes to be determined. The authors concluded that it is important to create a plasma plume with the appropriate physical conditions, maximum size, and long excited or ground state atom/molecular emission/absorption persistence. In short, an understanding of ‘when and where’ to look to obtain isotopic information in a laser induced plasma systems is critical.
A numerical method to evaluate the effects of various factors (e.g. optical density, plasma uniformity, noise, spectral resolution, etc.) on the performance of calibration free (CF)-LIBS was developed by Gornushkin et al.81 The CF algorithm incorporated certain improvements: it removed limits on the optical thickness of spectral lines that are used for the construction of the Saha–Boltzmann plot; retrieved the absorption path length (plasma diameter) directly from spectral lines; used the more realistic Voigt line profile function instead of the Lorentzian function; and employed the pre-calculated and tabulated thin-to-thick line ratios instead of approximating functions for self-absorption correction. CF-LIBS was also used by Borges et al.82 to determine the composition of a liquid sample. A frozen liquid sample was used to improve signal-to-noise ratios and to avoid problems of sample stability, such as liquid splash. An internal standard was added to the sample to achieve full control over the Saha–Boltzmann diagram, allowing a better determination of the plasma temperature value. The authors remarked that the selection of an internal standard with low ionisation potential and the use of accurate spectral parameters was required for a proper quantitative analysis. In addition, CF-LIBS required accurate knowledge of the temperature for accurate determination of analyte concentrations, so spectroscopic data were corrected by elimination of the self-absorption effect. Determinations of analyte concentrations obtained using CF-LIBS were only 3.3% different to those obtained using to MIP-AES.
Temperature dependence of the emission intensity in fs-LIBS was investigated by Wang et al.83 using a Ge laser at two wavelengths (400 and 800 nm) and different fluences. Ge I line emission at 422.66 nm decreased (up to 20%) with increasing sample temperature (from 20 °C to 200 °C). The authors attributed this to a rise in the average reflectivity of the Ge target, which they measured using an optical pump-probe. Similarly, the mechanisms responsible for intensity enhancement in double pulse fs-LIBS was investigated by Ahamer et al.84 The initial fs pulses at 800 nm were separated from the second harmonic radiation by a dichroic mirror, and delayed 300 ps before interacting with the sample material ablated by the 400 nm fs pulses. During this short delay time, the ablated material became spread over a few μm above the sample surface. Both laser pulses were focused on the same sample position with an angle of 45° between them. It was observed that enhancements in line intensities were larger, and the craters were smaller, for a lower energy first pulse. The spatio-temporal distribution of Ti and TiO molecules in fs-LIBS was investigated by Lee et al.85 using a weakly ionised plasma channel (a non-linear phenomena that takes place when the sample is out-of-focus). Plasma splitting processes were observed after the interaction of the weakly ionised plasma with the sample, accompanied by a change in the spatio-temporal distribution of molecules and atoms compared to sampling at the focus. Molecular emission was favoured at specific locations and was enhanced compared with atomic emission as the sample was moved underneath the laser focus. The authors suggested a potential use of this method to enhance or impede the formation of molecular and/or atomic species.
Raman spectrometry and LIBS were combined in a single instrument by Lednev et al.87 They used a pulsed solid state Nd:YAG laser, running in double pulse mode, with a short time delay between two successive pulses (∼10 μs). This allowed the acquisition of LIBS and Raman spectra at different moments but within a single laser flash-lamp pumping. The first low-energy laser pulse (power density far below ablation threshold) was used for Raman measurements, and the second powerful laser pulse was employed for LIBS analysis. The authors highlighted the high quality Raman/LIBS spectra acquisition, due to independent optimal gating for Raman and LIBS, and the absence of thermal alteration of the target during Raman measurements. This hybrid instrument was considered to be an efficient tool for identification of samples hidden by an opaque covering, for performing depth profiling analysis or remote sensing. A hybrid LIBS-Raman instrument (LIBRAS) was also developed by Lin et al.,88 which was capable of providing both atomic emission and vibrational spectra of polyatomic ions. LIBS and Raman signals were recorded simultaneously using the fundamental wavelength (1064 nm) and the second harmonic (532 nm) pulse beams emitted from a single pulse laser, respectively. An echelle spectrometer, equipped with an electron multiplying CCD, was employed to collect LIBS and Raman signals. The instrument was used to study the atomic emission lines and molecular vibrations from main components of mineral samples. Moros et al.89 used another type of hybrid LIBS/Raman instrument for the categorisation of rocks. This instrument was designed to remotely (5 m distance) and simultaneously register the elemental and molecular signatures of rocks under Martian surface conditions. Its capabilities were investigated through blind tests of 10 natural rocks with different origins.
A compact, robust and affordable laser source, which can be assembled in a portable LIBS system, was developed by Alvarez-Llamas et al.90 It consisted of a quasi-continuous wave diode pumped Nd:YAG laser with reduced size and low power consumption. The laser components were integrated in a compact module of 163 × 42 × 36 mm. The system yielded good results in terms of beam quality, pulse energy, repeatability and pulse duration, for different LIBS applications, and successfully used to classify different volcanic samples.
Quantitative analysis using LIBS requires high stability and accuracy. For applications outside the laboratory it is difficult to control the distance from the optical system to the sample surface, affecting the stability of the spectrum. Zhang et al.93 used PCA of LIBS plasma images to reduce spectral fluctuation. Images were collected coaxially with the laser beam and perpendicular to the sample surface. Data were pre-processed using PCA to reduce the dimensionality, and used to construct a model to directly correct the spectral line intensities. The method was validated using univariate and multivariate analysis to determine the concentrations of Cu, Cr, Mn and V in steel samples, with RSDs below 4% being achieved.
Low-intensity phase selective (PS)-LIBS has been used to discriminate between the elemental compositions of nanoparticles from the precursor vapour that coexist with them. In this technique, the excitation laser irradiance is controlled to be relatively low so that breakdown occurs only for nanoparticles. Improved sensitivity in PS-LIBS for in situ detection of titanium-dioxide nanoparticles during flame synthesis was recently achieved combining this technique with resonant excitation and the laser pulse tuned to the transition line of an excited neutral titanium atom in the formed nanoplasma.94 Secondary resonant excitation was used to improve sensitivity and achieve analyte-selective characterisation of nanoparticles in multi-component multiphase systems. For instance, the enhancement factor of this method for the analysis of TiO2 nanoparticles was up to 220 times with properly selected Ti I and Ti II emission lines.
Bierstedt et al.95 developed a novel LIBS approach for the analysis of gas-phase samples, by making use of an ultrasonic acoustic resonator. The effect of the acoustic standing wave inside the ultrasonic resonator, on the performance of an airborne LIBS, was investigated. A four-fold signal enhancement and discrimination between the sample and background gas was achieved. For example, oxygen (background gas) was statically trapped inside the pressure antinodes of the resonator, and the emission lines showed local minima at the pressure node positions. In comparison, the extrinsically applied and inwardly directed argon (analyte) flowed towards the low pressure regions, avoiding regions of elevated pressure. This local concentration leaded to a five-fold increase in Ar signal. At these positions inside the resonator the acoustic confinement yielded an increase in the signal-to-background ratio by a factor of >20. The authors claimed that this approach could pave the way towards a more robust and portable OES instrument for gas phase elemental analysis.
In situ detection of seawater, especially for hydrothermal areas, is an emerging field for LIBS applications. The effects of focusing geometry on a LIP in bulk water were investigated by Song et al.96 Four focusing arrangements were tested, with single-lens and double-lens combinations. The plasma morphology depended strongly on the laser-focusing geometry, with the double-lens combination (smaller effective focal length) found to generate a better localised plasma, thereby improving the spectral intensity, signal stability and SNR.
