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This paper presents a self-consistent multi-dimensional mathematical model and a numerical approach for simulating the low-temperature plasma induced by the femtosecond laser filament. Addressing limitations in current models, we analyze key aspects of the laser plasma behavior, including plasma generation, detailed chemical kinetics, energy exchange channels, total energy balance, and hydrodynamics. The developed model and LOTASFOAM code are applied to study the temporal and spatial decay of the plasma produced by a femtosecond laser pulse in pure nitrogen at atmospheric pressure. The paper also includes a discussion on the spatial and temporal dynamics of electronically excited states of nitrogen in the decaying laser plasma. [ABSTRACT FROM AUTHOR]

Conventional time-of-flight methods can be used to determine carrier mobilities for photovoltaic cells in which the transit time between electrodes is greater than the RC time constant of the device. To measure carrier drift on sub-ns timescales, we have recently developed a two-pulse time-of-flight technique capable of detecting drift velocities with 100-ps time resolution in perovskite materials. In this method, the rates of carrier transit across the active layer of a device are determined by varying the delay time between laser pulses and measuring the magnitude of the recombination-induced nonlinearity in the photocurrent. Here, we present a related experimental approach in which diffractive optic-based transient grating spectroscopy is combined with our two-pulse time-of-flight technique to simultaneously probe drift and diffusion in orthogonal directions within the active layer of a photovoltaic cell. Carrier density gratings are generated using two time-coincident pulse-pairs with passively stabilized phases. Relaxation of the grating amplitude associated with the first pulse-pair is detected by varying the delay and phase of the density grating corresponding to the second pulse-pair. The ability of the technique to reveal carrier diffusion is demonstrated with model calculations and experiments conducted using MAPbI3 photovoltaic cells. [ABSTRACT FROM AUTHOR]

Laser-induced breakdown and subsequent plasma are produced in ambient air in the proximity of an aqueous surface using a Nd:YAG Q-switched laser at 1064 nm with a pulse width of 9 ns and a delivered focused input energy of 170 mJ. The distance between the focal point of a 10 cm convex lens and the aqueous surface is 4 mm with laser propagation perpendicular to the surface. Using an intensified CCD camera attached to a 1-m spectrometer, spatial and wavelength-resolved plasma emission data are obtained for delay times after breakdown ranging from 50 ns to 10 μs with a gate window typically 5 ns. Plasma electron density is determined by applying Lorentzian fitting and FWHM extraction to three Stark-broadened spectral lines: N II 3P-3Do multiplet (593.85 nm), Hα (656.27 nm), and the Na D doublet (589.00 and 589.59 nm). One-dimensional spatially resolved measurements of the total emission intensity and electron density are obtained by binning the camera image along the laser axis in intervals of 250 μm and are reported as a function of time from 50 ns to 10 μs. Two plasmas are ignited from a single laser pulse; one from laser breakdown at the water surface and the other a few nanoseconds later from laser-induced air breakdown at the focal point of 4 mm above the water surface. Comparisons between the evolution of the air plasma near and far from the water surface are presented along with data for the water surface plasma itself. [ABSTRACT FROM AUTHOR]

This study presents a pioneering approach that combines artificial intelligence and laser-induced breakdown spectroscopy (LIBS) to predict soil moisture content (MC). The traditional laboratory-based method of MC measurement, involving soil weight comparison before and after heating, is time-consuming, labor-intensive, and prone to low accuracy. In this work, we propose a non-destructive soil MC measurement technique utilizing robust nonlinear models based on LIBS-derived elemental intensities. Support vector regression (SVR) and AdaBoost-based SVR models (SVR-ADB), employing Gaussian Kernel and input features from LIBS data, were employed for MC prediction. Model performance was assessed using standard metrics such as root mean square error, mean absolute error, Nash–Sutcliffe efficiency (NSE), and correlation coefficient (CC) between predicted and actual moisture content. The study employed 485 datapoints generated in our laboratory. An advanced feature optimization technique based on the correlation between the soil MC and the descriptors was employed to select relevant mineral elements as input features. Three feature combinations (Combo-1, Combo-2, and Combo-3) were evaluated to identify the most effective configurations for accurate soil MC predictions. SVR-ADB-3 (Combo-3) demonstrated the highest prediction efficiency in the testing phase, achieving an impressive CC of 0.9998 and NSE of 0.9997. Consistently, Combo-3 outperformed other configurations, emphasizing the importance of the selected features. Validation of the developed models on soils treated with cement and lime stabilizers, whose data were not used during model calibration and verification, confirmed the generalization capability of the models. This study provides valuable insights for policymakers and industry stakeholders, facilitating optimized soil moisture management practices. [ABSTRACT FROM AUTHOR]

