Journal of Analytical Atomic Spectrometry最新文献

This study evaluated the micro-homogeneity of seven different commercially available nanoparticulate pressed pellets based on a CaCO₃ matrix and their utility for quantitative elemental mapping of biogenic carbonates using laser ablation-inductively coupled plasma-time-of-flight-mass spectrometry (LA-ICP-TOF-MS). The analytical performance of matrix-matched calibration (using the aforementioned nano-pellets) was compared against that of non-matrix-matched calibration using a silicate glass (NIST SRM 610) reference material for quantification. Calibration with nano-pellets, combined with the use of Ca as an internal standard, significantly improved the quantification accuracy, providing recoveries between 80–120% for the majority of the 18 elements selected and spread across a wide concentration range (from sub-μg g⁻¹ to tens of wt%). However, some nano-pellets (e.g., BPLM-NP and BAM-RS3-NP) exhibited higher heterogeneity, leading to biased recoveries. Also, an inverse correlation between the mass fraction and the relative standard deviation (RSD) was observed. Throughout the work, elemental mapping was conducted with a laser beam size of 20 × 20 μm² as a compromise between spatial resolution, sensitivity (sub-μg g⁻¹ limits of detection required for trace elements), linear dynamic range, total analysis time and size of the region-of-interest. The quantitative mapping approach enabled the generation of high-resolution, multi-elemental 2D-maps of various CaCO₃-based natural chronological archives, including fish otoliths and bivalve shells, revealing detailed elemental distribution patterns for both trace (e.g., Mn, Ba) and major elements (e.g., Sr). This LA-ICP-TOF-MS methodology provides a powerful tool for resolving intricate microstructures and thus, for chronologically tracking bioaccumulation of environmentally relevant metals, offering significant advantages over traditional 1D (line scanning) analysis as the latter may lead to misinterpretation of elemental distributions.

Ice cores serve as unique paleo-archives allowing access to long-term records of trace elements, which are important for our understanding of global biogeochemical cycles and air pollution. However, analysis of trace elements in ice cores is a challenge, because of very low concentration levels and their presence in dissolved and particulate form. The commonly used and well-established technique for analysis of trace elements in ice cores is inductively coupled plasma sector field mass spectrometry (ICP-SF-MS). Recently, inductively coupled plasma time of flight mass spectrometry (ICP-TOF-MS) was introduced as a new, promising technique. Due to its fast acquisition time for the near-full mass spectral range, it allows for the detection of short transient signals, offering the opportunity to determine the elemental composition of single particles. In this study, the performance of this new technique for analyzing total trace element concentrations was tested and compared to the one established in the field of ice core research. The focus was on sensitivity, precision, and optimization of sample preparation in sections from two ice cores (Colle Gnifetti, Cerro Negro), characterized by different impurity levels. The performance of the ICP-TOF-MS was excellent for the investigated trace elements within the nominal mass range from 23 to 238, except for ⁴⁵Sc because of insufficiently resolved mass interferences. This is very promising for many applications in ice core research, especially in view of the great benefit to analyze single particles simultaneously in the same sample.

Soil elemental analysis is vital for assessing nutrient availability and contamination. For soil analysis, conventional calibration-free LIBS (CF-LIBS) methods suffer from unavoidable uncertainty of the Einstein coefficients and optical coefficients. Although one-point calibration LIBS (OPC-LIBS) can tackle these problems to some degree, it is still limited by the self-absorption effect and strict requirement of accuracy of all-elemental content. In this work, a modified OPC-LIBS method was proposed, which combines an internal reference element strategy with self-absorption correction and columnar-density Saha–Boltzmann (CD-SB) plotting. Only one major element, silicon, needed to be certified in the reference soil sample. All other elements across diverse soils were deduced. Moreover, self-absorption and plasma parameters (temperature and electron density) were corrected via CD-SB plots, providing a more reliable basis for elemental determination. The results demonstrated that mean relative errors (MRE) were reduced to 16.324–42.358% in the proposed method, much lower than in conventional CF-LIBS and in CF-LIBS with self-absorption correction. The analytical accuracy also matched or outperformed conventional OPC-LIBS (requiring certification of all elements in the reference sample). This work provided a more convenient and accurate method for multi-element soil analysis.