The presence of hydrogen in mineral structures is indicative of past hydrous conditions, hence, hydrogen is a critical element to measure on the surface of Mars. The Curiosity Rover uses LIBS on the ChemCam instrument to analyze rocks for their H emission signal at 656.6 nm, from which H can be quantified. Ytsma et al.97 investigated the H prediction accuracy of LIBS by making use of the largest suite of directly-measured geological standards analyzed to date. Univariate and multivariate methods produced roughly comparable results for individual instruments. However, prediction accuracy was found to dramatically suffer when data from one instrument were used to predict spectra obtained from a different spectrometer. Authors claimed that calibration transfer techniques might provide a solution to ameliorate such cross-instrument differences for hydrogen and other elements. Moreover, it was concluded that laser reproducibility is probably the ultimate limitation on detection and analysis of H on Mars.
One of the drawbacks of LIBS for imaging applications is the time required to evaluate the signals from the LIBS dataset. New data analysis strategies are required to deal with the complexity and number of emission spectra. Moncayo et al.98 developed a new methodology based on PCA, for the multivariate hyperspectral analysis of megapixel LIBS images. This could be used to extract information about mineral phases or identification of isolated elements.
3.2 Laser atomic absorption spectroscopy (LAAS)
A new, dual-beam atomic absorption technique was developed by Merten et al.99 for plasma diagnostics and isotope ratio measurements. Pseudo-continuum AAS measurements were performed using a commercial optical parametric oscillator, which allowed simultaneous measurement of all wavelengths and high spectral radiance of coherent pulsed laser probes. A unique prototype spectrograph with cylindrical optics, also provided nearly arbitrary resolution through simplified echelle grating multipassing. The analytical potential of this technique was demonstrated with spatially and temporally resolved measurements of magnesium metastable and lithium ground state optical depths in a LIP under reduced pressure conditions. A sample of Li metal was ablated under 1 torr of helium to obtain the spectrum of the Li resonance line at 671 nm. The spectra were sufficiently resolved to reveal overlap of the fine structure of the two Li isotopes, highlighting the potential of this technique for isotope ratio measurement.3.3 Cavity ringdown spectroscopy (CRDS)
A compact instrument based on a portable two channel CRDS instrument was developed by Li et al.100 for sensitive, temporal, in situ measurements of NO3 and N2O5 in ambient air. The NO3 and N2O5 were converted into the NO3 radical through thermal decomposition by optical extinction using a diode laser at 662.08 nm. Concentration of the target absorber was accomplished by comparing the fitted ring-down time constants in the presence and absence of the absorber, using the absorption cross section at the probing wavelength. LODs were of the order of ∼ppt, in an average time of 2.5 s. This was deemed to be adequate for quantifying the concentrations of short-lived trace gases NO3 and N2O5 under moderately polluted conditions. The portable CRDS instrument was deployed on a movable carriage to obtain vertical profiles. The carriage could ascend or descend at a rate of about 8 m min−1, or be positioned indefinitely at an arbitrary height. Dependence of the instrument’s sensitivity and accuracy on a variety of conditions was evaluated during two China-UK joint campaigns (in winter of 2016 and in summer of 2017). The instrument was demonstrated to make rapid measurements of atmospheric trace gases and capture their spatial and temporal variability, and might be useful to NOx chemistry on a large scale.4 Isotope analysis
Chemical separation and measurement of non-traditional stable isotopes (e.g. Ca, Cu, Hg, Mo, Te, etc.) was the subject of a number of analytical papers throughout the year. Instrumentation for these studies was again dominated by MC-ICP-MS, but it is clear that, for some systems, TIMS is the technique of choice. Yuan et al.101 even described feeding two MC-ICP-MS instruments simultaneously from the same laser ablation system! In comparison, investigations into potential advances in radiogenic isotope measurement continued to decline, and only focussed on improving analytical precision through detector improvements and data reduction protocols. In the world of Earth science analysis, the most common technique was LA-MC-ICP-MS, with the emphasis on micro-analysis of isotope ratios, and away from the traditional whole-rock measurement.4.1 Reviews
Mass-dependent fractionation of Ge isotopes was first identified in the late 1990’s, and has been used since in a variety of Earth, ocean and cosmochemistry applications. Meng and Hu102 reviewed many of the key aspects of Ge isotope analysis. This covered the various methods of chemical purification and the different introduction systems used to admit samples to the mass spectrometer, such as cyclonic nebulisation and hydride generation. Aspects of Ge mass spectrometry are documented including mass bias correction, isobaric interferences and isotopic fractionation notation. A brief coverage was also provided of the δ74/70Ge variations in geological reference materials.4.2 Isotope ratio analysis
Nd measurement at low concentrations was the focus of a study by Wakaki and Ishikawa.104 This presented an assessment of 143Nd/144Nd measurement by TIMS that used a total evaporation normalisation technique, which could be used to measure ratios on nanogram to sub-nanogram quantities of Nd. At 0.1 ng Nd, the external precision of reference material JNdi-1 was 184 ppm (0.009%, 2s), which equates to better than ≤± 1 epsilon Nd unit (one epsilon unit represents a one part per 10000 deviation from the chondritic unfractionated reservoir composition).
Ce isotopes have never achieved the ‘popularity’ of radiogenic Nd amongst geochemists, primarily because of the significant pitfalls in their measurement. These include isobaric interferences, tailing from the high-abundance 140Ce and the large dynamic range required to measure the major and minor isotopes. Willig and Stracke105 used TIMS to measure Ce isotopes utilising a combination of a 1010 Ω amplifier for 140CeO and 1011 Ω amplifiers for the other isotopes. The study concluded that interference on 142Ce (isobaric Nd) could be removed by aligning the 140Ce/142Ce ratio to be consistent with the 136Ce/142Ce used for the instrumental mass fractionation correction. The study also reported Ce isotopic data for several rock reference materials including BE-N, BIR-1, BCR-1, BCR-2 and BHVO-2.
Sr isotope measurement by laser ablation MC-ICP-MS was re-assessed in a study by Zhang et al.106 This evaluated ns and fs LA and found that the latter system essentially eliminated matrix-dependent ablation behaviour. In addition, selectively increasing the N2 in the sample carrier gas was found to suppress argide and doubly charged isobaric interferences. In addition, the Rb/Sr ratio in the ion beam was reduced by up to 1.5 times with the addition of 12 mL min−1 N2. Effectiveness of this gas addition was then tested using 87Sr/86Sr determinations of feldspars with variable Rb/Sr content.
Hg isotopes in low-concentration samples were measured using MC-ICP-MS with a cold-vapour generation system.108 Analysis of rock reference materials showed large variations in δ202Hg (from −1.24 to −2.47‰) but little variation in δ199Hg (from 0.01 to 0.11‰), indicating that mass dependent fractionation of Hg isotopes occurred during magmatic processes. Usefully, this study included analyses of the Hg isotopes in the reference materials BCR-2, BHVO-2, GSP-2 and GSR-2. Tang et al. [Tang #9326] used CVG-SF-ICP-MS to measure Hg isotope ratios. They investigated the use of Pb (208Pb/206Pb) and Tl as internal monitors of instrumental mass fractionation, and concluded that the bias in these isotope ratios was comparable to that of mercury, thus providing suitable internal monitors.
Amongst metals, Li has the largest proportional mass difference between its isotopes. Consequently, it is becoming a useful tracer of geological processes. Gou et al.109 investigated the performance of MC-ICP-MS when using various combinations of sampling and skimmer cone. They concluded that one particular instrument produced the most precise and accurate Li isotopic measurements using a configuration combining the standard-design sampling cone with the ‘X’ skimmer cone.
Measurement of Ag isotopes is hindered by a number of interferences, particularly in ore-related samples containing an abundance of transition metals. Guo et al.110 found the main isobaric interferences to be 65Cu40Ar+, 67Zn40Ar+ and doubly charged 208Pb2+ on 104Pd: the latter being used as a mass fractionation monitor. Isolation of Ag by ion exchange chromatography reduced the interferences by purifying ore samples such that ratios of Cu/Ag ≤ 50, Pb/Ag ≤ 10 and Zn/Ag ≤ 1 were achieved. Based on geological reference materials and ore samples, external reproducibility of δ109Ag was estimated to be between ±0.009 and 0.084‰, which is a useful precision given the current estimation of the range of geological materials is ±0.7‰.