ABSTRACT This study discusses potential toxic elements detection in conventional nail polish, including Cr and Pb. The noteworthy results highlight well‐established potential risks of elevated Cr and Pb concentrations. These elements are not allowed in the European Union. Implementing the minimum spanning tree (MST) approach and the isolation forest algorithm effectively clustered samples. Forty‐five samples were analyzed, and four clusters were identified. Two presented six samples with high concentrations of Fe (Cluster 1 with four samples) and Cr and Pb (Cluster 2 with two samples). The other 39 samples presented low concentrations of the determined elements (Co, Cr, Cu, Fe, Ni, and Pb). Cadmium, Zn, and Mn were not detected in any of the analyzed samples. Furthermore, integrating energy‐dispersive x‐ray fluorescence (ED‐XRF) and laser‐induced breakdown spectroscopy (LIBS) enabled fast direct analysis of nail polish samples, streamlining a swift and reliable data acquisition process. This research underscores the importance of ongoing vigilance and monitoring of potential health hazards associated with nail polish formulations, especially in regions with regulatory restrictions on certain elements. [ABSTRACT FROM AUTHOR]

A high‐throughput experimental approach is developed to assess the correlations between chemical composition, structure and conduction properties of inorganic solid ionic conductors. This approach covers the preparation of a large number of samples by combinatorial synthesis, followed by fast characterization of the material library. The approach is primarily based on combinatorial synthesis by magnetron co‐sputtering and the characterization of thin film samples where lithium phosphorus oxynitride (LiPON) is chosen as a case study. A library of 76 LiPON materials is prepared in one experiment from the reactive co‐sputtering of LiPO3 and Li3PO4 in a N2 atmosphere. A specific sample design allows conducting thickness and impedance measurements, Raman spectroscopy, then fast and spatially‐resolved chemical analysis by Laser‐Induced Breakdown Spectroscopy (LIBS) on each material. Particular developments are devoted to this technique to achieve quantitative analysis of lithium in thin films. The materials cover a wide range of compositions with 0.95

A novel analysis technique of elements at ambient conditions has been developed. The technique is based on microwave-assisted laser-induced breakdown spectroscopy (MW-LIBS) applied to acoustically levitated samples. The technique has been demonstrated using three solid samples with different properties and compositions. These are ore containing multiple elements (OREAS 520), aluminium oxide (Al3O2) and gypsum (CaSO4·2H2O). The mass of samples was 21 mg, 23 mg, and 55 mg for gypsum, mineral ore, and Al3O2, respectively. Significant signal enhancements were recorded for a variety of elements, using microwave-assisted laser-induced breakdown spectroscopy and levitation (MW-LIBS–Levitation). The signal enhancement for Mn I (403.07 nm), Al I (396.13 nm) and Ca II (393.85 nm) was determined as 123, 46, and 63 times, respectively. Moreover, it was found that MW-LIBS–Levitation minimises the self-absorption of the Ca I (422.67 nm) and Na I (588.99 nm and 589.59 nm) spectral lines. In addition to the signal enhancements, the levitation process produces a spinning motion in the solids with an angular frequency of 7 Hz. This feature benefits laser-based analysis as a fresh sample is introduced at each laser pulse, eliminating the need for the usual mechanical devices. Based on the single-shot analysis, it was found that ∼80% of the laser pulses produced successful MW-LIBS–Levitation detection, confirming an impressive repeatability of the process. This contactless analytical technique can be applied in ambient pressure and temperature conditions with high sensitivity, which can benefit disciplines such as forensics science, isotope analysis, and medical analysis, where the sample availability is often diminutive. [ABSTRACT FROM AUTHOR]

