Abstract:Exploration for critical minerals, such as beryllium (Be) and uranium (U), requires accurate reserve assessment, for which drill core analysis is essential. Techniques like laser-induced breakdown spectroscopy (LIBS) and X-ray fluorescence spectroscopy (XRF) are widely used for rapid core analysis but have some limitations. LIBS suffers from poor sensitivity for low-concentration U, while XRF cannot detect Be. Furthermore, matrix effects in both techniques hinder the accurate simultaneous quantification of Be and U. We introduce a novel LIBS-XRF method for the simultaneous measurement of Be and low-concentration U. The methodology involves first analyzing samples with XRF and LIBS. Subsequently, a support vector machine (SVM) algorithm classifies the samples based on the XRF data. A separate predictive model is then developed for each category. A basic linear model is constructed using the spectral line of the target elements as the dominant factor based on dominant factor (DF) modeling strategy, and machine learning algorithms are then used to compensate for the residuals of this basic model. Tests on ore cores demonstrated that this method significantly reduces quantification errors. The achieved mean relative errors were 7.58% for Be and 7.02% for U. These results represent improvements of 61.42%/77.20% and 69.77%/72.48% over conventional unclassified and experience-based methods, respectively. This work is the first to use a LIBS-XRF approach for the highly accurate and simultaneous detection of Be and low-concentration U in ore cores, proving its high practical utility for this application.

Abstract:Dolomite [CaMg(CO?)?] is a major carbonate mineral playing a critical role in various geological processes. Its carbon isotopic composition (δ13C) serves as an irreplaceable tracer for understanding Earth’s history and the deep-time global carbon cycle. Secondary ion mass spectrometry (SIMS) is one of the most dominant techniques for dolomite C- isotopic analysis. However, the widespread application is hindered by a shortage of high-quality dolomite standards. Furthermore, the classical off-line procedure, which is both inaccurate and inefficient due to its need for extra electron probe microanalyzer (EPMA) chemical compositions to calibrate the instrumental mass fractionation (IMF), poses a practical limitation. This study reports three new dolomite C-isotopic microanalysis standards (1001, 1026 and 1055) with Fe# values [molar Fe/(Mg + Fe)] varying from 0.02 to 0.35. By the concurrent SIMS measurement of 13C?12C?56Fe16O?24Mg16O, an accurate and rapid online matrix effect calibration method for dolomite C-isotope analysis was developed. The overall uncertainty for individual sample analyses was estimated to be ±0.9‰ (2SD), derived by propagating the measurement precision and the calibration residuals in quadrature. The new method concurrently determines δ13C and the 56Fe16O/24Mg16O ratio (a proxy for Fe#) in a single SIMS analysis, enabling accurate matrix-effect calibration that eliminates biases caused by spatial mismatch between separate EPMA and SIMS analytical domains. The advancement in accuracy and efficiency, as demonstrated by SIMS carbon isotope analysis of dolomite, has the potential to significantly enhance the fidelity of reconstructing ancient environments, establish more robust boundaries for carbon cycling, and refine the interpretation of geological records.

Abstract:TC4 is a representative titanium alloy that has been widely used in the manufacture of critical aerospace components. Its mechanical properties can be significantly enhanced through appropriate heat-treatment processes. These enhancements are fundamentally attributed to heat-treatment-induced changes in the microstructural characteristics. Conventional microstructural characterization techniques are capable of directly revealing microstructural morphology and phase constituents. However, these methods are typically destructive and suffer from low inspection efficiency. To enable rapid and in situ identification of different heat-treated microstructural states in titanium alloys, this study exploits the matrix effects inherent to fiber-optic laser-induced breakdown spectroscopy (FO-LIBS) as discriminative features and proposes a LIBS-based spectral classification framework combining principal component analysis (PCA) and support vector machine (SVM). Random pulse-to-pulse fluctuations are mitigated through intra-spot multi-pulse averaging, followed by feature extraction using PCA. On this basis, an SVM classifier is constructed, with model performance evaluated via cross-validation and quantitatively assessed using confusion matrices. The results demonstrate that, compared with pulse-level spectral classification, samples subjected to intra-spot averaging exhibit markedly improved separability in the low-dimensional principal component space. Using the proposed model, classification accuracies of 100% and 99.8% are achieved for titanium alloy samples subjected to four and eight different heat-treatment conditions, respectively. These findings indicate that, when integrated with data-driven modeling strategies, LIBS shows strong potential for the rapid identification of material microstructural states.