Determination of Ca isotope ratios in biological and geological systems is possible using TIMS and MC-ICP-MS, with precisions of between 0.1 and 0.2‰ (2s). Karasinski et al.111 developed a method for δ44Ca/42Ca that coupled cation exchange chromatography with low-resolution MC-ICP-MS. Precision was ∼3 times worse than for equivalent measurements with off-line Ca isolation, but were achieved with significant time- and labour-saving, and without clean room preparation. Li et al.112 took the level of precision for Ca isotopes one step further with an external precision of 0.07‰ (2s) for δ44Ca/42Ca. This was achieved using a large-geometry double-focusing MC-ICP-MS. A particular problem with Ca isotope measurement via ICP-MS is the proximity of the 40Ar+ ion beam and its associated scatter. To minimise these effects, a ‘dummy bucket’ or blank Faraday detector was added to the multi-collector array to receive, and contain scatter from, the stream of 40Ar+ and 40Ca+ ions. The paper documented clearly the potential interferences on each of the Ca isotopes, and defined in turn how each was reduced. Key methods deployed were: measurement using a mass resolution of 2500; chemical separation; blank subtraction; and peak subtraction. Similar levels of precision were obtained for Ca isotopic measurements by Mondal and Chakrabarti113 using TIMS. This study corrected instrumental mass fractionation with a 43Ca–48Ca double spike and achieved δ44Ca/42Ca and δ44Ca/40Ca ratios with external reproducibility better than ±0.08‰.
It is known that isotope fractionation of elements such as Ca can occur during isolation via ion exchange chromatography. Zhu et al.114 considered the relationship between this column-induced fractionation and the bias induced by mass spectrometry. They authors found that the chromatographic fractionation could be greatly reduced, provided the double spike was added to, and well mixed with, the analyte prior to column chemistry. The inference was that the fractionation of both column and mass spectrometer (TIMS) followed the same exponential fractionation law. An outcome of this work was that the cut taken from the Ca fraction of the column should be narrowed, which would reduce the pollution of the analytical fraction with chromatographically similar elements such as Sr and K.
Inconsistent δ186W/184W measurements have often been observed in previous studies. These were evaluated by Kurzweil et al.115 who presented a protocol for stable W isotope measurement by MC-ICP-MS. The δ186W/184W values for rock reference material AGV-2 were found to be similar to some previous studies, but significantly different to others. They found that high Hf content and organic molecular interferences, derived from ion exchange resins during separation, influenced the precision and accuracy of measurement, particularly those involving a double spike. Overall their found external reproducibility of ±0.018‰ 2s for δ186W/184W.
Analysis of Li and B isotopes at low concentrations by MC-ICP-MS was investigated by Liu et al.116 One feature of their protocol was reduction of blanks in reagents and the processing environment, including using boron-free ULPA filtration hoods (a known contaminant in B isotope analysis). They reported long-term external reproducibility for δ11B and δ7Li of ±0.35‰ (2s) on sample concentrations of 10 ng mL−1.
Mo isotope fractionation was the subject of a study by Malinovsky and Kashulin.117 This focused on developing the technique for measuring precise and accurate Mo isotope ratios in plant materials by MC-ICP-MS. Their method used Pd as an internal mass fractionation monitor and was tested on sample concentrations as low as 10 ng g−1. The fractionation exponent (commonly known as the beta-factor), measured in term of 97/95Mo and 98/95Mo, was found to be within uncertainty of the expected values for kinetic and equilibrium fractionation. An interesting observation was the progressive within-plant fractionation of δ98Mo between roots, stems and leaves in certain species (e.g. common juniper).
Zhang et al.118 assessed the effects of the proportion of double spike used in stable IR analysis for elements such as Zn, Mo, Cd and Sn. They used experimental and theoretical data to demonstrate the correlation between double spike proportion and the offset in isotope ratios relative to the expected values of reference materials. Ratios were found to progressively increase (δ66/64Zn, δ114/110Cd and δ120/118Sn) or decrease (δ98/95Mo) with spike addition, with the expected ratio achieved at the ideal theoretical sample/double spike mixture. These relationships were ascribed to the sensitivity of the double spike algebraic solution to the angles of intersection between multiple planes in isotope ratio space. Overall, the study highlighted the need for a precise and constrained proportion of double spike in analytical protocols.
Fe isotopes are known to show isotopic fractionation during ns LA. Similar, although much reduced fractionation during fs LA, was studied by Zheng et al.119 They deduced that fractionation was related to space-charge effects in the MC-ICP-MS, produced by matrix effects associated with differing analyte compositions, rather than during the LA process. These matrix effects were found to be suppressed by the introduction of water as an aerosol into the ablation carrier gas immediately before the plasma, but the limited fractionation effects derived from the LA were not.
An improved method of Cr ion exchange separation was reported by Zhu.120 This outlined a three-step purification with four column procedures, developed to isolate Cr from low Cr samples with complex matrices. Combined with a reduction in blank to <1 ng, this enabled the accurate measurement of Cr in samples that contained only 500 ng. Rock standards along with biological and environmental materials were trialled with this separation and produced results similar to previously published δ53Cr values.
Pb isotopes were also measured by Delavault et al.122 using LA-MC-ICP-MS. They investigated the potential for achieving meaningful precision on Pb isotope ratios on small spot-sizes: of the order of 10–30 μm. Testing was done on 10 μm diameter 12 μm depth ablation craters in K-feldspar phenocrysts within Shap granite. Various 20xPb/204Pb ratios were found to be reproducible to within 1.4%, and were within 0.2% of the value achieved on 150 μm spot size which has ∼230 times the volume. These results highlighted the potential for isotopic micro-analysis of crystalline material to evaluate geological processes such as the evolution of the continental crust. Hamada et al.123 compared Pb isotope analysis of crystal-bound melt inclusions in basalt samples by LA-MC-ICP-MS with SIMS. It was found that the ICP technique improved the precision of 208Pb/206Pb by a factor of ∼10 with a similar ablation spot size of 30 μm.
A rigorous examination of sample, ablation system and mass spectrometric effects on U/Pb dating of zircons by LA-ICP-MS was completed by Thompson et al.124 They highlighted the need for tightly controlled operating conditions. Atmospheric air in the laser cell was found to affect U–Pb elemental fractionation during ablation and consequently influenced precision of the U–Pb age. The amount of air in the ablation cell was monitored using 40Ar16O+. It was suggested that zircon epoxy zircon mounts should be desiccated and evacuated prior to analysis to prevent outgassing during analysis, and keeping the laser fluence <2 J cm−2 would improve age determination.
Weber et al.125 measured 87Sr/86Sr on carbonate and phosphate reference materials, attempting to maintain a similar matrix between the sample and calibration standard. This was completed using solutions, and also ns and fs LA-MC-ICP-MS. Good agreement was achieved between solution and LA for all of the samples where the concentrations where higher than ∼500 μg g−1, indicating that the reference materials were suitable for calibrating and monitoring carbonate and phosphate microanalysis.
An alternative to LA-MC-ICP-MS is micro-sampling of materials using micro-drilling. This has the advantage of allowing purification of the element of interest by ion exchange chromatography prior to mass spectrometry. Such a micro-drilling and separation method was used by Di Salvo et al.126 to evaluate 87Sr/86Sr variations in both volcanic and biological/archaeological materials using TIMS. These authors found that material recovered by drilling the core and rim of plagioclase feldspar phenocrysts from the Nisyros volcano, Greece showed systematic differences in strontium isotopes. These equated to 87Sr/86Sr of 0.7040 and 0.7045: i.e. 0.07% difference. As this was significantly greater than the equivalent precision of the measurement of standards prepared using the same protocol (0.013%), it enabled these stages of crystal growth to be attributed to the preceding magmatic events and provided an insight to the volcanoes’ plumbing system.