Sheet Molding Compound (SMC) materials are extensively utilized as high-voltage insulation materials in electrical equipment. SMC materials are prone to aging after long-term operation. Conducting non-destructive testing to assess their electrical and physicochemical properties is crucial for the safe operation of electrical equipment. This study identifies the optimal equipment parameters for testing SMC materials using Laser-Induced Breakdown Spectroscopy (LIBS) technology through experimental investigation and also explores the ablation characteristics of SMC under various laser parameters. The results indicate a significant positive correlation between the ablation depth and laser pulse number, while there is no correlation with single laser pulse energy. However, the ablation area demonstrates a strong positive correlation with both single laser pulse energy and laser pulse number. Additionally, LIBS spectral analysis provides elemental results comparable to Energy Dispersive Spectroscopy (EDS), facilitating the examination of variations in Na, Ti, Fe, Mg, Ca, and C elemental contents with depth. Moreover, an enhanced iterative Boltzmann plot method is suggested for calculating the plasma temperature using 21 Fe I spectral lines and the electron density using the Fe II 422.608 nm line. The variations of these plasma parameters with laser pulse number are documented, and the results show consistent trends, confirming that the laser-induced SMC plasma adheres to local thermodynamic equilibrium. [ABSTRACT FROM AUTHOR]

This study aims to analyze the spectral properties of plasma produced from rice husk(Rh) using the laser breakdown spectroscopy (LIBS) method. The plasma generation process used the fundamental harmonic (1064 nm) of a Q-switched Nd:YAG laser. Yttrium aluminum garnet (YAG) is a man-made crystalline material. The laser fired pulses with a duration of 10 ns and a repetition rate of 6 Hz. Thus, the energy outputs achieved were 50–200 mJ at the wavelength of 1064 (nm). The silica content in the rice hulls was verified using an XRF measurement, which revealed the presence of silica in the rice hulls in a high percentage. Precise beam focusing was achieved by focusing the laser on the target material. This target material is placed within an atmospheric environment at standard pressure settings. The electron temperature was derived using the Boltzmann diagram method by harnessing experimental data for the linear properties associated with the neutral lines (Si II), (O II), and ion lines (Si I). The use of analytical methodology led to the determination of electron temperature values from 0.79 eV to 1.16 eV for the fundamental harmonic of the laser. At the same time, the electron (ne) density was determined by analyzing the Stark broadening profile associated with the neutral silica line. Furthermore, the study included an additional dimension by determining the plasma properties (electron temperature and electron density) by adjusting the laser energy on the target surface longitudinally along the path of the plasma plume. [ABSTRACT FROM AUTHOR]

Calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is successfully employed to determine the chemical composition of brass samples using the LIBS technique. The sample is irradiated with a Q-switched Nd: YAG laser with a pulse width of 5 ns to generate laser-induced plasma (LIP) on the sample surface. The time evolution spectra were recorded from the surface of the brass sample only with an accumulation of five laser shots to get one LIP spectrum. Time-resolved LIP spectra have been utilized to identify the most appropriate time window (where the plasma is optically thin and in local thermal equilibrium) suitable for CF-LIBS implementation. Stoichiometric ablation is also demonstrated for metallic brass samples with the aforementioned laser in the present study. To obtain definitive quantitative information from LIP, the characterization of the plasma, i.e., spectral line intensity, spectral line broadening, electron number density, and plasma temperature, has been analyzed in this paper. Based on two different CF-LIBS algorithms, the brass sample composition was determined and found to be in good agreement with the certified results. This paper also compares and contrasts both strategies, as well as discusses their place and importance. The results of the present manuscript illustrate the potential applicability of CF-LIBS for yielding precise and accurate compositions of brass. [ABSTRACT FROM AUTHOR]

Cherts originating from carbonate lacustrine environments have been widely exploited by Upper Palaeolithic hunter‐gatherers in the south of the Pyrenees. Archaeo‐petrographic sourcing studies have identified different potential sources but were unable to distinguish them. This study conducted geochemical characterisation of geological and archaeological lacustrine chert samples using laser‐induced breakdown spectroscopy (LIBS), and applied the supervised classification model partial least squares–discriminant analysis to LIBS spectra. The model was able to discriminate geological sources and provide predictions for the origin of a selection of chert artefacts recovered at the Middle Magdalenian level from Cova del Parco (Lleida, Spain). [ABSTRACT FROM AUTHOR]