Abstract:A method for the preconcentration and determination of Pd, Pt, and Au in ore was developed. A basic alumina sorbent with an 0.01 M HCl conditioning wash was used for the retention of chloro-complexed noble metals, which were then eluted with a 3% thiourea and a 10% aqua regia mixture. Flow injection was used for introduction of eluates into inductively coupled plasma mass spectrometry to effectively mitigate signal drift typically caused by thiourea with direct nebulization. Using this method, complete recovery (i.e. a 25-fold preconcentration) was achieved for Pd and Pt with an 8-fold recovery for Au and effective removal of matrix interferences. The method was validated using CDN-PGMS-29 ore reference material: agreement with certified concentrations of Pd, Pt and Au was achieved based on a Student’s t-test at the 95% confidence level. This simple, low-cost method enables efficient preconcentration of Pd, Pt and Au, making it well suited for trace determination of Pt, Pd and Au for geological applications.

Abstract:Surface-enhanced laser-induced breakdown spectroscopy (SENLIBS), with the advantage of higher detection sensitivity, is widely applied in the field of water quality monitoring. However, the self-absorption effect occurs, which reduces the accuracy of quantitative analysis. To correct for the self-absorption effect, the self-absorption coefficient (SA) iteration method was proposed. This method iteratively calculates the SA through the exponential fitting parameter of standard samples to correct the spectral intensity of standard samples and unknown sample. With this method, the SA values of Cr spectral lines were corrected to be closer to 1. As a result, the average limit of detection (LOD), average of the average relative error (ARE), and average root mean square error of cross-validation (RMSECV) were reduced from 0.118 ppm to 0.057 ppm, 39.94% to 14.00%, and 0.752 ppm to 0.403 ppm, respectively. This demonstrated that SA iteration method could improve the quantitative analysis performance of LIBS by correcting for the self-absorption effect.

Abstract:A study on Pb isotopes was conducted within the soil–plant–aerosol system. The results indicate that Pb isotopes serve as a suitable tool not only for tracing atmospheric pollution sources but also for tracking the Pb transfer process into and within plants. The main findings are as follows: 1) Pb isotopes in plants are a powerful tool for tracing Pb sources. When plants are removed from their original location, Pb isotopes in the whole plant or roots are suitable for tracing their growth sites; Pb isotopes in leaves are suitable for tracing aerosol particles in the surrounding environment; however, Pb isotopes in stems are not suitable for tracing Pb sources. 2) Pb isotopic fractionation occurs during the growth process of E. splendens Nakai (δ208Pb?????–???? = -4.31 to 0.30‰), and the extent of fractionation is larger than that of most mineral nutrients. This study also demonstrates that Pb isotopes in plants are a powerful tool for tracing the absorption and transport processes of Pb into and within the plant. Regardless of whether Pb is absorbed through the roots or leaves, lighter isotopes tend to be preferentially enriched in the subsequent tissues (from soil to root, from root to stem, and from leaf to stem within the plant), indicating non-selective absorption of Pb through ion channels. This is consistent with the diffusion effect on isotope ratio variation. Pb absorbed through the roots constitutes the main source of Pb in the plant. 3) The correlation between Pb isotope ratios could verify Pb pathways. Whether the correlation conforms to the principle of mass fractionation depends on whether Pb comes from one path or multiple pathways. This provides a new insight into understanding Pb sources in any physicochemical process or geological sample. 4) The addition of ethylene diamine disuccinic acid (EDDS, C??H??N?O?) promotes the uptake of Pb in the plant. However, it only affects the Pb concentration in the root and stem, but not in the leaf. This shows that altering soil state and promoting plant absorption are not ideal for reducing Pb pollution in soil for non-accumulator plants. The addition of EDDS in the soil also affects the variation in Pb isotope ratios within the plant. Compared with CK plants, heavier Pb isotopes were enriched in the EDDS-treated plants, which suggests a plant protection mechanism whereby heavier Pb isotopes are stored in biological macromolecules such as Pb-proteins/ligands to mitigate toxicity.