Liu and Selby127 characterised a reference material for Re–Os concentration and isotopic measurements of petroleum and crude oil related products (RM 8505). The Re–Os system allows the direct dating of petroleum generation processes, and potentially to identify the source of the petroleum. The reference material, Venezuelan crude oil, was characterised for 187Re/188Os and 187Os/188Os with errors of 2.8% and 1.6% (1s) respectively.
A potential technique for radionuclide evaluation prior to nuclear decommissioning was presented by Kuwahara et al.130 They used a diode laser absorption spectrometer with a high-temperature Xe plasma. The instrument was demonstrated to be effective without the requirement to isolate the element of interest. With further development, it has the potential to fulfil the role of a rapid on-site analytical tool. Another type of field instrument was trialled by Lebedev et al.131 who examined the potential of laser-induced breakdown spectroscopy. A crucible of reference material held in a modest vacuum and heated with a 200 W current produced an atomic beam suitable for measurement with a diode laser. Preliminary results for the SRM960 natural uranium standard indicated precision of around ±3% for 238U abundance.
Lee et al.132 examined the potential for TIMS measurement of minor radionuclides in mixed U–Pu particles. Using a continuous heating method, the study achieved a precision of 1.6% (2s) for 235U/238U and ∼20% for 234U/238U. The particles measured were down to ∼1.8 μm in size, but it is unclear how much U and Pu these contained. Isotopes of U in particles were also measured by Park et al.133 These contained between 1 pg and 1 ng of U and were measured using TIMS with a Re filament. Replicates analyses yielded external precision of 0.3% (2s) for 235U/238U and 18% for 234U/238U. Ronzani et al.134 used LA-ICP-TOF-MS to measure μm-sized uranium particles and achieved better than 0.8% external precision for equal-atom 235U/238U standards and better than 10% for a U005 depleted uranium standard.
Pu isotope determination in urine was the subject of a paper by Ni et al.135 They used SF-ICP-MS to measure 240Pu/239Pu in blank urine (∼0.4 fg L−1) spiked with an isotopically characterised Pu reference material (NBS-947, 240Pu/239Pu = 0.242). Results indicated an external precision of better than 9% (2s) on 240Pu/239Pu with sub fg mL−1 Pu concentrations. Pu isotope in particulates were also determined by Wang et al.,136 using LA-MC-ICP-MS to ablate particles with a 30 μm laser spot size. Accuracy and precision were found to be best with analyses longer than 15 min, and 240Pu/239Pu better than ±1.4% was achieved.
4.3 New developments
Tellurium has a range of isotope ratios in natural materials equating to 2‰ δ130/125Te. A method for high-precision analysis of Te isotopes was reported by Fukami et al.,137 using MC-ICP-MS with a 125Te and 128Te double-spike to correct for instrumental mass fractionation. Results yielded 0.027‰ and 0.035‰ external reproducibility (2s) for δ130/125Te, for dry and wet plasma conditions respectively. Dry plasma conditions were favoured due to lower potential isobaric hydride interferences.Raw isotope data obtained using LA usually requires more sympathetic treatment than typical processing routines written for MC-ICP-MS or TIMS acquisitions. Willmes et al.138 have developed an application to reduce 87Sr/86Sr IR data in a standardised way. This freeware enabled corrections, noise reduction and time resolution to be applied to the inevitably large amounts of data produced by a typical LA session. The source code for the application was made available, which may promote future development of the software.
Xie et al.139 developed a new type of sample cell for LA, specifically designed to reduce the influence of sample location within the cell on the measured isotopic ratios, the so-called ‘position effect’. This effect has been ascribed to the variable transport efficiency of particles of different sizes at different sampling positions which, combined with particle size effecting isotope fractionation, results in imprecision in MC-ICP-MS determinations.
Wu et al.140 examined the precision of isotope ratio data obtained using ICP-MS operated in different signal acquisition modes: pulse, analog and dual. Optimal performance was achieved using pulse-mode with the ion counting detector and a signal intensity of ∼1 × 106 ± 0.3 counts per s. A key feature of their cell design was to suppress gas flow turbulence adjacent to the samples, was achieved using a two-stage buffer through which the gas flow was homogenised. Tests based on Fe isotope analysis of a reference pyrite indicated that fractionation related to the position effect was negligible.
If you have plenty of mass spectrometers in your laboratory, you may as well use them. That is exactly what Yuan et al.101 did. Their study coupled a ns LA system to two MC-ICP-MS instruments with the objective of measuring Pb and S isotopes simultaneously. The reported results were consistent with stand-alone measurement of the same isotopes. As the material measured was sulphides (pyrite, chalcopyrite, galena and sphalerite) there was ample sulphur present. This allowed the ablation stream to be split between the two instruments and varied: 1:1 for high Pb sample and 1:5 in favour of the Pb instrument where Pb content was more limited.
5 Glossary of abbreviations
Whenever suitable, elements may be referred to by their chemical symbols and compounds by their formulae. The following abbreviations may be used without definition. Abbreviations also cover the plural form.| 2D | Two dimensional |
| 3D | Three dimensional |
| AA | Atomic absorption |
| AAS | Atomic absorption spectrometry |
| ADI | Ambient desorption ionisation |
| AES | Atomic emission spectrometry |
| AF | Atomic fluorescence |
| AF4 | Asymmetric flow field-flow fractionation |
| AFM | Atomic force microscopy |
| AFS | Atomic fluorescence spectrometry |
| ANN | Artificial neural network |
| APDC | Ammonium pyrrolidine dithiocarbamate |
| APGD | Atmospheric pressure glow discharge |
| APS | Aerodynamic particle sizer |
| BGA | Buffer gas assisted |
| CCD | Charge coupled detector |
| CCP | Capacitively coupled plasma |
| CDSS | Continuous direct solid sampling |
| CRM | Certified reference material |
| CRS | Cavity ringdown spectroscopy |
| CS | Continuum source |
| CV | Cold vapour |
| CVG | Chemical vapour generation |
| DBD | Dielectric barrier discharge |
| DC | Direct current |
| DC-GD-QMS | Direct current glow discharge quadrupole mass spectrometry |
| DDW | Distilled deionised water |
| DL | Diode laser |
| DLTV | Diode laser thermal vaporisation |
| DMA | Dimethylarsenic |
| DOF-MS | Distance of flight mass spectrometry |
| DOTA | 1,4,7,10-Tetraazacyclo-dodecane-N,N′,N′′,N′′′-tetra acetic acid |
| ECAD | Electrolyte cathode atmospheric pressure discharge |
| EDB-LIBS | Electrodynamic balance trap laser induced breakdown spectroscopy |
| ED-XRF | Energy dispersive X-ray fluorescence |
| ES-MS | Electrospray mass spectrometry |
| ETV | Electrothermal vaporisation |
| ETV-AAS | Electrothermal vaporisation atomic absorption spectrometry |
| ETV-ICP-MS | Electrothermal vaporisation inductively coupled plasma mass spectrometry |
| EVG | Electrochemical vapour generation |
