Journal of Analytical Atomic Spectrometry最新文献

Spectral imaging generates information-rich datasets comprising a large map of pixels that each contain a comprehensive spectrum. A specific form of mass spectral imaging is laser ablation-inductively coupled plasma-time-of-flight mass spectrometry (LA-ICP-TOFMS). This technique enables elemental imaging of almost the entire periodic table. The large number of isotopes per pixel leads to high-dimensional data posing major challenges for visualisation, pattern recognition and interpretation. To decrease this complexity, dimensionality reduction techniques, such as uniform manifold approximation and projection (UMAP), provide powerful tools to transform high-dimensional datasets into low-dimensional representations aiming to preserve data point relationships and visualise spectral similarities. This study provides a detailed introduction to UMAP for analysing LA-ICP-TOFMS data. By transforming high-dimensional MS imaging data into two-dimensional spaces, UMAP facilitates automated visualisation to identify spectral clusters. UMAP's utility to reveal spectrally distinct regions and tissue heterogeneity is demonstrated for a chicken embryo and a honeybee specimen. For detailed cluster analysis, a hierarchical strategy is introduced involving iterative UMAP applications, first to the global dataset, and then to resulting clusters. This approach helps uncover subtle chemical patterns hidden in the initial global UMAP application. Furthermore, the influence of the most relevant UMAP hyper-parameters is discussed, providing guidance for selecting critical parameters for further datasets. Overall, this study introduces UMAP as an exploratory and versatile tool for targeted and non-targeted analysis of complex LA-ICP-TOFMS data. Its integration into imaging workflows supports spectral clustering, image segmentation, hypothesis generation, and rapid analysis of large and high-dimensional spectral data from biological and environmental specimens.

Determination of trace arsenic in complex matrices is crucial due to its toxicity, yet it remains a significant analytical challenge. Photochemical vapor generation (PVG) has emerged as an efficient alternative to conventional chemical vapor generation (CVG), offering superior sample introduction and matrix separation. Semiconductor nanomaterials and their composites are often used to enhance the efficiency of PVG. In this work, Ni₂P/CdS nanorod (NR) composites were synthesized via a one-step gas–solid phosphorylation process, with Ni₂P serving as a non-noble metal co-catalyst. The composites enabled efficient photochemical reduction of As(III) to arsine (AsH₃) under UV irradiation and its ultrasensitive detection using inductively coupled plasma mass spectrometry (ICP-MS), achieving an impressive limit of detection (LOD) of 3 ng L⁻¹ with a low concentration of formic acid. The method was successfully applied to the determination of trace As(III) in real water samples and certified reference materials. Additionally, the photocatalytic mechanism of the composites was investigated to elucidate their efficient photocatalytic performance. This work provides some new insights into designing advanced composite photocatalysts for PVG-based trace analysis.

The response of a discrete ion counter is not perfectly linear due to count loss caused by dead time and pulse pileup. As a result, the output rate of the counter does not scale linearly with the input rate of ions reaching the detector. The value of a stable input rate can be determined from the measured output rate by inverting the throughput formula of the ion counter. However, when the input rate varies during the measurement, a mismatch between the average input rate and the average output rate becomes apparent. The resulting bias can be particularly significant when measuring transient signals. A correction procedure is proposed to calculate a better estimate of the average input rate from the observed mean and variance of the output rate. Implementation of this refined throughput formula is recommended to improve accuracy of mass spectrometry utilising discrete ion counters.

The instability of the Laser Induced Breakdown Spectroscopy (LIBS) spectral intensity amplitude of C element in low-carbon alloy steel greatly decreases the analysis accuracy. Traditional one model strategies usually suffer from the over-fitting problem, while multi-model strategies heavily depend on the prior knowledge of segmentation. In this paper, an automatic segmented model with nonlinear-regression-based spectral line selection and Mahalanobis distance kernel space classification is proposed to enhance the LIBS quantitative analysis accuracy of C element in low-carbon alloy steel. The nonlinear logarithmic PLSR method is used for analysis line selection. For predicting the concentration of an unknown test sample, the Mahalanobis Distance Kernel Space Classification (MD-KSC) method is utilized to determine which segment model should be applied. Experiments on the alloy steel dataset which consists of 7 standard samples and 30 industrial production samples, with C concentrations less than 0.102%, were carried out. Results show that with the proposed automatic segmented modelling the total Mean Relative Errors (MREs) for predicting C element can reach 2.75%, which is better than those of the traditional methods. The comparative experiments also verified that the nonlinear logarithmic PLSR based analysis line selection method is superior to the Ridge-RFE and the second derivative method.