Abstract:Stable isotope systems of iron, copper, and zinc have emerged as powerful tracers in understanding metal sources, migration, and deposit formation processes. Accurate and precise determination of Fe, Cu, and Zn isotopic compositions in sulfide minerals, especially in simple-matrix minerals characterized by their relatively pure composition, with low content of impurity elements and few interfering components, requires matrix-matched reference materials to validate analytical methods, particularly for direct analysis protocols without column chromatography. This study introduces a suite of novel secondary reference materials (NWU-Fe, NWU-Cu, and NWU-Zn sulfide powders) developed to address the critical gap in calibration standards for direct isotopic analysis without column chemistry of simple-matrix minerals. These sulfide powders exhibit excellent homogeneity and stability, fulfilling the requirements for high-precision determination of Fe, Cu, and Zn isotope ratios using MC-ICP-MS without column chemistry. Reference values were derived from interlaboratory comparisons across three independent laboratories. The isotopic compositions (δ-values), reported in per mil notation relative to international standards (IRMM-014 for Fe, NIST SRM-976 for Cu, and JMC-Lyon for Zn), are as follows: δ56Fe = -0.38 ± 0.03‰ (2s), δ65Cu = 0.44 ± 0.04‰ (2s), δ66Zn = -0.04 ± 0.02‰ (2s). This study provides a robust calibration framework for Fe-Cu-Zn isotopic studies in geochemistry and environmental science.

Abstract:Zircon U-Pb and Hf-O isotope compositions preserve valuable records of the formation and evolution of geological processes. To obtain accurate and precise zircon geochronology and Hf-O isotope ratios using in situ techniques, matrix-matched reference materials are essential. In this study, we introduce a new potential zircon reference material, the Perilla megacryst, which has homogeneous U-Pb ages and Hf-O isotopic compositions, as demonstrated by multiple analytical techniques. The chemical abrasion isotope dilution thermal ionization mass spectrometry (CA-ID-TIMS) method presents a weighted mean 206Pb/238U age of 42.40 ± 0.06 Ma (2σ, n = 8). Further examination of the heterogeneity of U-Pb ages of the Perilla zircon megacryst was conducted by secondary ion mass spectrometry (SIMS) and laser ablation (multiple collector) inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) among six laboratories. We obtained mean 206Pb/238U ages of 42.6 ± 0.3 Ma (2σ, n = 23) using SIMS (SHRIMP), 42.6 ± 0.3 Ma (2σ, n = 20) using SIMS (CAMECA), 42.2 ± 0.3 Ma (2σ, n = 14) using LA-MC-ICP-MS, and 42.6 ± 0.1 Ma (2σ, n = 207) using LA-Q-ICP-MS, respectively. The Hf isotopic compositions of Perilla were evaluated using LA-MC-ICP-MS, yielding a uniform mean 176Hf/177Hf ratio of 0.282565 ± 0.000040 (2SD, n = 149) among four laboratories. Oxygen isotope analysis using laser fluorination yielded results consistent with SIMS data, providing a recommended mean δ18O value of 6.53 ± 0.34 ‰ (2SD, n = 5). The reproducibility of results obtained from multiple analytical techniques across different laboratories demonstrate the homogeneity of U-Pb ages and Hf-O isotopic compositions in the Perilla zircon megacryst. Based on these results, we propose the Perilla zircon megacryst as a potential secondary reference material for external monitoring or analytical validation of Cenozoic U-Pb geochronology and Hf-O isotopic measurements.

Abstract:Magnesium (Mg) isotopic composition of sedimentary silicate fractions provides key critical constraints on the history of silicate weathering and climate evolution. Since sedimentary rocks typically contain authigenic carbonates, standard whole-rock digestion co-dissolves both carbonate and silicate phases, resulting in hybridized Mg isotope signals. Accurate analysis therefore requires separation of silicate components through selective dissolution methods that exclude Mg from carbonates. However, standardized dissolution methods specifically designed for Mg isotope analysis of the silicate phase in sedimentary rocks are still lacking. Significant variations exist among different pretreatment protocols, particularly in the choice of leaching reagents and cleaning procedures. And the Mg isotope fractionation behavior of silicate phases under different acid reagents and leaching procedures remains unclear. In particular, the effects of strong acids on silicate components and the potential extent of induced fractionation are not well constrained. This issue becomes notably critical in studies requiring high-precision Mg isotope analysis. In this investigation, we have systematically designed and performed chemical leaching experiments on Marinoan diamictites from South China to develop an optimized and robust leaching pretreatment scheme for Mg isotope studies of clastic silicate fractions. Our results demonstrate that 0.5 mol·L-1 Acetic acid (HAc) exhibits limited efficiency in leaching poorly soluble carbonate minerals (e.g., siderite), as shown by only 7.7% and 1.4% decreases in the leached residue's Mg/Al and Fe/Al ratios relative to the whole-rock values. For samples containing Mg-rich and Fe-rich carbonates, 0.4 mol·L-1 hydrochloric acid (HCl) is recommended to ensure efficient carbonate removal and subsequent reliable acquisition of silicate Mg isotope signatures. This study provides the essential experimental basis for developing sedimentary Mg isotopes as a quantitative paleoenvironmental proxy, thereby enabling more refined reconstructions of Earth's surface evolution.