| FAPA | Flowing atmospheric pressure afterglow |
| FF | Flame furnace |
| FFPN | Flow focussing pneumatic nebuliser |
| FI | Flow injection |
| FMPS | Fast mobility particle sizer |
| fs | Femto second |
| FWHM | Full width at half maximum |
| GD | Glow discharge |
| GD-MS | Glow discharge mass spectrometry |
| GD-OES | Glow discharge optical emission spectrometry |
| GFAAS | Graphite furnace atomic absorption spectrometry |
| HG | Hydride generation |
| HG-AAS | Hydride generation atomic absorption spectrometry |
| HG-AFS | Hydride generation atomic fluorescence spectrometry |
| HPLC-ICP-MS | High performance liquid chromatography inductively coupled plasma mass spectrometry |
| HR | High resolution |
| HR-CS-GFAAS | High resolution continuum source graphite furnace atomic absorption spectrometry |
| hTISIS | Heated torch integrated sample introduction system |
| HV | High voltage |
| ICHPN | In-column high-pressure nebuliser |
| ICP-AES | Inductively coupled plasma atomic emission spectrometry |
| ICP-DOF-MS | Inductively coupled plasma distance of flight mass spectrometry |
| ICP-MS | Inductively coupled plasma mass spectrometry |
| ICP-MS/MS | Triple quadrupole inductively coupled plasma mass spectrometry |
| ICP-MC-MS | Inductively coupled plasma multi-collector mass spectrometry |
| ICP-OES | Inductively coupled plasma optical emission spectrometry |
| ICP-QMS | Inductively coupled plasma quadrupole mass spectrometry |
| ICP-QQQ-MS | Inductively coupled plasma triple quadrupole mass spectrometry |
| ICP-TOF-MS | Inductively coupled plasma time-of-flight mass spectrometry |
| ID | Isotope dilution |
| IDA | Isotope dilution analysis |
| ID-ICP-MS | Isotope dilution inductively coupled plasma mass spectrometry |
| ID-MRM-MS | Isotope dilution multiple reaction monitoring mass spectrometry |
| ID-MS | Isotope dilution mass spectrometry |
| IL | Ionic liquid |
| IR | Isotope ratio |
| IRMS | Isotope ratio mass spectrometry |
| IT-SPME | In-tube solid-phase microextraction |
| LA | Laser ablation |
| LA-ICP-MS | Laser ablation inductively coupled plasma mass spectrometry |
| LA-MC-ICP-MS | Laser ablation multi-collector inductively coupled plasma mass spectrometry |
| LAMIS | Laser ablation molecular isotopic spectrometry |
| LC | Liquid chromatography |
| LCGD | Liquid cathode glow discharge |
| LDR | Linear dynamic range |
| LEP | Liquid electrode microplasma |
| LI | Laser ionisation |
| LIBS | Laser induced breakdown spectroscopy |
| LIF | Laser induced fluorescence |
| LOD | Limit of detection |
| LOV | Lab-on-a-valve |
| LPME | Liquid phase microextraction |
| MALDI | Matrix-assisted laser desorption ionisation |
| MC-ICP-MS | Multi-collector inductively coupled plasma mass spectrometry |
| MinLC-DAD | Miniaturised liquid chromatography with diode array detection |
| MIP | Microwave induced plasma |
| MIP-OES | Microwave induced plasma optical emission spectrometry |
| MMA | Monomethylarsenic |
| MNP | Magnetic nano-particle |
| MP | microsecond pulsed |
| MPT | Microwave plasma torch |
| MSIS | Multimode sample introduction system |
| MW-LIBS | Microwave assisted LIBS |
| MWP | Microwave plasma |
| nanoHPLC | Nanolitre high-performance liquid chromatography |
| Nd:YAG | Neodymium doped:yttrium aluminum garnet |
| n e | Electron number density |
| NIST | National Institute of Standards and Technology |
| NP | Nano-particle |
| NRMSEs | Normalised root mean square errors |
| ns | Nano second |
| o.d. | Outer diameter |
| OPO | Optical parametric oscillator |
| PCA | Principal components analysis |
| PCR | Polymerase chain reaction |
| PDMS | Polydimethylsiloxane |
| PF | Particle flow |
| PFH | Perfluorohexane |
| PLS | Partial least squares |
| PN | Pneumatic nebuliser |
| PNC | Particle number concentration |
| ppb | Parts per billion (10−9) |
| ppm | Parts per million (10−6) |
| ppq | Parts per quadrillion (10−15) |
| ppt | Parts per trillion (10−12) |
| PSD | Particle size distribution |
| PVG | Photochemical vapour generation |
| PVP | Polyvinylpyrrolidone |
| Q | Quadrupole |
| QTF | Quartz tube furnace |
| RDD | Rotating disc diluter |
| RF | Radiofrequency |
| RIMS | Resonance ionisation mass spectrometry |
| RSD | Relative standard deviation |
| RVM | Relevance vector machine |
| SALD | Substrate assisted laser desorption |
| SBR | Signal-to-background ratio |
| SCGD | Solution cathode glow discharge |
| SEM | Scanning electron microscopy |
| SIBS | Spark-induced breakdown spectroscopy |
| SIMS | Secondary ionisation mass spectrometry |
| SMPS | Scanning mobility particle sizer |
| sNP | Single nanoparticle |
| SNR | Signal-to-noise ratio |
| sp | Single particle |
| spICP-MS | Single particle inductively coupled plasma mass spectrometry |
| SPME | Solid phase microextraction |
| SRM | Standard reference material |
| STM | Scanning tunnelling microscopy |
| SVR | Support vector regression |
| TDLAAS | Tunable diode laser atomic absorption spectroscopy |
| T e | Electron temperature |
| TE | Transport efficiency |
| TEM | Transmission electron microscopy |
| TGA | Thermogravimetric analysis |
| T gas | Gas temperature |
| TIMS | Thermal ionisation mass spectrometry |
| T ion | Ionisation temperature |
| TOF | Time-of-flight |
| TOF-MS | Time-of-flight mass spectrometry |
| T rot | Rotational temperature |
| UV | Ultraviolet |
| VG | Vapour generation |
| XPS | X-ray photoelectron spectroscopy |
| XRF | X-ray fluorescence |
Conflicts of interest
There are no conflicts of interest.References
- O. T. Butler, W. R. L. Cairns, J. M. Cook, C. M. Davidson and R. Mertz-Kraus, J. Anal. At. Spectrom., 2018, 33(1), 8–56 RSC.
- S. Carter, R. Clough, A. Fisher, B. Gibson, B. Russell and J. Waack, J. Anal. At. Spectrom., 2018, 33(11), 1802–1848 RSC.
- R. Clough, C. F. Harrington, S. J. Hill, Y. Madrid and J. F. Tyson, J. Anal. At. Spectrom., 2018, 33(7), 1103–1149 RSC.
- E. H. Evans, J. Pisonero, C. M. M. Smith and R. N. Taylor, J. Anal. At. Spectrom., 2018, 33(5), 684–705 RSC.
- A. Taylor, N. Barlow, M. P. Day, S. Hill, N. Martin and M. Patriarca, J. Anal. At. Spectrom., 2018, 33(3), 338–382 RSC.
- C. Vanhoof, J. R. Bacon, A. T. Ellis, L. Vincze and P. Wobrauschek, J. Anal. At. Spectrom., 2018, 33(9), 1413–1431 RSC.
- R. Sanchez, S. Maestre, S. Prats and J. L. Todoli, Anal. Chem., 2017, 89(24), 13618–13625 CrossRef CAS PubMed.
- C. K. Su and W. C. Chen, Microchim. Acta, 2018, 185(5), 268 CrossRef PubMed.
- Y. J. Luo, Y. Yang, Y. Lin, Y. F. Tian, L. Wu, L. Yang, X. D. Hou and C. B. Zheng, Anal. Chem., 2018, 90(3), 1547–1553 CrossRef CAS PubMed.
- L. Cid-Barrio, F. Calderon-Celis, P. Abasolo-Linares, M. L. Fernandez-Sanchez, J. M. Costa-Fernandez, J. R. Encinar and A. Sanz-Meder, TrAC, Trends Anal. Chem., 2018, 104, 148–159 CrossRef CAS.
- G. Y. Xiao, B. B. Chen, M. He, K. W. Shi, X. Zhang, X. T. Li, Q. M. Wu, D. W. Pang and B. Hu, Spectrochim. Acta, Part B, 2017, 138, 90–96 CrossRef CAS.
- X. T. Li, B. B. Chen, M. He, G. Y. Xiao and B. Hu, Talanta, 2018, 176, 40–46 CrossRef CAS PubMed.
- R. Liu, C. Q. Wang, Y. M. Xu, J. Y. Hu, D. Y. Deng and Y. Lv, Anal. Chem., 2017, 89(24), 13269–13274 CrossRef CAS PubMed.
- T. K. Anderlini and D. Beauchemin, J. Anal. At. Spectrom., 2018, 33(1), 127–134 RSC.
- T. K. Anderlini and D. Beauchemin, J. Anal. At. Spectrom., 2018, 33(6), 1068–1075 RSC.