Accurately quantifying rhenium (Re) and osmium (Os) at ultra-trace concentrations in geological matrices, such as soils and rocks, is essential for progress in Earth sciences. The isotopic compositions of these elements serve as critical geochronometers and geochemical tracers, providing valuable insights into mantle evolution, crustal recycling, and ore deposit formation. However, their extremely low natural abundances, often ranging from picograms per gram (pg g⁻¹) to nanograms per gram (ng g⁻¹), present significant analytical challenges that require methods with exceptionally low detection limits.This review presents a detailed comparative analysis of leading analytical approaches for Re and Os determination in geological samples, emphasizing their lower limit of detection (LLD) performance. Mass spectrometry-based techniques, particularly Negative Thermal Ionization Mass Spectrometry (N-TIMS) and Multi-Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS), are identified as the most effective methods for achieving ultra-low detection limits. N-TIMS has historically demonstrated superior performance in reaching the lowest absolute LLDs for osmium, frequently attaining picogram-level sensitivity due to its high ionization efficiency and advanced detector technologies. For rhenium, MC-ICP-MS, especially when integrated with advanced chromatographic separation protocols, achieves LLDs in the sub-pg g⁻¹ range. Attaining this level of sensitivity depends not only on instrumental capabilities but also on comprehensive analytical strategies, including meticulous sample preparation, stringent control of procedural blanks, and sophisticated measures for reducing spectral and matrix interferences.To ensure methodological reliability and precision, this review also examines the use of certified reference materials in geological sample analysis. Ongoing advancements in these analytical methodologies remain vital for furthering geochemical research and enhancing our understanding of Earth's intricate history.

The increasing demand for new energy sources, such as lithium batteries, has driven exploration of lithium sources like brines and pegmatites, with spodumene being the only mineral with an economically viable extraction route. In 2020, the European Commission listed lithium as a critical raw material. To ensure the quality of spodumene, rapid and accurate analytical methods are essential. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for direct, rapid multi-element analysis, but it usually suffers from intense matrix effects. This study proposes a partial matrix matching multi-energy calibration approach (PMM-MEC) for the determination of Al, Fe, Li and Si in spodumene samples from different locations in Minas Gerais, Brazil, using LIBS. A mixture of spodumene samples, previously characterized by XRF and ICP OES, was used as the standard. The PMM-MEC method was validated by determining Al, Fe, and Ti in bauxite (CRM BXMG-2); Ca, Si and Mn in manganese ore (CRM NCS47009); and Al, Ca and Si in portland cement (CRM 1889a). Sodium and boron, or lithium and boron, were used as internal standards to mitigate matrix effects and improve the method's accuracy. The method provided relative errors between −12% and 10% and relative standard deviations (RSD) ranging from 0.2% to 2.5%. The limits of detection for all analytes were in the 0.0003–0.7% range.

Kα _1,2, Lα_1,2, and Lβ₁ X-ray spectra linewidths have been measured in elements Nb, Mo, and Rh, using a high-resolution double-crystal X-ray spectrometer. From the obtained experimental values, Γ_K, Γ_L2, and Γ_L3 level widths were estimated and compared with the recommended and semi-empirical ones, and our theoretical results. The overall tendency of the corrected full width at half maximum of the Kα₁ and Kα₂ lines as a function of Z agrees with the data in the literature.