Abstract:Graphite can preserve crucial information related to the carbon cycle in metamorphic, magmatic, and hydrothermal systems. However, traditional bulk isotope analysis often obscures significant microscale heterogeneity. This study establishes a reliable protocol for in situ carbon isotope analysis of graphite using laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS). Two critical challenges were addressed: the mass loading effect and the scarcity of appropriate reference materials. Mass loading induces significant carbon isotope fractionation, with the δ13C deviation showing a linear dependence on the 12C? intensity ratio of sample to standard (12C?Isam/12C?Istd). This deviation intensifies as the ratio diverges from 1, surpassing |2‰| at values of 0.2 and 2.6. The application of a linear regression correction reduces the deviations at these extreme ratios (0.2 and 2.6) from over |2‰| to within 0.50‰. Commercial pencil leads were validated as cost-effective reference materials for the in situ C isotope analysis of graphite. The 2H grade exhibited excellent micro-scale homogeneity (0.30‰, 2SD), performing slightly better than pressed pellets of the United States Geological Survey graphite standard USGS24 (0.50‰, 2SD), and negligible inter-matrix fractionation between these two samples (|Δδ13C| ≤ 0.22‰). Calibration of variable-grade pencil leads (2B to 6B) achieved precisions ranging from 0.12‰ to 0.58‰ (2SD), with deviations within 0.18‰ of IRMS values. The method provides high spatial resolution with sub-permil accuracy, enabling resolution of intra-crystalline δ13C zoning in graphite. It offers a robust framework for reconstructing metamorphic temperature histories, tracing carbon sources, and investigating fluid-mediated carbon precipitation in geological systems.

Abstract:High precision magnesium isotope data have been widely used in geological and astrochemical research. Previous studies used cation-exchange resins (e.g., AG50W-X8, AG50W-X12, AGMP-50) for Mg purification of routine geological samples, and these Mg purification protocols yield solutions meeting multiple-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) analytical requirements, but one problem with the reported protocols is that the elution procedure is complex and time-consuming. In addition, some manganese nodule and shale samples have high Mn/Mg mass ratios. Previous studies have used highly concentrated HCl (e.g., 9–12 mol·L?1 HCl) or acetone (95%) to separate Mg from Mn and other elements. However, a low Mn removal efficiency, alongside the toxicity of acetone, may limit the purification of Mg in high-Mn samples (Mn/Mg >16), suggesting that further improvements should be made to the protocol. Here, we developed an efficient, user-friendly, and highly robust protocol for Mg isotope purification and analysis by MC-ICP-MS. Briefly, to isolate Mg from high-Mn matrices, an initial separation from matrix elements (e.g., Mn, Cu, Zn) was performed using AGMP-1M resin (100–200 mesh) eluted with 4.5 mL of 10 mol·L?1 HCl. A subsequent purification step using AG50W-X12 resin (200–400 mesh) was applied to remove major residual matrix elements with a mixed HNO?–HF solution, and Mg was finally collected by elution with 8 mL of 2 mol·L?1 HNO?. With this method, the yield during Mg purification was ~100%, and after one column or a two-column pass, most geological samples were suitable for high-precision Mg isotope analysis. We demonstrate that our method yields accurate Mg isotope ratios with a precision of ±0.07‰ for δ2?Mg, based on analyses of seawater, basalt, granodiorite, shale, manganese nodule, and carbonate reference materials.

