Abstract:Water is a critical volatile component in planetary bodies and plays a key role in the Earth’s dynamic evolution. Traditional methods to analyze water in either mineral or glass phases are usually limited to areas larger than 10 microns. The advent of secondary ion mass spectrometry (SIMS), especially nanoscale SIMS (NanoSIMS), has enabled in situ analysis at micron- to submicron scales. However, there is an increasing demand to quantify water content at much finer scales, including those recovered from high-pressure experiments or nanoscale planetary materials. This study demonstrates the ability of atom probe tomography (APT) to investigate the distribution of hydroxyl water in glass at sub-nanoscale resolution. Five glass working standards with trace amounts of water were analyzed to demonstrate that the OH+ mass spectrum obtained by APT could potentially represent the hydroxyl content of the glass. The detection limit of the APT was determined to be better than 0.02 atomic %. The heterogeneity of APT OH+ in the form of nanoclusters in glass was readily discerned, and its concentration in the nanoclusters increased proportionally to the water content in the studied samples. These findings provide valuable insights into the sub-nanoscale distribution of hydroxyl water in glasses and establish APT as a promising tool for characterizing water at an ultra-high spatial resolution.

Abstract:This paper describes the use of an ionic liquid ferrofluid for the preconcentration and simultaneous ultra-trace determination of inorganic As and Se species in waters by inductively coupled plasma mass spectrometry. An ultrasound-assisted sol-gel method was used for the synthesis of silica and titania coated and N-(2-aminoethyl)-3-aminopropyltrimethoxysilane functionalized magnetic nanoparticles (SCTCMNPs-AEAPTMS). The structural features of the SCTCMNPs-AEAPTMS were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive X-ray spectroscopy, X-ray diffraction, and transmission electron microscopy. Experimental conditions, including the sample solution pH, elution time, and eluent concentration, were optimized. After oxidation of As(III) and Se(IV) to As(V) and Se(VI) by using H2O2, the total concentrations of As and Se were determined and those of As(III) and Se(IV) were obtained through subtraction of the concentration of As(V) and Se(VI) from the total concentrations. Under the optimal experimental conditions, the detection limit for As(V) and Se(VI) were 0.3 ng L-1 and 0.2 ng L-1 respectively. The accuracy of this method was verified by analyzing a certified reference material (1568a Rice Flour): the measured As and Se concentrations agreed with the certified values based on a Student’s t-test at the 95% confidence level. The proposed method was also successfully applied to the preconcentration and ultra-trace determination of As and Se species in different water samples.

Abstract:Microplasma-based optical emission spectroscopy (MP-OES) has great potential for application in analytical chemistry. However, further integration of efficient sample introduction methods is essential to enhance its capability for elemental field detection. Herein, a handheld nozzle-electrode point discharge optical emission spectrometry (μPD-OES) device coupled with a self-heating solid-phase microextraction (SH-SPME) device was constructed, which integrated sample introduction, detection, and data processing systems with low power consumption (~ 25 W) and battery-powered operation. The innovative SH-SPME completed thermal analyte desorption by directly heating the SPME fiber through a mini voltage regulator circuit board, significantly reducing power consumption and eliminating the external heating and high-temperature thermal desorption chamber required for conventional SPME-μPD-OES. The customized SH-SPME-μPD-OES device was successfully applied to analyze lead in urinary and other biological samples, with a limit of detection of 1.2 μg L-1 and recoveries ranging from 92% to 108%. It is worth noting that SH-SPME allows the building of a palm-sized atomic spectrometer (20.3 cm length × 10.3 cm width × 10.5 cm height). This device represents an important breakthrough in miniaturized atomic spectrometers and holds promise as a valuable tool for on-site elemental monitoring in various fields.