- A. Al Hejami and D. Beauchemin, J. Anal. At. Spectrom., 2018, 33(5), 738–744 RSC.
- H. Y. Cheng, W. W. Zhang, Y. C. Wang and J. H. Liu, J. Chromatogr., 2018, 1575, 59–65 CrossRef CAS PubMed.
- D. Foppiano, M. Tarik, E. G. Muller and C. Ludwig, J. Anal. At. Spectrom., 2018, 33(9), 1493–1499 RSC.
- D. Foppiano, M. Tarik, E. G. Muller and C. Ludwig, J. Anal. At. Spectrom., 2018, 33(9), 1500–1505 RSC.
- S. Naasz, S. Weigel, O. Borovinskaya, A. Serva, C. Cascio, A. K. Undas, F. C. Simeone, H. J. P. Marvin and R. J. B. Peters, J. Anal. At. Spectrom., 2018, 33(5), 835–845 RSC.
- S. Myashita, S. Fujii and K. Inagaki, Bunseki Kagaku, 2017, 66(9), 663–676 CrossRef.
- J. Hu, D. Deng, R. Liu and Y. Lv, J. Anal. At. Spectrom., 2018, 33(1), 57–67 RSC.
- E. Novakova, M. Rybinova, J. Hranicek, P. Rychlovsky and V. Cerveny, J. Anal. At. Spectrom., 2018, 33(1), 118–126 RSC.
- Y. H. Qi, X. F. Mao, J. X. Liu, X. Na, G. Y. Chen, M. T. Liu, C. M. Zheng and Y. Z. Qian, Anal. Chem., 2018, 90(10), 6332–6338 CrossRef CAS PubMed.
- P. Zurynkova, J. Dedina and J. Kratzer, Anal. Chim. Acta, 2018, 1010, 11–19 CrossRef CAS PubMed.
- X. Liu, Z. L. Zhu, Z. Y. Bao, H. T. Zheng and S. H. Hu, Spectrochim. Acta, Part B, 2018, 141, 15–21 CrossRef CAS.
- A. Maratta Martínez, S. Vázquez, R. Lara, L. D. Martínez and P. Pacheco, Spectrochim. Acta, Part B, 2018, 140, 22–28 CrossRef.
- Z. R. Lei, L. Q. Chen, K. Hu, S. C. Yang and X. D. Wen, Spectrochim.Acta, Part A, 2018, 203, 522–527 CrossRef CAS PubMed.
- J. Vyhnanovsky, J. Kratzer, O. Benada, T. Matousek, Z. Mester, R. E. Sturgeon, J. Dedina and S. Musil, Anal. Chim. Acta, 2018, 1005, 16–26 CrossRef CAS PubMed.
- K. A. Romanovskiy, M. A. Bolshov, A. V. Munz, Z. A. Temerdashev, M. Y. Burylin and K. A. Sirota, Talanta, 2018, 187, 370–378 CrossRef CAS PubMed.
- Z. R. Zou, F. J. Xu, Y. F. Tian, X. M. Jiang and X. D. Hou, J. Anal. At. Spectrom., 2018, 33(7), 1217–1223 RSC.
- Z. R. Zou, Y. F. Tian, W. Zeng, X. D. Hou and X. M. Jiang, Microchem. J., 2018, 140, 189–195 CrossRef CAS.
- B. Meermann and V. Nischwitz, J. Anal. At. Spectrom., 2018, 33(9), 1432–1468 RSC.
- R. A. Gonzalez-Fuenzalida, Y. Moliner-Martinez, C. Molins-Legua and P. Campins-Falco, Anal. Chim. Acta, 2019, 1045, 23–41 CrossRef CAS PubMed.
- V. L. Dressler, E. I. Muller and D. Pozebon, in Metallomics: The Science of Biometals, ed. M. A. Z. Arruda, 2018, vol. 1055, pp. 139–181 Search PubMed.
- G. H. Niu, Q. Shi, X. Yuan, J. Wang, X. Wang and Y. X. Duan, J. Anal. At. Spectrom., 2018, 33(11), 1954–1961 RSC.
- S. C. Yao, J. L. Xu, X. Zhang, L. F. Zhang, Z. M. Lu and J. D. Lu, J. Anal. At. Spectrom., 2018, 33(6), 986–991 RSC.
- G. Gamez and K. Finch, Spectrochim. Acta, Part B, 2018, 148, 129–136 CrossRef CAS.
- Z. Xing, M. Yang, W. Guo, L. L. Jin, Z. F. Liu and S. H. Hu, Spectrochim. Acta, Part B, 2018, 147, 141–148 CrossRef CAS.
- J. Yu, X. M. Zhang, Q. F. Lu, D. X. Sun, X. Wang, S. W. Zhu, Z. C. Zhang and W. Yang, Spectrochim. Acta, Part B, 2018, 145, 64–70 CrossRef CAS.
- J. Yu, S. W. Zhu, Q. F. Lu, Z. C. Zhang, D. X. Sun, X. M. Zhang, X. Wang and W. Yang, Anal. Lett., 2018, 51(13), 2128–2140 CrossRef CAS.
- L. Hang, Z. Y. Xu, Z. B. Yin and W. Hang, Anal. Chem., 2018, 90(22), 13222–13228 CrossRef CAS PubMed.
- J. M. Wang, S. Y. Li, P. C. Zheng, K. Liu and P. F. Tang, J. Anal. At. Spectrom., 2018, 33(6), 1014–1020 RSC.
- P. C. Zheng, S. Y. Li and J. M. Wang, Anal. Lett., 2018, 51(6), 860–869 CrossRef CAS.
- M. Hola, J. Ondracek, H. Novakova, M. Vojtisek-Lom, R. Hadravova and V. Kanicky, Spectrochim. Acta, Part B, 2018, 148, 193–204 CrossRef CAS.
- M. Hola, Z. Salajkova, A. Hrdlicka, P. Porizka, K. Novotny, L. Celko, P. Sperka, D. Prochazka, J. Novotny, P. Modlitbova, V. Kanicksy and J. Kaiser, Anal. Chem., 2018, 90(20), 11820–11826 CrossRef CAS PubMed.
- T. Luo, Z. C. Hu, W. Zhang, D. Gunther, Y. S. Liu, K. Q. Zong and S. H. Hu, J. Anal. At. Spectrom., 2018, 33(10), 1655–1663 RSC.
- S. Alavi, T. Khayamian and J. Mostaghimi, Anal. Chem., 2018, 90(5), 3036–3044 CrossRef CAS PubMed.
- J. Giersz, K. Jankowski, A. Ramsza and E. Reszke, Spectrochim. Acta, Part B, 2018, 147, 51–58 CrossRef CAS.
- M. Schild, A. Gundlach-Graham, A. Menon, J. Jevtic, V. Pikelja, M. Tanner, B. Hattendorf and D. Gunther, Anal. Chem., 2018, 90(22), 13443–13450 CrossRef CAS PubMed.
- Z. R. Zou, Y. J. Deng, J. Hu, X. M. Jiang and X. D. Hou, Anal. Chim. Acta, 2018, 1019, 25–37 CrossRef CAS PubMed.
- A. Kiss and A. Gaspar, Anal. Chem., 2018, 90(10), 5995–6000 CrossRef CAS PubMed.
- A. Kuwahara, Y. Aiba, T. Nankawab and M. Matsuic, J. Anal. At. Spectrom., 2018, 33(5), 893–896 RSC.
- P. S. Doidge, Spectrochim. Acta, Part B, 2018, 143, 78–90 CrossRef CAS.
- Z. Weiss, E. B. M. Steers and J. C. Pickering, Spectrochim. Acta, Part B, 2018, 144, 20–28 CrossRef CAS.
- X. P. Shen, W. L. Wang, L. H. Zhai, H. Deng, J. Xu, X. L. Yuan, G. Y. Wei, W. Wang, S. Fang, Y. Y. Su and Z. M. Li, Spectrochim. Acta, Part B, 2018, 145, 96–98 CrossRef CAS.