In this work, we present studies on the effect of laser wavelengths on the laser-induced plasma characterization using a femtosecond (fs) ytterbium-doped potassium-gadolinium tungstate (Yb:KGW) laser. Plasma plumes of copper, steel, ceramics, and glass samples were induced using a multiple shot of 200 fs laser pulses with 1030 nm and 343 nm wavelengths at fixed laser fluence (10.5 J / cm 2) and analyzed using the laser-induced breakdown spectroscopy (LIBS) technique. Time-resolved fs-LIBS measurements were performed on the same set of samples and under the same experimental conditions. For the calculation of plasma parameters, the set of spectral lines of Cu(I) (for copper sample), Fe(I) (for steel sample), and Ca(I), K(I) (for glass and ceramics samples) were observed. The plasma electron temperature and density were evaluated from the Boltzmann plots and Stark-broadening profiles of the plasma spectral lines, assuming the local thermodynamic equilibrium condition. Time-resolved plasma temperature and electron density for fs-LIBS using ultraviolet (UV) and infrared (IR) laser wavelengths were analyzed and no significant dependence on fs laser wavelength was observed for any of the samples. However, for all samples the signal-to-noise ratio (SNR) significantly increased using UV laser radiation: copper (∼ 100 %), steel (∼ 300 %), glass (∼ 400 %), and ceramics (∼ 40 %). Therefore, by using a fs UV laser wavelength for laser-induced breakdown spectroscopy experiments, for certain materials the SNR and at the same time the limit of detection can be significantly enhanced. [ABSTRACT FROM AUTHOR]

The present study describes the potential use of the Laser-induced breakdown spectroscopy (LIBS) coupled with the principle component analysis (PCA) for the discrimination/analysis of the precious gold alloy has been reported. It is very hard to discriminate between the Au-Alloys using conventional LIBS and it has been suggested that the use of multivariate methods assisted LIBS could solve the problem. Gold alloys of karats 18 K, 19 K, 20 K, 22 K, and 24 K with concentrations of 75, 79, 85, 93, and 99.9% have been tested and analyzed using LIBS. Plasma was generated on the surface of the target sample by focusing Nd: YAG laser under atmospheric pressure. Time-integrated emission spectra from plasma were collected in the range of 250–870 nm. The characteristic emission lines of constituents were identified using the NIST atomic spectra database. Normalized optical emission intensities of the detected elements were used as input data for principle component analysis (PCA). Five different three-dimensional clusters were observed, that belonged to five different karats of gold, suggesting the reliability of the model for the classification of precious alloy samples. The finding from this study showed that the LIBS coupled with PCA is an effective method for the classification of gold alloys with different percentages. [ABSTRACT FROM AUTHOR]

As one of the six nuclear energy systems selected by the "Fourth Generation Nuclear Reactor International Forum", the Thorium Molten Salt Reactor (TMSR) has garnered significant attention due to its fascinating features, including excellent neutron economy, online fuel reprocessing, and reduced production of actinides. However, real-time online analysis of the nuclear elements remains a crucial technology throughout the fuel reprocessing. In this study, the femtosecond laser-induced breakdown spectroscopy (LIBS) was employed with both univariate and multivariate regression models for the quantitative analysis of Th and U elements in a graphite matrix. The concentrations of ThO 2 in six homemade samples were ranged from 4.998 to 40.012 wt % , while the concentrations of U 3 O 8 were ranged from 0.970 to 2.498 wt % . The mean relative error (MRE), root mean square error of prediction (RMSEP), root mean square error of calibration and coefficient of determination (R 2 ) were employed as indicators to evaluate the quantitative accuracy and stability of the LIBS analysis. For the univariate regress, the standard curve method was performed, utilizing a non-interferential emission line (Th II 286.99 nm) as analytical line for Th measurement. However, no suitable analysis line was found for U element. For the multivariate regression, the random forest (RF) method and partial least squares (PLS) regression method utilized three spectral regions (285.00–288.00, 330.00–370.00 and 390.00–425.00 nm) as analytical bands for ThO 2 , while two regions (380.00–389.00 and 514.00–517.00 nm) were employed for U analysis. The results suggest that the PLS regression exhibited the best performance, yielding RMSEP T h O 2 = 0.785 wt % , RMSEP U 3 O 8 = 0.135 wt % , MRE T h O 2 = 4.24 % , and MRE U 3 O 8 = 4.90 % . Therefore, the combination of LIBS with multivariate regression models exhibits significant potential as a robust in-situ analytical approach for the online fuel reprocessing in TMSR. [ABSTRACT FROM AUTHOR]