Abstract:In inductively-coupled plasma – mass spectrometry (ICP-MS) analyses, internal standards are often used to correct for signal variability. Determining the best internal standard has historically involved matching certain characteristics of the internal standard element like mass or first ionization energy to the analyte of interest. However, advances in ICP-MS such as reaction cell (RC) technology, which can effectively modify the ion beam or chemically alter the analyte of interest, introduce new considerations for the choice of internal standard. The commonly used internal standard elements 6Li, 45Sc, 69Ga, 74Ge, 89Y, 115In, 159Tb, 165Ho, 187Re, 193Ir, and 209Bi were analyzed under five different analytical conditions and displayed a wide range of RC behavior including suppressed signal, increased signal (collisional focusing) and product ion formation. The behavior of these elements is not correlated to first ionization energy or mass and the product ions formed with NH3 or O2 as a cell gas are not consistent for all elements. To evaluate their use as internal standards, several product ions were used to correct the mass-shifted analysis of As, Fe, S and Zn in the NIST standard reference materials SRM 1573a Tomato Leaves and SRM 1577c Bovine Liver. With few exceptions, both mass-shifted and on-mass internal standards were effective in correcting the analytes of interest. Poor performance of the internal standards could be explained by sample matrix specific interferences, highlighting the importance of understanding RC behavior and its influence on analyses.

Abstract:As the selenium (Se) levels in the serum are critical to human health, it is imperative to develop highly sensitive analytical methods for determining the content of Se in the serum. Although using O2 as a reaction gas in the MS/MS mode can effectively eliminate spectral interference, the sensitivity for determining Se remains low with the use of inductively coupled plasma tandem-mass spectrometry (ICP-MS/MS). In this study, a new strategy of using ICP-MS/MS to determine the trace Se level in human serum containing gadolinium (Gd)-based magnetic resonance imaging (MRI) contrasting agents was proposed. In the MS/MS mode, N2O was used as the reaction gas, N atom transfer reaction between N2O and Se+ was adopted, and SeN+ was selected as the detection ion to eliminate all mass spectrometric interferences, including Gd++. The accuracy and precision of the analytical method were evaluated by using standard reference materials. The results obtained indicated that interference-free determination of the Se level can be achieved by using high abundance isotopes 80Se and 78Se in the N2O reaction mode. The sensitivity of Se was higher when compared to that of the case in the conventional O2 reaction mode. The limit of detection (LOD) was set as low as 2.19 ng L-1 (for the most-abundant Se isotope). The RSD was 2.5%–4.2%, and the spiking recovery was 94.8%–106%. The proposed method is simple and practical, with high sensitivity and good accuracy and precision. The present study offers not only a precise and dependable approach for the highly sensitive detection of Se level in human serum containing gadolinium (Gd)-based MRI contrast agents but also introduces a novel concept for designing an N2O-reaction mode to eliminate spectral interference, thereby enabling the wider application of Se detection across various fields.

Abstract:Laser-induced breakdown spectroscopy (LIBS) detection on coal in particle flow form is more real-time and beneficial for the effective use of coal. However, the inevitable instability fluctuation of particle flow affects the laser ablation and spectral collection. This work attempted to use particle flow confinement schemes and spectral screening to optimize the quantitative analysis performance of coal particle flow. A cylindrical spatial confinement was developed to stabilize the coal particle flow, laser ablation and plasma evolution. Then a relative signal-to-noise ratio (RSNR) method was proposed for spectral data screening to overcome the inadaptability of traditional signal-to-noise ratio (SNR) method to the samples with large difference in SNR. Based on the RSNR method with the optimal screening threshold obtained by cross-validation, the spectral relative standard deviation (RSD) such as C I 247.86 nm and Mg I 285.21 nm were significantly reduced. Subsequently, quantitative analysis models for coal proximate analysis indexes were established. The models employing RSNR method and spatial confinement showed the superior performance. The root mean square error of prediction (RMSEP) of ash content, fixed carbon content, volatile matter content and calorific value were improved from 3.5667%, 3.3965%, 3.0905% and 1.0188MJ/Kg to 1.6280%, 2.0344%, 1.4999% and 0.4553MJ/Kg. The proposed spatial confinement and RSNR method have applicability and mutual gain for quantitative analysis of coal particle flow.

Abstract:High-quality Sr isotopic data are critically dependent on the quality of reference materials that are used for instrumental calibration and data monitoring during LA-MC-ICP-MS analysis. Two natural apatite samples (SL-7 and SM139-1) were investigated here to test their suitability as in-situ Sr isotopic analysis reference materials. Major and trace element analyses by EPMA and LA-ICP-MS show that apatites are all characterized by high Cl (1.80~2.46 wt%), high Sr contents (> 3752 μg g-1) and extremely low Rb/Sr ratios. A total of 120 and 126 LA-MC-ICP-MS analyses for SL-7 and SM139-1 apatite show consistent and homogeneous Sr isotopic compositions with average 87Sr/86Sr ratio of 0.70521 ± 0.00016 (2SD, n = 120) and 0.70509 ± 0.00015 (2SD, n = 126), respectively, which are in good agreement with solution-based data determined by TIMS or SN-MC-ICP-MS (0.705219 ± 0.000019 (2SD, n = 13) and 0.705114 ± 0.000041 (2SD, n = 13), respectively), suggesting that SL-7 and SM139-1 apatites can be used as potential reference materials for microbeam Sr isotopic analysis.

