Journal of Analytical Atomic Spectrometry最新文献

Elemental imaging (EI) techniques, such as laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS), produce spatially resolved elemental data comprising multiple elemental channels and associated spatial coordinates for each pixel. Although EI originated in geochemistry, it is increasingly applied in the life sciences, where between-specimen comparison of individual elements is central to experimental interpretation. However, most existing EI visualization software tools are designed for single specimen datasets, and comparative analysis between specimens is time-intensive and inefficient. In addition, large LA-ICP-TOF-MS datasets, often several gigabytes in size, hinder multi-specimen comparison, and slow data loading and sharing. Here, we describe a new framework for the visualization and comparison of EI data across multiple specimens, implemented using open-source Python tools tailored to biological EI workflows. ScaleBarOn enables scaled, multi-specimen visualization and image generation for individual elements, while Muad'Data supports single-specimen exploration, including multi-element overlays. To reduce computational burden and improve interoperability, multi-channel EI datasets are decomposed into single-element matrix files stored in lightweight, widely supported formats. This enables consistent scaling and efficient comparison of elemental distributions across large biological datasets, supporting reproducible and interpretable analysis.

Laser-induced breakdown spectroscopy (LIBS) is a rapid and minimally destructive technique which enables measurement of almost every element of the periodic table. However, fluorine determination remains challenging due to low sensitivity and weak emission signals. In this work, the influence of reduced ablation atmosphere pressure on fluorine detection by LIBS is systematically investigated, including parameter optimization steps for gate delay and laser energy. A significant increase in fluorine signal intensity was observed with decreasing pressure. The impact of pressure on signal stability, calibration behaviour, and limits of detection was assessed and compared to measurements at atmospheric pressure. In that regard, different evaluation approaches, including univariate and multivariate models (using Partial Least Squares) were considered. The results demonstrate that reduced-pressure conditions lead to improved sensitivity and lower limits of detection, enabling more reliable fluorine quantification. For the univariate calibration models, sensitivity was approx. double at 50 mbar compared to atmospheric pressure, while the limit of detection reduced from 505 to 104 µg g⁻¹. Further, sensitivity in the multivariate models improved by up to 80% leading to a decreased limit of detection of 121 µg g⁻¹ at 50 mbar in comparison to 286 µg g⁻¹ at atmospheric pressure. The findings presented here show that controlling the ambient pressure is an effective strategy to enhance fluorine detection by LIBS without requiring extensive sample preparation or major instrumental modifications. This approach broadens the applicability of LIBS for the direct analysis of fluorine in solid samples and provides a practical route to improved analytical performance.

Nitrous oxide, a linear asymmetric molecule, comprises site-specific isotopologues ¹⁴N¹⁵N¹⁶O and ¹⁵N¹⁴N¹⁶O, which provide insight into nitrous oxide production pathways. We explored the ν₁ symmetric stretching mode of nitrous oxide and identified a unique interference-free spectroscopic window spanning 0.065 cm⁻¹, in which ¹⁴N¹⁵N¹⁶O and ¹⁵N¹⁴N¹⁶O can be probed simultaneously with a single laser scan. Here, we employed an external-cavity quantum cascade laser (EC-QCL) emitting at 7.8 µm, coupled with cavity ring-down spectroscopy, to probe high-resolution ro-vibrational transitions of the ¹⁴N¹⁵N¹⁶O and ¹⁵N¹⁴N¹⁶O isotopologues. We prepared various concentrations of a sample mixture of ¹⁴N¹⁵N¹⁶O and ¹⁵N¹⁴N¹⁶O by mixing zero-air and then introduced it into the cavity at an optimized pressure of 8.1 torr. We systematically investigated the spectrometer response for various concentrations of the isotopologues probed within the spectroscopic window with a measurement rate of ∼1 Hz. We then performed a stability analysis, which exhibited a detection limit of 0.44 ppb for ¹⁴N¹⁵N¹⁶O with a 103 s integration time. In contrast, for ¹⁵N¹⁴N¹⁶O, the minimum detection limit was 0.37 ppb at a 102 s integration time, indicating highly sensitive detection of trace isotopologue levels. This work provides a unique spectroscopic window that could find applications in the investigation and characterisation of various biogeochemical pathways for atmospheric nitrous oxide.