Laser-induced breakdown spectroscopy (LIBS) is a swift and potent analytical method utilized for element detection, owing to its distinct advantages in online/in situ detection. However, the analysis of LIBS spectra encounters a significant challenge during the acquisition phase due to measurement uncertainty caused by matrix effects and self-absorption. To improve the performance of LIBS analysis, LIBS combined with a deep learning method based on a back propagation (BP) neural network optimized by the improved sparrow search algorithm (ISSA) was proposed here for the recognition of seven different types of tea. In order to realize rapid green identification of tea, a total of 1050 spectral datasets from seven tea samples were obtained by laser-induced breakdown spectroscopy. The spectral datasets were preprocessed to eliminate noise and background interference, and eight principal components were extracted by principal component analysis (PCA). In order to solve the issues of slow convergence of the traditional BP neural network model and its tendency to fall into the local optimal value, a hybrid strategy incorporating a tent chaotic map, adaptive T-distribution variation, number of producers and dynamic adjustment of search space were introduced to improve the SSA, and then the BP neural network hyperparameters were optimized with the ISSA. Subsequently, the hyperparameters of the BP neural network were optimized using the ISSA. Finally, the model is compared with K-Nearest Neighbors (KNN), BP, SSA-BP and other models. The results show that the ISSA-BP model has the best performance, and the recognition accuracy is superior to other models, with a classification accuracy reaching 99.1%. In conclusion, LIBS combined with the ISSA-BP neural network model can quickly and accurately recognize tea types.

In various technological fields, different nanomaterials are being used to push toward ever smaller and more complex structures. Different X-ray based methods can be extremely helpful to develop, analyze and improve such materials. Combining element sensitivity with lateral in-depth resolution, grazing incidence X-ray fluorescence (GIXRF) is a perfect candidate for this task. GIXRF represents an extension of standard X-ray fluorescence analysis (XRF) and total reflection XRF, and its utility has been demonstrated in a number of synchrotron studies over the years. Especially with improvements in X-ray sources and X-ray optics, GIXRF has become accessible to laboratory setups as well. Based on the principle of reciprocity, grazing emission – or gazing exit X-ray fluorescence (GEXRF) was postulated and proven to work in a similar way as GIXRF, with different advantages and disadvantages due to the inverse geometry. However, with their comparably more complex analysis procedures GIXRF and GEXRF methodologies are not yet widespread in research and industry. Thus, this review aims to give a comprehensive overview on the physical principle, technical requirements and recent applications in research and industry of these versatile nanoscale characterization methods.

Single particle microwave plasma optical emission spectrometry (SP MWP OES) was applied for the characterization of selenium nanopowder synthesized via a microwave-assisted green protocol using citrus juice as a reducing and stabilizing agent. The technique enabled real-time, single-particle detection of elemental signals, allowing assessment of particle size distribution and surface composition. The influence of particle size on signal intensity was determined using in-house synthesized quasi-spherical SeNP standards of known sizes. Time-correlated selenium and carbon signals confirmed the presence of surface-bound carbon-containing biomolecules, while co-detection of cadmium indicated potential interactions between SeNPs and cadmium species. These findings highlight the utility of SP MWP OES for probing nanoparticle surface functionalization and compositional variability. Although current calibration focused on spherical SeNPs, further development will address more complex systems. Overall, SP MWP OES proves to be a sensitive and informative tool for the characterization of SeNPs in biologically and environmentally relevant contexts.

Spot U–Pb isotopic dating of columbite–tantalite minerals provides a useful way to directly constrain the timing of Nb–Ta mineralization and fingerprint the provenance of columbite–tantalite ore concentrates. However, application of accurate columbite–tantalite U–Pb isotopic dating using microbeam techniques, such as laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) or secondary ion mass spectrometry, relies largely on the availability of well-characterized matrix-matched reference materials. Although some columbite–tantalite reference materials have been developed for microanalysis, columbite–tantalite minerals are typically highly variable in chemical composition, which may strongly affect the accuracy and quality of spot U–Pb dating. Here, a columbite megacryst LCT02 is investigated using a combined LA-ICPMS and isotope dilution-thermal ionization mass spectrometry (ID-TIMS) approach to assess its suitability as a reference material for spot U–Pb dating. The LA-ICPMS U–Pb measurements of LCT02 in two laboratories yield reproducible U–Pb dates, which are in good agreement with the ID-TIMS date within analytical uncertainties, indicating that LCT02 has the potential to become a new reference material for spot columbite U–Pb isotopic microanalysis. The weighted mean ID-TIMS ²⁰⁷Pb/²⁰⁶Pb date of 908.6 ± 1.4 Ma (2σ) is recommended as the best estimated crystallization age for LCT02.