Abstract:Elemental analyzer - isotope ratio mass spectrometry (EA-IRMS) is the most popular method for the measurement of sulfur isotopes in various samples including sulfide, sulfate and organosulfur compounds. The precision of ~±0.3‰ (1σ) can be achieved for samples with ~100 μg S. However, for samples with low sulfur content, or organic matter in particular (e.g., animal bone collagen), the precise and accurate sulfur isotope analysis remains challenging, with typical δ34S precision ranging from ±0.3‰ to ±1‰. In this study, we applied an improved EA-IRMS with a custom-built cryofocus device for the analysis of sulfur isotopes in organic matter. After sample combustion, all the product gases were transferred into a cold trap by a fast helium flow (100 mL/min). SO2 was then separated from other gases through a packed gas chromatographic (GC) column at lower flow rate (10 mL/min). The sample size of this method is ~300 nmol S, which is only 1/10 of that required by the conventional method. Lowered sample size allows fully oxygen isotope homogenization of sample SO2 with oxygen buffers during combustion. With this method, the δ34S precision from the measurement of organosulfur standards was better than ±0.3‰.

Abstract:Given the increasingly serious threat of heavy metal pollution in farmland to the safety of agricultural products and human health, it is of great significance to develop rapid, non-destructive detection technologies. Traditional chemical detection methods suffer from being destructive, time-consuming and costly. In contrast, spectrum and imaging technology has become the research hotspot due to its advantages of fast and non-destructive. Heavy metal pollution alters the physiological and biochemical characteristics and optical responses of crops. Spectrum and imaging technology can rapidly and non-destructively obtain the corresponding spectral and spatial information, providing a way for pollution screening and quantitative and qualitative analysis. This paper systematically reviews the application of spectral imaging techniques such as visible/near-infrared spectroscopy, hyperspectral imaging, fluorescence hyperspectral imaging, laser-induced breakdown spectroscopy, and Raman spectroscopy in this field, and identifies that these technologies existing limitations and challenges. Future research should focus on multi-technology integration, model universality improvement, and portable device development. Through algorithm optimization, cost control and the extension of the industrial chain, the in-depth application of spectrum and imaging technology should be promoted. This article aims to provide theoretical references and practical guidance for the research and application of rapid non-destructive detection technology for heavy metals in crops.

Abstract:Laser-Induced Breakdown Spectroscopy (LIBS)technology, a type of atomic emission spectrometry analysis that utilizes a laser as an excitation source, has undergone rapid development in recent years owing to its rapid, in-situ, multi-element detection capabilities and minimal sample preparation. Although its sensitivity is generally lower than that of inductively coupled plasma mass spectrometry (ICP-MS) and some other techniques, LIBS—by virtue of its deployment flexibility, portability, and the foregoing attributes—is better suited to online monitoring. This work summarizes the latest research progress of LIBS in the field of real-time monitoring and provides a comprehensive comparative analysis of the strengths and weaknesses of LIBS relative to XRF, ICP-MS, and other related techniques, specifically focusing on industrial raw material/product quality control during manufacturing, in situ elemental analysis during laser processing, and environmental pollutant emissions tracking. Across these applications, LIBS exhibits variable detection stability and sensitivity: in industrial settings, relative standard deviations (RSDs) typically remain below 15% (with minor elements reaching 15–30%), while detection limits (LODs) predominantly range at ppm levels (with limited ppb-level achievements). Environmental monitoring shows RSDs heavily dependent on instrumentation and field conditions, with reported LODs spanning ng/m3 to mg/m3 (air pollutants), μg/L to mg/L (water quality), and mg/kg (soil analysis). This work also explores the practical challenges encountered during the implementation of LIBS across various domains. In the industrial sector, the primary obstacles involve suboptimal detection accuracy and stability, stemming from high solid-surface complexity, the difficulties of liquid metal analysis, contamination of metallurgical molds, and harsh operating environments. Within the field of laser processing, the challenges mainly arise from the instability of the welding molten pool and the ambiguity in defining thresholds for determining the extent of machining. Conversely, environmental monitoring is primarily constrained by relatively low sensitivity when analyzing gaseous and liquid states. Finally, targeted solutions corresponding to the specific technical challenges in each field are proposed. Future developments in signal enhancement are anticipated to overcome current technical constraints, enabling robust high-sensitivity, multi-element detection in complex sample systems.