The rapid, high-precision determination of actinide isotopic compositions is critical for nuclear forensics, safeguard verification, and environmental assessment, yet these applications are often limited by multi-day chemical preparations and dependence on specialized labware. In this work, we develop a micro-scale dissolution and extraction chromatography workflow that reduces sample preparation times for U, Pu, Np, and Am to a few hours while maintaining isotopic accuracy suitable for high-precision MC-ICP-MS/MS analysis. Small-mass aliquots of geologic and reference materials (0.2–3 mg) and pre-digested SRM solutions are purified using 0.1 mL UTEVA microcolumns, with AG1-X4 and stacked UTEVA-DGA microcolumns used in separate experiments. Custom 3D-printed microcolumns and holders mounted on a repurposed liquid-handling platform deliver reagents under positive pressure, enabling rapid, automated microchemistry without a dedicated commercial extraction-chromatography system. Across a suite of NIST SRMs and glass standards, automated micro-UTEVA separations yielded U recoveries of 4–111% and Pu recoveries of 47–110%, which, although spanning a broader range, were generally lower than those obtained from manual gravity driven microcolumns (30–79% and 82–96%, respectively). Regardless, U and Pu isotope ratios from the automated separation remained within approximately 1% of certified values. Neptunium and Am recoveries were lower (typically 16–41%), highlighting areas for further optimization of the multi-actinide protocol. End-to-end workflows combining microdissolution in custom-machined well plates, 3D-printed microcolumns, and MC-ICP-MS/MS analysis were completed in under 4 hours, showing that laboratory-adaptable, platform-agnostic microchemistry on repurposed liquid-handling hardware (Hamilton MicroLab) can deliver high-quality actinide isotope ratios for time-critical nuclear forensics and safeguards.

Lithium (Li), as a key mineralizing element, is not only of substantial strategic importance but also acts as a powerful tracer for a wide range of geological processes, owing to the large relative mass difference between its two stable isotopes, ⁶Li and ⁷Li. Conventional Li separation methods either use organic solvents that entail health hazards and degrade ion-exchange resins, or rely on AG 50W-X8 or X12 resins in single- or dual-column configurations, which are limited by poor universality, high acid consumption, and laborious procedures. To overcome these drawbacks, this study presents a rapid chemical separation protocol for lithium applicable to a variety of rock matrices. The entire procedure uses 0.2 mol L⁻¹ hydrochloric acid as the eluent under a single elution scheme with 3.0 mL of AGMP-50 resin, enabling simplified operation while effectively suppressing Na breakthrough. The purified Li fractions exhibit high purity (>99.8%) and low procedural blank levels, allowing high-precision isotopic analysis by multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) using the standard-sample bracketing (SSB) method. Furthermore, by lowering the sample loading quantity, this protocol can also be used for the isolation and purification of Li from seawater. To assess the reliability of the proposed method, a systematic analysis was performed on eighteen widely used certified reference materials covering a diverse range of lithologies. The results demonstrate that our data are in excellent agreement with published reference values within analytical uncertainties. Collectively, the rapid Li separation protocol developed in this study integrates high efficiency, good reproducibility, and broad applicability, satisfying the demands for high-precision Li isotopic studies in diverse geological samples.

Several batches of NIST SRM 981 dissolved in 0.15 mol kg⁻¹ HNO₃ were used for the determination of K factors of isotope ratios ²⁰⁴Pb/²⁰⁸Pb, ²⁰⁶Pb/²⁰⁸Pb, and ²⁰⁷Pb/²⁰⁸Pb applying MC-ICP-MS. Pure solutions of the primary standard (reference) material NIST SRM 981 (w(Pb) ≈ 70 ng g⁻¹ to 100 ng g⁻¹) were compared with those treated with a chromatographic separation using a crown ether resin, and additionally with those treated with microwave digestion followed by chromatographic separation. The procedural blank influence was studied and potential interferences of ²⁰⁴Hg on the ²⁰⁴Pb signal were corrected. An improved chromatographic separation protocol demonstrates the suitability of Pb separation. Mass bias correction factors (K factors) were determined for each ratio and compared for the three procedures. The respective uncertainty budgets for the first time gave direct quantitative indications of differences and uncertainty contributions of the respective digestion and column separation processes compared to untreated solutions. To derive the impact of the preparation steps alone (digestion, column separation), pure SRM® solutions with Pb (no Pb containing matrix samples) were investigated. For K(²⁰⁴Pb/²⁰⁸Pb) an impact of a sample pretreatment cannot be observed and isotopic fractionation can be mainly deduced from the mass spectrometric measurement. In case of the ratios ²⁰⁶Pb/²⁰⁸Pb and ²⁰⁷Pb/²⁰⁸Pb, the K factors of the digested and column separated as well as only column separated samples can be distinguished from the non-pretreated samples for k = 1, which suggests a small, but observable impact of the sample history on the K factor although the initial samples were matrix-free.

Evaluating the ionization capability of microwave-induced plasma (MIP) ion sources remains challenging due to the lack of rapid, straightforward diagnostics. A rapid analysis platform integrating optical emission spectroscopy (OES) diagnostics with CCD-based plasma imaging was established in this study. An atmospheric-pressure argon MIP was characterized under varying microwave power (50–250 W) and argon flow rates (200–1000 SCCM). The results showed that T_exc ranged from approximately 4500 to 6340 K, T_rot from 758 to 1234 K, and N_e from 3.21 × 10¹⁴ to 5.55 × 10¹⁴ cm⁻³ across the tested conditions, in agreement with previously reported OES values for similar plasmas. Notably, the thermal and ionization characteristics of the plasma can be effectively regulated through optimization of the input power and gas flow rate. By analyzing the concomitant changes in plasma morphology, we further illustrate how discharge power and gas flow influence the stability and ionization behavior of the MIP. Finally, based on the calculated T_exc and N_e, the Saha framework was used to semi-quantitatively estimate the apparent ionization tendency of selected elements and compounds. The results indicate that the ion source exhibits a high ionization tendency for species with first ionization energies below 6 eV, whereas species with first ionization energies above 10 eV are difficult to ionize. Overall, the proposed integrated spectroscopic and imaging diagnostic platform provides a practical, rapid strategy for evaluating and improving MIP ion source performance. It also offers insights into further optimization of the ion source to enhance analytical capabilities.