Combining different but related isotopic systems is key to understanding biological systems as biological functions involving metals in the body generally interact. Potassium, magnesium, and calcium in the ionic form are such elements with related properties. The present work aims to demonstrate a new method to isolate these three metals from a single sample aliquot using AG50W-X12 cation exchange resin, custom-made quartz columns and HCl at different molarities for their subsequent isotopic analysis using MC-ICP-MS. The accuracy of the method was assessed using thirteen certified reference materials with different biological matrices, seven of which have not been analyzed for either their potassium, magnesium, or calcium isotopic compositions before. The procedure allows for an efficient isolation of potassium using AG50W-X12 resin only. However, for matrices characterized by high concentrations of copper, zinc, and/or iron, a prior chromatographic treatment is required, as copper and zinc co-elute with magnesium and iron with calcium, causing matrix effects during the subsequent isotopic analysis. Furthermore, with AG50W-X12 resin, strontium co-elutes with calcium, thus requiring another purification step to separate these elements using a Sr-Spec resin. The efficiency of this method is confirmed by quantitative chromatographic recoveries, low procedural blanks and isotopic compositions corresponding to literature values. This protocol should greatly enhance sample processing with lower volumes of acid, resin, and sample. From a single aliquot, and three consecutive steps, it is possible to isolate seven target elements. Additionally, we provide new values for the isotopic compositions of K, Mg, and Ca for diverse biological certified reference materials enabling improved future method validation of biological applications by using reference materials that show closer resemblance to the investigated samples.

Tag-Laser Induced Breakdown Spectroscopy (Tag-LIBS) is an emerging technique designed to enhance the analytical performance of conventional LIBS using specific tagging strategies. This review of Tag-LIBS presents studies on its applications since its introduction in 2009. We describe the methodology of Tag-LIBS, with focus on the types of tags used, the mechanisms behind tagging, and the approaches used to achieve molecular or elemental specificity. In addition, we review common assay types and techniques for separation and enrichment that enhance both sensitivity and selectivity. Applications of Tag-LIBS in biomedicine, specifically in biomarker detection and bacterial pathogen identification, are highlighted, followed by an analysis of its capabilities compared to other bioassay techniques, considering metrics beyond the conventional Limit of Detection (LOD).

The utilization of rhenium (Re) mass fractions or isotopes (δ¹⁸⁷Re, reported relative to SRM 3143) as a high-sensitivity geochemical tracer has advanced substantially in the past decade, driven by its unique redox-controlled mass-dependent fractionation behavior spanning low- to high-temperature geological processes and systems. Current analytical protocols mainly employ HCl–HNO₃ digestion without desilicification for Re mass fraction analysis and HF–HNO₃ digestion with complete desilicification for δ¹⁸⁷Re_{SRM 3143} analysis, the latter procedure ensuring quantitative Re liberation but concurrently introducing potential interfering elements. In this study, we developed a novel and simple chromatographic separation protocol making use of HCl–HNO₃ and HF–HNO₃ mixtures to obtain pure Re fractions for analysis of silicate-hosted Re contributions to bulk δ¹⁸⁷Re_{SRM 3143} signatures. The Re isotope ratio of the purified fraction was determined by multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS) employing a calibration model combining sample-standard bracketing with internal normalization (C-SSBIN). The robustness and reliability of the newly developed separation procedure was validated through analysis of certified reference materials digested by HF–HNO₃, including BCR-2, TDB-1 and OKUM, showing good agreement with literature data. Comparative analysis of non-desilicified reference materials (WPR-1a, OKUM, TDB-1, BHVO-2, AGV-2) revealed δ¹⁸⁷Re_{SRM 3143} discrepancies ≤ 0.07‰ (intermediate precision) despite the presence of >10% silicate-bound Re, demonstrating that HF-desilicification is not a necessary operation for Re isotope analysis. This finding suggests that sample mass can be increased to obtain sufficient Re for high-precision isotope measurement. Our separation procedure can be applied to various types of samples regardless of their Re mass fractions. Additionally, the δ¹⁸⁷Re_{SRM 3143} of the sulfur-rich peridotite WPR-1a (first reported here) shows relatively lower values compared to other silicate reference materials, implying that redox processes can induce Re isotope fractionation.

