Journal of Analytical Atomic Spectrometry最新文献

As one of the main energy sources in human production and life, the accurate and rapid classification of coal is of great significance to industrial production and the control of pollution emissions. However, the complex composition and highly similar elemental composition of coal with different physical properties and chemical composition lead to a high degree of similarity in coal spectral data measured by laser-induced breakdown spectroscopy (LIBS), which poses a great challenge to accurate classification and identification work. In this paper, based on LIBS technology, we integrate the chi-square test (CST) and principal component analysis (PCA) to construct a quadratic dimensionality reduction network (CST-PCA), and for the first time, we propose a new improved sparrow search algorithm (ISSA) by introducing spatial pyramid matching (SPM) chaotic mapping, adaptive inertia weights (w) and Gaussian mutation, and combine it with kernel based extreme learning machine (KELM) to construct an ISSA-KELM data classification model to classify and identify seven types of coal samples. Firstly, 2520 12248-dimensional coal spectral data were preprocessed using a combination of the chi-square test (CST) and principal component analysis (PCA). The KELM was hyper-parameter optimised using ISSA. By comparing with the unoptimized model, the accuracy of coal classification reaches 99.773%. The experimental results show that the CST-PCA-based ISSA-KELM algorithm effectively optimizes the parameters, improves the classification accuracy of coal, and provides a new data processing scheme for accurate qualitative analysis of coal.

The significance of Si determination has increased with the rise of production of silanes, siloxanes and silicones. The determination of Si plays an important role to determine the presence of such compounds in solution and provide quantitative data. For most methods, lower limits of detection of Si so far have been in the mg L⁻¹ to μg L⁻¹ range. However, to comply with the maximum levels for Si absorption through food and dietary supplements, trace determination of Si in the very low μg L⁻¹ to high ng L⁻¹ range is required. In this study, a method for determining ultra-trace amounts of Si in food simulants, ethanol, and acetic acid, was developed using GF-AAS. The method was validated according to the guidelines set by the FDA, and the results showed Si quantification limits of 0.2 μg L⁻¹ and 0.4 μg L⁻¹ for ethanol and acetic acid, respectively.

The expansion dynamics of target particles are crucial for rapid isotope analysis using resonance ionization mass spectrometry (RIMS) combined with laser ablation as an atomization source. The spatial and temporal spectral signatures in laser-produced plasma (LPP) provide insights for applying RIMS to understand the expansion behavior of target particles. In this study, diode laser absorption spectroscopy was employed to observe U atoms in UO₂ LPP in a high-vacuum environment (3.0 × 10⁻⁴ Pa). Results showed the remarkable differences in the expansion dynamics of U atoms compared to Al atoms. Specifically, the UO₂ ablation plume had a double layer due to charged particles, and the spectra of the U atoms do not exhibit clear spectral splitting. Moreover, the U atoms in the ⁵L₆ ground state and low-lying ⁵K₅ meta-stable state (notably, >99% of U atoms generally exist in both energy states) are probed to examine their distributions between the two energy states. The results reveal that approximately 28–38% of the U atoms are distributed in the ⁵K₅ meta-stable state because of thermal excitation. These quantitative insights provide a clear pathway toward advancing the applications of laser ablation.

Concentrations of Ir in natural samples can provide useful information for tracing a variety of geological and planetary processes; however, efficient, sensitive, and precise analysis of Ir contents remains challenging, especially for crustal samples that are highly depleted in Ir (i.e., at the pg g⁻¹ level). Here we report an analytical method for determining ultralow Ir contents (pg g⁻¹ level) in small geological samples (<1 g) by the isotope dilution method (ID) using a multiple ion counting inductively coupled plasma mass spectrometer. An ¹⁹¹Ir-enriched spike was mixed with the sample during sample digestion, followed by the separation and purification of Ir from the rock matrix using AG MP-1 anion exchange resin. Ir isotope ratios were analyzed on a Nu 1700 Sapphire MC-ICP-MS using the multiple ion counting. Our tests indicated that the use of collision cell mass spectrometry with helium and hydrogen as the collision/reaction gases did not offer benefits in removing isobaric interferences for Ir isotope analysis. However, through the combination of chemical purification with conventional wet-plasma mass spectrometry, we attained sufficient accuracy for Ir analysis at ultralow levels. The total procedural blank and detection limit for this method were determined to be 7.6 ± 3.5 pg (2σ, N = 10) and 0.35 pg g⁻¹, respectively. To validate the accuracy of this analytical method, a K-Pg boundary reference sample (DINO-1) and six USGS reference materials were analyzed, and the obtained results were consistent with previous studies. Furthermore, we report Ir contents in other 11 international geological reference materials with low Ir abundance, demonstrating the applicability of this method in studying ultralow Ir content samples associated with magmatic processes, supergene processes and impact events.