Approaches for in-situ monitoring elemental composition in the working zone during additive manufacturing (AM) with directed energy deposition are relatively underdeveloped and especially needed for processes with multiple powder delivery feeds, such as laser-based directed energy deposition. In this study, Laser-Induced Breakdown Spectroscopy (LIBS) was explored for monitoring elemental composition of an AM-sintered graded Fe-Ni alloy. Fe and Ni powder feeds were varied during Fe-Ni alloy sample building, and LIBS was used to determine gradient alloy composition, which was also verified by mapping Fe and Ni gradients along the sample build direction with an Energy-Dispersive X-ray Spectroscopy (EDS) technique. An integrated experimental and modeling approach presented in this work rapidly fits Fe and Ni peak LIBS emission data by using a physics-informed emission peak identification algorithm based on an atomic emission spectrum simulation to predict peak occurrences, locations, and significant intensities. The approach allows to considerably reduce the computational time needed for peak identification, labeling, and fitting in experimental recorded spectroscopic data. The performed LIBS experimental measurements using this approach demonstrated a 5-Hz composition analysis data rate. Changes in the Fe and Ni peak intensity areas of the compositionally graded sample were correlated to the externally measured composition using EDS, which yielded a good correlation between LIBS and EDS-measured data. The developed approaches indicate directions for obtaining elemental composition data at speeds comparable with AM process control parameter variations, striding towards in-situ non-invasive composition monitoring and closed-loop process control implementations. [ABSTRACT FROM AUTHOR]

For in situ detection via laser-induced breakdown spectroscopy (LIBS), the effect of the sample surface morphology matrix exacerbates spectral variations, leading to inaccurate and unstable analysis results, even under ideal laboratory conditions. Thus, it is essential to consider the influence of sample surface morphology on LIBS to obtain optimal detection results. Therefore, to reduce this influence, herein, we proposed spectral correction methods to correct LIBS spectra based on our previous research results on the relationship between LIBS characteristic spectral intensity and physical parameter of the sample surface morphology, where the parameter was the angle θ between the tangent of the sample surface and the horizontal direction. The results showed that the fluctuations in the corrected spectra were reduced and the relative standard deviation (RSD) was less than 10%, and the spectral intensities were close to that of the samples with a flat surface morphology. To assess the effectiveness of the proposed methods in improving the quantitative analysis accuracy, Cr, Ni, and Mn elements in standard stainless-steel samples were analyzed by partial least squares regression (PLSR). We established the model using the spectra of standard samples with a flat surface morphology as the training set, and the results showed that the accuracy was very low when the test set was the spectra of samples without a flat surface morphology, with R² of 0.781, 0.779, and 0.695 for Cr, Ni, and Mn elements, respectively. In contrast, when the test set was the corrected spectra, R2 increased to 0.950, 0.925, and 0.825 for Cr, Ni, and Mn elements, respectively, and the RMSE and MRE were reduced. When the corrected spectra of standard samples without a flat surface morphology were added to the training set, the accuracy was improved, with R² of 0.978, 0.939, and 0.929 for the three elements and their RMSE and MRE were minimum. [ABSTRACT FROM AUTHOR]

As there are distinct variations in economic value for greenish-white to white nephrites based on their geographical origin, it is crucial to develop a robust origin discrimination method for them. The reported correlation between the intensity of spectra and material properties gives us a clue that such a correlation may exist in nephrites worldwide. In this study, 364 pieces of greenish-white to white nephrite jades from different locations, including Qiemo, Qinghai, Xiuyan and Yecheng in China, South Korea, and Russia, were analyzed using laser-induced breakdown spectroscopy (LIBS). Four machine learning methods, including linear discriminant analysis (LDA), support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and an ensemble learning approach known as a voting classifier for origin discrimination were then employed. The results show a higher training accuracy of 99.81% (LDA), 94.01% (SVM), 100% (PLS-DA), 98.08% (RF), and 99.93% (voting classifier), with corresponding testing accuracies of 96.13%, 93.04%, 94.99%, 95.90%, and 99.93%, respectively. By appropriately selecting voting weights, the voting classifier effectively mitigates misclassification, achieving balanced accuracy for each origin. Therefore, the LIBS analyses could be utilized in the origin discrimination of greenish-white to white nephrite jades, offering valuable insights for accurately evaluating these gemstones, based on the successful application of various machine learning methods in the origin discrimination of nephrite jades. An integrated voting ensemble method was further introduced, providing new possibilities for rapid discrimination in diverse industries, including gemstone trading, manufacturing, archaeology, and more. [ABSTRACT FROM AUTHOR]