Accurate quantification of volatile elements (F and Cl) in mafic silicate glasses is critical for understanding magmatic processes; however, it remains analytically challenging due to spectral interference (e.g., Fe Lα on F Kα) and matrix effects during overlap correction. We develop a refined electron probe microanalysis (EPMA) protocol based on an established single-standard overlapping-peak-correction procedure. This method is applicable across a range of beam currents (60–300 nA), eliminating the need for a multi-standard calibration curve, which typically requires the same beam current as the F measurement in unknown samples. Systematic evaluation using F-free glass standards (G5, G6, and G7) with varying Fe contents demonstrates that calibrated F concentrations in BHVO-2G remain consistent within uncertainty across different beam currents and standards, agreeing with previous studies. Matrix effects from different overlap standards cannot be completely eliminated by the single-standard correction procedure. Consequently, F concentrations determined using different overlap standards clustered into five distinct ranges corresponding to standard types: (1) silicate glasses, (2) garnet, (3) olivine, pyroxene, and spinel, (4) iron oxides and chalcopyrite, and (5) pyrite and pure iron metal. Calibrated values show insignificant variation with the iron valence state in overlap standards. Matrix effects are the dominant factor in the calibration of Fe Lα–F Kα spectral interference. Under optimized analytical conditions (15 kV, 300 nA, 15 μm, and PC0 crystal), detection limits are 46 ppm for F and 12 ppm for Cl. The method's accuracy was validated by comparing the test results of international glass standards with literature data.

Owing to their wide applicability and relative ease of use, 193 nm ArF excimer lasers are commonly-used laser sources for laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS). However, some materials, like quartz, sulphates, potassium salts, fused silica or water ice, often show poor ablation characteristics at 193 nm due to low absorption at deep-UV (DUV) wavelengths. Only very few LA-ICP-MS systems have utilized 157 nm F₂ excimer lasers, likely due to their low laser energy output in combination with the challenges that the transmission of vacuum-UV (VUV) radiation poses. Nevertheless, by using a 157 nm laser, some of the shortcomings of 193 nm LA can be overcome, because many of the “difficult to ablate” materials are opaque at 157 nm and the ∼20% higher photon energies at 157 nm. Here we describe a custom-built dual-wavelength (157 nm & 193 nm) cryo-LA-ICP-MS/MS system, built around the RESOlution-SE LA system with an S155 two-volume ablation cell, to which a separate 157 nm beam path was added. The system utilizes two distinct laser sources and beam paths for the two wavelengths, each optimized for the specific requirements and use-cases, and facilitates switching between the wavelengths within less than half a day. Furthermore, the system can be equipped with a newly-designed large cryo-sample holder for the S155 LA cell to analyze natural ice samples. Alongside the characterization of the 157 nm beam path, yielding on-sample fluences of up to 8 J cm⁻², we present comparative results of ablation characteristics for a range of materials at the two wavelengths, including threshold fluences of ablation and effective absorption depths. Our results show that ablation at 157 nm happens at low fluences (0.3–0.5 J cm⁻²) comparable with 193 nm for soda-lime glasses and calcites. For materials like calcium sulphates, quartz and fused-silica glasses, we demonstrate controlled, photochemical ablation at low fluences (0.3–1.1 J cm⁻²). To illustrate the applicability of 157 nm laser ablation for ICP-MS measurements, a trace element map of a quartz sample with variable composition is shown. Additionally, initial, qualitative results of the ablation of water ice are shown for both 193 nm and 157 nm, which demonstrate controlled ablation behaviour even in low impurity ice at 157 nm. Overall, our results indicate that LA-ICP-MS at 157 nm is a viable analytical method for sample matrices that are near-transparent at 193 nm and thus often difficult to ablate.

Plastic pollution in marine environments poses ecological risks, in part because plastic debris can release hazardous substances, such as metal-based additives. While microplastics have received considerable attention as vectors of contaminants, less is known about larger macroplastics and their role in the spatial and temporal redistribution of substances. In this study, pristine, store-bought plastic items and macroplastics recovered from the North Pacific Subtropical Gyre (NPSG) were analysed using Fourier-Transform Infrared Spectroscopy (FTIR) to identify polymer types, and bulk acid digestion followed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for total metal quantification. These techniques were complemented by high resolution elemental mapping by Laser Ablation Inductively Coupled Plasma Time-of-Flight Mass Spectrometry (LA-ICP-TOFMS). Detailed elemental maps revealed native metal distribution in pristine plastics, and evidence of both sorption and intrinsic metal depletion in weathered plastics. In particular, weathered plastics showed surface depletion of intrinsic metals, and enrichment of seawater-derived elements (e.g., Na, Mg, I). Linear regressions were used to quantify spatial distribution trends across cross sections, providing statistical support for directional gradients. Since pristine and weathered plastics were opportunistically collected, variability in product type, polymer chemistry, and weathering time limited direct comparisons. Instead, this study demonstrates the utility of LA-ICP-TOFMS for mapping elemental distribution in plastics, offering a novel analytical approach for investigating spatial metal distribution in plastics and laying the groundwork for future studies on weathering processes in marine environments.