The oxygen isotopic microanalysis of calcite is essential for obtaining high spatial resolution data linked to microstructures, a challenge for conventional techniques. This analysis, however, relies heavily on matrix-matched reference materials, of which only a few calcite standards are available. In this study, an inorganically precipitated calcite vein sample (WS-1) was evaluated through 225 SIMS oxygen isotope analyses and was found to have a homogeneous isotopic composition, with an external reproducibility ≤0.21‰ (1σ), suggesting its potential as a SIMS reference material. The precise δ¹⁸O_VPDB value, determined via traditional gas-source IRMS, was −16.52 ± 0.13‰ (1SD). Matrix effects were assessed using various carbonates, including abiotic aragonite (VS001/1-A), three abiotic calcites (NBS18, Cal-1, WS-1), and a high-Mg calcite (gorgonian coral). The results revealed negligible matrix effects between abiotic aragonite and calcites but significant differences between calcites and high-Mg calcite, likely due to Mg content or differences in biogenic crystal morphology and trace organic composition. This study demonstrates the utility of in situ oxygen isotopic microanalysis for calcite but emphasizes the need for caution when analyzing high-Mg calcitic skeletons.

A fundamental study of four different sample introduction systems was carried out to evaluate the upper size limit of microplastics measured by inductively coupled plasma-time-of-flight-mass spectrometry (ICP-TOFMS). Three different, certified microplastic samples (PS, PMMA and PVC) within a size range of 3–20 µm in suspension were measured. In this study, no particles larger than 10 µm could be detected using pneumatic nebulization for sample introduction. However, we were able to extend the upper size limit to 20 µm by either using a falling-tube device or a vertical downwards-pointing ICP-TOFMS. Particle transport efficiencies could only be estimated and were within a range of 13% to 184%. The particle size was quantified by using dissolved citric acid (non-matrix matched) and agreed with reference values. The critical size values were 2.3 µm for PS, 2.4 µm for PMMA and 3.0 µm for PVC. Additionally, in the case of PVC, chlorine could also be detected and the critical size value was 3.9 µm based on the ³⁵Cl⁺ ion signal.

The focused position of the lens relative to the sample surface affects the density, temperature, and dynamic characteristics of laser-induced plasma, which are important for improving the spectral intensity, minimizing self-absorption, and improving stability of laser-induced breakdown spectroscopy (LIBS). The emission intensities of the Al atomic line and the AlO B²Σ⁺–X²Σ⁺(0,0) band, using nanosecond pulse laser ablation of an aluminum target in air, at three different focused point-to-sample distances were investigated. The Al atomic line was optimal when the focus was 1 cm above the sample surface, which is attributed to the low density and high temperature of the plasma. Conversely, the AlO B²Σ⁺–X²Σ⁺(0,0) band emission spectrum is superior when the focused point is 1 cm below the Al surface, with the spectral intensity enhancing as the number of laser shots increases. A time-resolved pump–probe shadowgraph technique was employed to record dynamic snapshots of the ablation plume at different focused point-to-sample distances to account for the enhancement mechanism of the spectral intensity. The intensity variations in the atomic and molecular spectra are related to the shock wave propagation velocity in the longitudinal and radial directions, providing insights into the enhancement mechanism of the spectral signals. Moreover, the morphology of craters was analyzed by using a scanning electron microscope and a profilometer, revealing that the depth-to-diameter ratio and ablation amount correlated with different spectral intensity variations at focused point-to-sample distances of −1 and 0 cm. These results will assist in choosing optimal strategies for quantifying elements using LIBS atomic or molecular spectrometry.