The geographic provenance of minerals provides key insights into a range of geologic problems, including the source of gem materials. The tourmaline supergroup is unparalleled in its ability to record and preserve extensive chemical signatures of its formational environment. To evaluate the likelihood that tourmalines of similar compositions from separate geographic localities could be differentiated, a multivariate statistical approach has been utilized on two complementary data sets. These chemical analytical data sets of copper-bearing "Paraíba" tourmaline include data sets acquired with Laser Induced Breakdown Spectroscopy (LIBS) and electron microprobe analysis (EMPA). Fifty-four samples of copper-bearing tourmalines from known source locations from Brazil (São José de Batalha of Paraíba state and the neighboring Rio Grande do Norte state), Mozambique, and Nigeria, were analyzed using LIBS with a subset of these samples analyzed by EMP. Data sets obtained by each method were evaluated with multivariate statistics (PCA, PLSR). Although the sample set is limited, sequential PLSR modeling of the spectra clearly distinguished the four localities with high success: >95% for LIBS and >87% for EMP. The statistical analyses of the two techniques, LIBS and EMP, suggest that each technique emphasizes different elements for discrimination when considered in the context of the available data. The elements Cu, Mn, Fe, Mg, Ti, Zn, K, H, Co, and V were significant in LIBS chemometric models. Statistically significant elements in EMP models were Mn, Cu, Al, Ca, K, and F. Each technique results in a robust determination for geographic provenance of tourmalines with comparable compositions. The significant distinguishing chemical elements reflect geochemical distinctions in each host environment that are imparted on the tourmaline. Multivariate statistics applied to LIBS and EMP data provide an effective tool for provenance discrimination of Paraíba tourmalines, distinguishing Brazilian-sourced samples from African-sourced materials. These data provide new methods for separating the geographic origin of minerals with very similar composition such as demonstrated here for copper-bearing tourmalines. [ABSTRACT FROM AUTHOR]

Moving the laser focus to the vicinity of the gas-liquid interface is the key point for many new enhanced and new methods to improve the quality of spectral signals in water Laser induced breakdown spectroscopy (LIBS) detection. Understanding the generation and evolution characteristics of the plasma induced by pulsed laser near the gas–liquid interface is of great significance for the establishment of evolution models and improvement of these new LIBS methods. In this paper, a set of slow horizontal flow auxiliary system is established to provide an ideal flat gas–liquid two-phase interface experimental condition. Experimental research on vertical incidence flat system was conducted using techniques such as time-resolved imaging, plasma characterization diagnosis, and spectral analysis. And the detection capabilities of the system were also tested. The characteristics and mechanisms of LIBS near the gas-liquid two-phase interface were investigated with the laser incident on the sample along the vertical direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that the shift of plasma generation position relative to the focal point results from the refraction of the laser beam entering the solution from the air and the 'interface effect' of propagation on the vertical direction. Moreover, the plasma forms only the optical power density surpasses the breakdown threshold. In this work, plasma with smaller size, rounder shape, stronger radiation, higher temperature, and higher density can be produced when the focus position is in the liquid column 0.3 mm away from the upper interface. Simultaneously, for example, the Mg ion line at 285.213 nm, the obtained spectral intensity to signal-to-background ratio reaches the maximum value, and a better spectral signal can be obtained, which is 2–4 times of other positions, and the detection limits of the elements Na, Mg, and Ca also reach the lowest level, with 1.6–2.4 times of the detection limit of other focusing positions for Mg and 1.4–1.7 times for Ca, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a streak camera system is used for obtaining the spectral images in laser-induced breakdown spectroscopy. Streak images are time-resolved, thus enabling tracking of the temporal development of the atomic and ionic emission lines from the plasma plume. To make our study more comprehensive, we have used a machine-learning approach to data analysis. We propose how to reduce the level of noise on streak images by applying the principal component analysis technique. The usual method of improving the signal-to-noise ratio by taking a large number of expositions in streak camera photon counting mode is often not practical. [ABSTRACT FROM AUTHOR]