- Q. Li, Q. Yu, X. H. Wang, Y. Gao, Q. Wang, Y. M. Gong and Z. W. Dai, J. Opt. Soc. Am. B, 2018, 35(9), 2244–2250 CrossRef CAS.
- X. H. Wang, P. Quinet, Q. Li, Q. Yu, Y. F. Li, Q. Wang, Y. M. Gong and Z. W. Dai, J. Quant. Spectrosc. Radiat. Transfer, 2018, 212, 112–119 CrossRef CAS.
- A. Sevy, D. J. Matthew and M. D. Morse, J. Chem. Phys., 2018, 149(4), 044306 CrossRef PubMed.
- J. Fuchs, M. Aghaei, T. D. Schachel, M. Sperling, A. Bogaerts and U. Karst, Anal. Chem., 2018, 90(17), 10271–10278 CrossRef CAS PubMed.
- J. E. Lesniewski, W. P. McMahon and K. Jorabchi, J. Anal. At. Spectrom., 2018, 33(11), 1981–1992 RSC.
- L. N. Zheng, P. Kulkarni and P. Diwakar, Spectrochim. Acta, Part B, 2018, 144, 55–62 CrossRef CAS.
- X. Tan, J. Anal. At. Spectrom., 2018, 33(11), 1867–1874 RSC.
- Y. Yamamoto, A. Tagami, T. Shiarasaki, A. Yonetani, T. Yamamoto and S. Imai, Spectrochim. Acta, Part B, 2018, 142, 55–61 CrossRef CAS.
- N. L. A. Jamari, A. Behrens, A. Raab, E. M. Krupp and J. Feldmann, J. Anal. At. Spectrom., 2018, 33(8), 1304–1309 RSC.
- C. B. Williams, B. T. Jones and G. L. Donati, J. Anal. At. Spectrom., 2018, 33(7), 1224–1232 RSC.
- C. B. Williams and G. L. Donati, J. Anal. At. Spectrom., 2018, 33(5), 762–767 RSC.
- A. Virgilio, J. A. Nobrega and G. L. Donati, Anal. Bioanal. Chem., 2018, 410(3), 1157–1162 CrossRef CAS PubMed.
- S. Baghdadi, M. Crozet, S. Gracia, J. L. Dautheribes, C. Rivier and S. Picart, J. Anal. At. Spectrom., 2018, 33(11), 1903–1909 RSC.
- K. I. Cherviakouski, J. Anal. Chem., 2017, 72(14), 1434–1440 CrossRef CAS.
- S. Y. Shi, X. X. Gong, Y. Mu, K. Finch and G. Gamez, J. Anal. At. Spectrom., 2018, 33(10), 1745–1752 RSC.
- R. Noll, C. Fricke-Begemann, S. Connemann, C. Meinhardt and V. Sturm, J. Anal. At. Spectrom., 2018, 33(6), 945–956 RSC.
- G. G. A. de Carvalho, M. B. B. Guerra, A. Adame, C. S. Nomura, P. V. Oliveira, H. W. P. de Carvalho, D. Santos, L. C. Nunes and F. J. Krug, J. Anal. At. Spectrom., 2018, 33(6), 919–944 RSC.
- V. Motto-Ros, D. Syvilay, L. Bassel, E. Negre, F. Trichard, F. Pelascini, J. El Haddad, A. Harhira, S. Moncayo, J. Picard, D. Devismes and B. Bousquet, Spectrochim. Acta, Part B, 2018, 140, 54–64 CrossRef CAS.
- Y. C. Li, D. Tian, Y. Ding, G. Yang, K. Liu, C. H. Wang and X. Han, Appl. Spectrosc. Rev., 2018, 53(1), 1–35 CrossRef.
- T. Takahashi and B. Thornton, Spectrochim. Acta, Part B, 2017, 138, 31–42 CrossRef CAS.
- P. Porizka, J. Klus, E. Kepes, D. Prochazka, D. W. Hahn and J. Kaiser, Spectrochim. Acta, Part B, 2018, 148, 65–82 CrossRef CAS.
- A. Safi, B. Campanella, E. Grifoni, S. Legnaioli, G. Lorenzetti, S. Pagnotta, F. Poggialini, L. Ripoll-Seguer, M. Hidalgo and V. Palleschi, Spectrochim. Acta, Part B, 2018, 144, 46–54 CrossRef CAS.
- S. S. Harilal, B. E. Brumfield, N. L. LaHaye, K. C. Hartig and M. C. Phillips, Appl. Phys. Rev., 2018, 5(2), 021301 Search PubMed.
- T. Dietz, P. Kohns and G. Ankerhold, Spectrochim. Acta, Part B, 2018, 148, 51–59 CrossRef CAS.
- I. B. Gornushkin, T. Volker and A. Y. Kazakov, Spectrochim. Acta, Part B, 2018, 147, 149–163 CrossRef CAS.
- F. D. Borges, J. U. Ospina, G. D. Cavalcanti, E. E. Farias, A. A. Rocha, P. Ferreira, G. C. Gomes and A. Mello, J. Anal. At. Spectrom., 2018, 33(4), 629–641 RSC.
- X. Wang, A. Chen, L. Sui, Y. Wang, D. Zhang, S. Li, Y. Jiang and M. Jin, J. Anal. At. Spectrom., 2018, 33(2), 168–174 RSC.
- C. M. Ahamer and J. D. Pedarnig, Spectrochim. Acta, Part B, 2018, 148, 23–30 CrossRef CAS.
- Y. Lee, X. Mao, G. C. Y. Chan, J. Gonzalez, R. E. Russo and V. Zorba, J. Anal. At. Spectrom., 2018, 33(11), 1875–1883 RSC.
- X. H. Wang, Z. S. Liang, Y. F. Meng, T. T. Wang, W. Hang and B. L. Huang, Spectrochim. Acta, Part B, 2018, 141, 1–6 CrossRef CAS.
- V. N. Lednev, S. M. Pershin, P. A. Sdvizhenskii, M. Y. Grishin, A. N. Fedorov, V. V. Bukin, V. B. Oshurko and A. N. Shchegolikhin, Anal. Bioanal. Chem., 2018, 410(1), 277–286 CrossRef CAS PubMed.
- Q. Y. Lin, S. Wang, G. M. Guo, Y. H. Tian and Y. X. Duan, Instrum. Sci. Technol., 2018, 46(2), 163–174 CrossRef CAS.
- J. Moros, M. M. ElFaham and J. J. Laserna, Anal. Chem., 2018, 90(3), 2079–2087 CrossRef CAS PubMed.
- C. Alvarez-Llamas, C. Roux and O. Musset, Spectrochim. Acta, Part B, 2018, 148, 118–128 CrossRef CAS.
- Y. Tang, J. M. Li, Z. Q. Hao, S. S. Tang, Z. H. Zhu, L. B. Guo, X. Y. Li, X. Y. Zeng, J. Duan and Y. F. Lu, Opt. Express, 2018, 26(9), 12121–12130 CrossRef CAS PubMed.
- Y. Tang, L. B. Guo, J. M. Li, S. S. Tang, Z. H. Zhu, S. X. Ma, X. Y. Li, X. Y. Zeng, J. Duan and Y. F. Lu, J. Anal. At. Spectrom., 2018, 33(10), 1683–1688 RSC.
- P. Zhang, L. X. Sun, H. B. Yu, P. Zeng, L. F. Qj and Y. Xin, Anal. Chem., 2018, 90(7), 4686–4694 CrossRef CAS PubMed.
- G. Xiong, S. Li and S. D. Tse, Spectrochim. Acta, Part B, 2018, 140, 13–21 CrossRef CAS.
- A. Bierstedt, U. Panne and J. Riedel, J. Anal. At. Spectrom., 2018, 33(1), 135–140 RSC.
- J. J. Song, J. J. Guo, Y. Tian, B. Y. Xue, Y. Lu and R. E. Zheng, Appl. Opt., 2018, 57(7), 1640–1644 CrossRef CAS PubMed.
- C. R. Ytsma and M. D. Dyar, Spectrochim. Acta, Part B, 2018, 139, 27–37 CrossRef CAS.