Single-cell inductively coupled plasma mass spectrometry (scICP-MS) is an emerging technique for the determination of elemental contents in individual cells. No standardized system for the introduction of cultured mammalian cells has been established owing to difficulties in cell transport and detection. The transport efficiency of human chronic myelogenous leukemia K562 cells (hereinafter “K562 cells”) in a conventional sample introduction system comprising a pneumatic nebulizer and a total consumption spray chamber is low owing to cell damage. To improve cell transport efficiency, we installed a piezo-actuator-driven microdroplet generator (μDG) into the sample introduction system of an ICP-MS for fast time-resolved analysis. Cell transport efficiency was drastically improved by using a μDG. For the determination of elemental contents, calibration curves were created by analyzing microdroplets of ionic standard solutions generated by the μDG. The pulsed signals originating from the microdroplets were analyzed and the sensitivity (i.e., signal intensity per elemental mass) was calculated for each element. The quantification protocol was validated using silver nanoparticles, titanium dioxide nanoparticles, and dried yeast cells. Finally, we introduced intact K562 cells and detected signals with high throughput. The average masses of five essential elements in single K562 cells were precisely determined as follows: 270 ± 100 fg for Mg, 23.0 ± 2.0 fg for Zn, 7684 ± 675 fg for P, 2136 ± 165 fg for S, and 14.4 ± 1.2 fg for Fe. These values are consistent with the values obtained by solution nebulization ICP-MS analysis after the acid digestion of K562 cells.

The measurement of vacuum degree and electrification in vacuum switches has been a critical issue constraining the development of vacuum switches for over half a century, remaining unresolved. In recent years, our team has proposed the use of laser-induced breakdown spectroscopy (LIBS) for the non-contact measurement of vacuum switch pressure. However, its application is hindered by relatively high detection limits, low sensitivity, and susceptibility to background noise interference, which result in suboptimal precision. Extensive research has indicated that metal nanoparticles can effectively enhance signal detection capabilities, however, their enhancement effects under low-pressure conditions remain unclear. This study aimed to investigate the enhancement effects of silver nanoparticles (AgNPs) on signals under low-pressure conditions. By analyzing spectral data, plasma images, and radiation integral intensity, we seek to improve the accuracy of vacuum level measurements in vacuum switches. Results showed that in low-pressure environments, AgNPs enhanced spectral signals by up to 7.17-fold, increasing vacuum detection accuracy from 95.7% to 98.05% and extending the detection range by an order of magnitude to 10⁻³ Pa. This enhancement was regulated by particle size and concentration, with 10 nm AgNPs exhibiting better enhancement effects than 5 nm particles. The optimal concentration varied with both particle size and pressure. Nanoparticle-enhanced LIBS (NELIBS) increased the drop in plasma radiation integral intensity, prolonging the pre-expansion state of the plasma when excited and improving the accuracy of vacuum level measurements. This explores the potential of applying nanomaterials to conduct electrical detection in vacuum conditions and lays a theoretical and experimental foundation for optimizing spectroscopic analysis technologies.

NdFeB magnetic materials are widely used in daily life, such as in permanent magnet motors, loudspeakers and computer disks. The NdFeB magnetic material has excellent magnetic properties, and its magnetic properties are also the key to judge the production quality of NdFeB. Therefore, the precise quantification of the magnetic properties of NdFeB magnetic materials is crucial. Laser induced breakdown spectroscopy (LIBS) is a technique to obtain the spectrum of chemical elements by excitation of plasma on the surface of a sample with a high energy laser. In this paper, a precise classification and magnetic quantification method for NdFeB magnetic materials based on laser-induced breakdown spectroscopy is designed, which is different from the traditional direct magnetic property detection method and uses element detection to quantitatively analyze the magnetic properties indirectly. A laser-induced breakdown spectroscopy system was used to collect the characteristic spectrum of NdFeB magnetic materials, and the sliding window minimum removal base method was independently designed to further optimize the detection accuracy. A classification model and quantitative analysis method model were further established and optimized. The random forest method was used to preliminarily classify NdFeB magnetic materials, and the GA-ELM method was used to conduct quantitative analysis of magnetic properties. Quantitative magnetic properties include Br, Hcj, Hcb and (BH)max. The error analysis of the final quantitative analysis is as follows: RMSE of Br reaches 0.0001526, RMSE of Hcj reaches 0.0001937, RMSE of Hcb reaches 0.00197, and RMSE of (BH)max reaches 0.00785. It is verified that the magnetic quantification method for NdFeB magnetic materials based on laser-induced breakdown spectroscopy can effectively conduct accurate quantitative analysis of the magnetic properties of NdFeB magnetic materials and provide a fast, convenient, accurate and economical detection method for the quality control of magnetic materials workshops.