Understanding the stable isotope fractionation mechanism of antimony (Sb) under different oxidation states is crucial for tracking its migration and fate in the environment. Redox-specific Sb isotope characteristics and fractionation behavior in natural environments remain poorly known, largely because Sb species of different oxidation states are difficult to separate. To address this limitation, an on-site separation method for Sb(III) and Sb(V) was developed using a strong cation-exchange resin (SCX, sulfonated silane resin) that does not induce Sb isotope fractionation. Separation conditions were optimized, and method robustness was evaluated systematically as a function of pH, ionic strength, total Sb concentration, the Sb(III)/Sb(V) ratio, and resin reuse cycles. The results indicate that Sb concentration and the Sb(III)/Sb(V) ratio have minimal effects on separation performance. Although pH and ionic strength exert pronounced influences on Sb speciation, recoveries remain stable at 95.0–100% over a pH range of 2–9 and an ionic strength range of 0.001–0.05 mol L⁻¹. Application to natural samples yields an Sb recovery of 98.6 ± 3.0%, with isotopic differences before and after separation of less than 0.1‰. Density functional theory (DFT) calculations indicate that Sb(III) is retained via outer-sphere complexation with sulfonic groups without direct bonding, which accounts for the absence of isotope fractionation; in contrast, Sb(V) interacts less favorably on thermodynamic grounds and is therefore weakly retained. By enabling on-site separation of Sb(III) and Sb(V) without inducing Sb isotope fractionation, this method provides the prerequisite for investigating Sb isotope signatures and fractionation behavior in complex natural matrices.

Fading of handwritten text in archival paper documents poses a significant challenge for information preservation and document analysis. Conventional restoration methods, particularly chemical treatments, may cause irreversible damage to both ink and paper substrates. In this study, a nondestructive elemental analysis strategy was developed to reconstruct faded handwriting by mapping the spatial distribution of inorganic elements remaining in ink traces. Field-emission scanning electron microscopy coupled with energy-dispersive spectroscopy (FESEM-EDS) and macro X-ray fluorescence spectroscopy (MA-XRF) were employed to obtain elemental distribution maps of faded scripts. Artificially aged ink samples were prepared through ultraviolet irradiation to simulate different degrees of fading. The results demonstrate that both FESEM-EDS mapping and MA-XRF can effectively identify elemental distributions in moderately faded handwriting and enable visual reconstruction of the original script morphology. However, when the elemental concentration decreases to approximately 0.211%, FESEM-EDS mapping shows limited capability for handwriting restoration. In contrast, MA-XRF maintains higher detection sensitivity and enables successful reconstruction under nondestructive conditions. The proposed elemental mapping strategy provides a practical analytical approach for the identification and visualization of severely faded handwriting in paper-based cultural heritage materials.

Laser-induced breakdown spectroscopy (LIBS) demonstrates substantial potential for rapid rock identification. However, its classification performance is limited when distinguishing rocks with highly similar elemental compositions due to the high dimensionality of spectral data and complex spectral feature relationships. This study employed seven diorite-related rock samples to systematically evaluate the effects of one-dimensional spectral representation and two-dimensional spectral transformation on classification performance. First, the original spectra were resampled from 16 376 to 1024 wavelength points using the piecewise cubic Hermite interpolation polynomial (PCHIP). Support vector machine (SVM) and one-dimensional convolutional neural network (1D-CNN) served as baseline models for one-dimensional classification. Subsequently, the one-dimensional spectra were converted into two-dimensional spectral images using Gramian Angular Summation Field (GASF) and continuous wavelet transform (CWT). Four two-dimensional models—2D-CNN, DenseNet121, GoogLeNet, and MSCNN—were then applied for classification. The results demonstrated that two-dimensional spectral representation significantly improved classification performance compared with direct one-dimensional spectral classification. The classification accuracies of SVM and 1D-CNN were 74.76% and 82.86%, respectively, whereas the accuracy, precision, and recall values of all two-dimensional models under both transformation methods exceeded 85%. Furthermore, the results indicated that the compatibility between model architecture and spectral transformation method further influenced the final classification performance. DenseNet121 achieved the highest accuracy of 97.62% under the GASF representation. In contrast, GoogLeNet and MSCNN performed better under the CWT representation, attaining accuracies of 95.71% and 96.67%, respectively. These findings suggest that two-dimensional spectral representation enhances the capability of LIBS to discriminate between similar rock samples. Furthermore, the final classification performance depends not only on the transformation method but also on its compatibility with the model architecture. This study provides a reference for optimizing spectral representation strategies in LIBS-based rock classification.