- S. Moncayo, L. Duponchel, N. Mousavipak, G. Panczer, F. Trichard, B. Bousquet, F. Pelascini and V. Motto-Ros, J. Anal. At. Spectrom., 2018, 33(2), 210–220 RSC.
- J. Merten and B. Johnson, Spectrochim. Acta, Part B, 2018, 139, 38–43 CrossRef CAS.
- Z. Y. Li, R. Z. Hu, P. H. Xie, H. Chen, S. Y. Wu, F. Y. Wang, Y. H. Wang, L. Y. Ling, J. G. Liu and W. Q. Liu, Opt. Express, 2018, 26(10), A433–A449 CrossRef CAS PubMed.
- H. L. Yuan, X. Liu, L. Chen, Z. Bao, K. Y. Chen, C. L. Zong, X. C. Li and J. W. Qiu, J. Asian Earth Sci., 2018, 154, 386–396 CrossRef.
- Y. M. Meng and R. Z. Hu, Anal. Lett., 2018, 51(5), 627–647 CrossRef CAS.
- M. Garcon, M. Boyet, R. W. Carlson, M. F. Horan, D. Auclair and T. D. Mock, Chem. Geol., 2018, 476, 493–514 CrossRef CAS.
- S. Wakaki and T. Ishikawa, Int. J. Mass Spectrom., 2018, 424, 40–48 CrossRef CAS.
- M. Willig and A. Stracke, Chem. Geol., 2018, 476, 119–129 CrossRef CAS.
- W. Zhang, Z. C. Hu, Y. S. Liu, T. Wu, X. D. Deng, J. L. Guo and H. Zhao, Chem. Geol., 2018, 479, 10–21 CrossRef CAS.
- W. Chen, J. Lu, S. Y. Jiang, K. D. Zhao and D. F. Duan, Anal. Chem., 2017, 89(24), 13415–13421 CrossRef CAS PubMed.
- H. Y. Geng, R. S. Yin and X. D. Li, J. Anal. At. Spectrom., 2018, 33(11), 1932–1940 RSC.
- L. F. Gou, Z. D. Jin, L. Deng, M. Y. He and C. Y. Liu, Spectrochim. Acta, Part B, 2018, 146, 1–8 CrossRef CAS.
- Q. Guo, H. Z. Wei, S. Y. Jiang, S. Hohl, Y. B. Lin, Y. J. Wang and Y. C. Li, Anal. Chem., 2017, 89(24), 13634–13641 CrossRef CAS PubMed.
- J. Karasinski, E. Bulska, L. Halicz, M. Wojciechowski and A. A. Krata, J. Mass Spectrom., 2018, 53(1), 78–82 CrossRef CAS PubMed.
- M. Li, Y. Lei, L. P. Feng, Z. C. Wang, N. S. Belshaw, Z. C. Hu, Y. S. Liu, L. Zhou, H. H. Chen and X. N. Chai, J. Anal. At. Spectrom., 2018, 33(10), 1707–1719 RSC.
- S. Mondal and R. Chakrabarti, J. Anal. At. Spectrom., 2018, 33(1), 141–150 RSC.
- H. L. Zhu, F. Liu, X. Li, Y. J. An, G. Q. Wang and Z. F. Zhang, J. Anal. At. Spectrom., 2018, 33(4), 547–554 RSC.
- F. Kurzweil, C. Munker, J. Tusch and R. Schoenberg, Chem. Geol., 2018, 476, 407–417 CrossRef CAS.
- Y. H. Liu, K. F. Huang and D. C. Lee, J. Anal. At. Spectrom., 2018, 33(5), 846–855 RSC.
- D. Malinovsky and N. A. Kashulin, Anal. Methods, 2018, 10(1), 131–137 RSC.
- L. Zhang, J. Li, Y. G. Xu and Z. Y. Ren, J. Anal. At. Spectrom., 2018, 33(4), 555–562 RSC.
- X. Y. Zheng, B. L. Beard and C. M. Johnson, J. Anal. At. Spectrom., 2018, 33(1), 68–83 RSC.
- J. M. Zhu, G. L. Wu, X. L. Wang, G. L. Han and L. X. Zhang, J. Anal. At. Spectrom., 2018, 33(5), 809–821 RSC.
- A. M. Bauer and M. S. A. Horstwood, Chem. Geol., 2018, 476, 85–99 CrossRef CAS.
- H. Delavault, B. Dhuime, C. Hawkesworth and H. R. Marschall, J. Anal. At. Spectrom., 2018, 33(2), 195–204 RSC.
- M. Hamada, J. I. Kimura, Q. Chang, T. Hanyu, T. Ushikubo, K. Shimizu, M. Ito, T. Ozawa and H. Iwamori, Geochem. J., 2018, 52(1), 69–74 CrossRef CAS.
- J. M. Thompson, S. Meffre and L. Danyushevsky, J. Anal. At. Spectrom., 2018, 33(2), 221–230 RSC.
- M. Weber, F. Lugli, K. P. Jochum, A. Cipriani and D. Scholz, Geostand. Geoanal. Res., 2018, 42(1), 77–89 CrossRef CAS.
- S. Di Salvo, E. Braschi, M. Casalini, S. Marchionni, T. Adani, M. Ulivi, A. Orlando, S. Tommasini, R. Avanzinelli, P. P. A. Mazza, S. Conticelli and L. Francalanci, J. Anal. Methods Chem., 2018, 2018, 1292954 Search PubMed.
- J. Liu and D. Selby, Geostand. Geoanal. Res., 2018, 42(1), 97–113 CrossRef CAS.
- M. L. Baruzzini, H. L. Hall, K. J. Spencer and F. E. Stanley, Int. J. Mass Spectrom., 2018, 430, 57–62 CrossRef CAS.
- E. D. Hoegg, R. K. Marcus, G. J. Hager, G. L. Hart and D. W. Koppenaal, J. Anal. At. Spectrom., 2018, 33(2), 251–259 RSC.
- A. Kuwahara, Y. Aiba, S. Yamasaki, T. Nankawa and M. Matsui, J. Anal. At. Spectrom., 2018, 33(7), 1150–1153 RSC.
- V. Lebedev, J. H. Bartlett and A. Castro, J. Anal. At. Spectrom., 2018, 33(11), 1862–1866 RSC.
- C. G. Lee, J. Park and S. H. Lim, Nucl. Eng. Technol., 2018, 50(1), 140–144 CrossRef CAS.
- J. H. Park and K. Jeong, Microchem. J., 2018, 137, 334–341 CrossRef CAS.
- A. L. Ronzani, F. Pointurier, M. Rittner, O. Borovinskaya, M. Tanner, A. Hubert, A. C. Humbert, J. Aupiais and N. Dacheux, J. Anal. At. Spectrom., 2018, 33(11), 1892–1902 RSC.
- Y. Y. Ni, J. Zheng, Q. J. Guo, W. Men, K. Tagami and S. Uchida, Anal. Chim. Acta, 2018, 1000, 85–92 CrossRef CAS PubMed.
- W. Wang, Z. M. Li, J. Xu, G. Q. Zhou, Y. Y. Su, Y. M. Wu, G. Y. Wei, S. Fang and W. L. Wang, Chin. J. Anal. Chem., 2017, 45(11), 1719–1726 CAS.
- Y. Fukami, J. I. Kimura and K. Suzuki, J. Anal. At. Spectrom., 2018, 33(7), 1233–1242 RSC.
- M. Willmes, K. M. Ransom, L. S. Lewis, C. T. Denney, J. J. G. Glessner and J. A. Hobbs, PLoS One, 2018, 13(9), e0204519 CrossRef PubMed.
- L. W. Xie, L. Xu, Q. Z. Yin, Y. H. Yang, C. Huang and J. H. Yang, J. Anal. At. Spectrom., 2018, 33(9), 1571–1578 RSC.
- Z. W. Wu, W. Guo, L. L. Jin and S. H. Hu, Microchem. J., 2018, 142, 251–257 CrossRef CAS.
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