Abstract:In recent years, laser-induced breakdown spectroscopy (LIBS) combined with machine learning methods has become a hot research topic for detecting malignant tumors. For gliomas with infiltrative features, the tumor boundary is difficult to identify during surgery. To improve the survival time of patients, surgeons often perform extended resection, potentially damaging functional brain areas. Therefore, it is crucial to help surgeons quickly and accurately identify tumor resection boundaries during surgery. In this paper, simulation experiments are conducted using isolated tissues, proposing a polarization-resolved LIBS (PRLIBS) spectral fusion method to boost the accuracy of glioma boundary tissue detection. First, the polarization effect of the plasma emission is analyzed using the Stokes parameters, and it is found that the plasma emission belonged to partially polarized light. To better exploit the polarization information of the plasma, the polarized spectra from the four channels are fused to build a machine learning model. Comparing to classification models using LIBS intensity spectra, polarization parameters, and single-channel polarization spectra, the PRLIBS fusion model exhibits superior classification performance. The correct classification rate (CCR) of support vector machine (SVM) model is 99.05% for the training set and 89% for the test set, respectively. In the future, the PRLIBS spectra fusion method proposed in this research can be used for glioma boundary tissue identification.

Abstract:Alternative protein sources such as insects are of interest because of their many nutritional and ecological benefits compared to traditional animal-based proteins. As they may contain potentially toxic elements in addition to essential elements, their analysis is important to ensure their safety for human consumption. To avoid time-consuming acid digestion, which may lead to contamination or loss of analytes, the direct analysis of insects via solid sampling electrothermal vaporization coupled with inductively coupled plasma optical emission spectrometry (SS-ETV-ICPOES) was explored for the first time. Different approaches for the analysis of black soldier fly meal were evaluated, using CF4, polytetrafluoroethylene (PTFE) powder pre-mixed with the sample, or PTFE pre-mixed with the sample and H2 in the carrier gas as chemical modifier. Addition of N2 as a sheathing gas around the ETV effluent to increase plasma robustness was also studied. The best results were obtained with the Ar-N2 mixed-gas plasma, PTFE powder pre-mixed with samples, and H2 in the carrier gas, allowing the accurate determination of Cd, Co, Fe, K, P, S, and Zn in black fly soldier meal in 100 s by external calibration with a dogfish muscle certified reference material (CRM) and internal standardization with Ar 404.442 nm to compensate for sample loading effects on the plasma. Application of this method to other insects resulted in accurate results for Co, Fe, and S in cricket flour as well as Co, Fe, P, S, and Zn in mealworm powder. Thus, SS-ETV-ICPOES shows promise as a screening method for insect analysis.

Abstract:The analysis accuracy of energy dispersion X-ray fluorescence spectrometry (XRF) for detecting heavy metal in agricultural soils is severely depending on complex matrix effect, thereby posing a challenge in fast and precise monitoring soil contamination. To calibrate the XRF detection, a Gaussian mixture clustering-multilevel model (GMC-MLM) was proposed to enhance XRF accuracy for Cd in agricultural soils. Compared with other models such as multiple linear regression (MLR), random forest regression (RF), and support vector machine regression (SVMR), the GMC-MLM effectively disentangled the nested distribution of XRF detection errors. The correlation coefficient between the XRF detection results and ICP-MS test results for the corrected samples can reach 0.9085, with 74% of the corrected samples having a relative error of less than 30%. Notably, according to the GMC-MLM correction method, a knowledge base for localizing corrections in XRF detection has been constructed. When the number of knowledge base sample points is 50, the RMSE (Root Mean Squared Error), and REM (Relative Error of Mean) are 0.7347, 3.7014%, respectively. It can be observed that the model has good extrapolation capability, and with the increase in the number of knowledge base sample points, the correction effect based on the knowledge base gradually stabilizes. This knowledge base-based GMC-MLM calibration method can be embedded into XRF detection instruments to recalibration XRF detection results.