Through elemental analysis, laser-induced breakdown spectroscopy (LIBS), a quick and effective analytical method, has enormous potential to advance agriculture. In this context, our study intends to better the fertilizer sector by utilizing LIBS's capabilities. The main objective is to make it possible to rapidly and accurately analyze the elements in frequently used fertilizers such as nitrophos (NP), diammonium phosphate (DAP), and single super phosphate (SSP). We identify all elements contained in the fertilizers using qualitative and semi-quantitative analysis utilizing a single LIBS shot by noting their matching spectral lines and peak positions. This identification is validated more thoroughly by matching peak positions to the National Institute of Standards and Technology (NIST) database. Phosphorus (P), potassium (K), iron (Fe), calcium (Ca), nickel (Ni), and aluminum (Al) are effectively recognized due to their distinct spectral fingerprints. Our findings highlight the vital need to precisely characterize fertilizer content in order to maximize agricultural yield. Furthermore, our approach presents an efficient means for rapid and precise analysis of fertilizers, offering the advantage of minimal sample requirements. [ABSTRACT FROM AUTHOR]

The aim of this work is to evaluate two quantitative methods, based on the external calibration applied in laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analysis, known as (i) analytical curve and (ii) one-point calibration, using the concept of matrix matching to quantify three potentially toxic elements (PTEs) in wood samples. These can biologically register changes in the abiotic environment and be applied to monitoring climate change or environmental toxicity. In this case, standard sample preparation was evaluated to prepare the standard pellets using Pinus taeda species as a matrix-matching concept. Six pellets of P. taeda, with different Pb, Cd, and Ba concentrations, were prepared to build the analytical curve and one-point calibration strategies. The LA-ICP-MS parameters were optimised for 206Pb, 208Pb, 112Cd, 114Cd, 137Ba, and 138Ba isotope analysis in wood samples. The two calibration strategies provided 74–110% analytical recovery from certified reference materials and similar results to those obtained by ICP-MS through the acid digestion of environmental wood samples from São Paulo City (Brazil). This demonstrated the applicability of the one-point calibration strategy in quantifying PTEs in wood samples, which could be used with environmental analyses. Differences observed between the Ba isotope results obtained via LA-ICP-MS and ICP-MS quantification were related to sampling by LA-ICP-MS and the ICP-MS sample introduction, as well as to laser matrix and transport effects because of the difference between the wood species evaluated. [ABSTRACT FROM AUTHOR]

Lead in any food is harmful even at low concentrations. In this study, a direct and highly sensitive lead analysis technique was developed for wheat flour using laser-induced fluorescence combined with laser-induced breakdown spectroscopy. Wheat flour was pressed into small pellets and ablated by a low-energy ultraviolet 266-nm laser. A tunable dye laser constructed in our laboratory was used to resonantly excite the lead. The optimized interpulse time delay was 400 ns. A calibration curve was constructed and the detection limit for lead was 73.8 ppb. This method could be used to directly and sensitively analyze wheat flour for trace concentrations of lead. [ABSTRACT FROM AUTHOR]

The rapid identification and classification of metal garbage has been experimentally investigated. By combining laser-induced breakdown spectroscopy (LIBS) and machine learning, metal garbage can be effectively identified through spectral analysis. In this work, a novel method for metal garbage classification was developed, and a LIBS system was self-developed. As an example of metal recycling, five types of metal were adopted. Several characteristic lines of Al, W, Fe, Cu, Sn, Pb, and C were identified. For a more effective classification, principal component analysis was conducted to reduce the dimension of the spectra. Samples after the dimension reduction were classified by using K-nearest neighbors, and five types were obtained, exhibiting a final classification accuracy of 97.18%. Moreover, a mathematical model of the linear formulas between spectrum and concentration was established to achieve quantitative analysis with Fe taken as an example, laying the foundation for more refined classification. [ABSTRACT FROM AUTHOR]

The identification and determination of elements from the Indonesian coral skeleton are required to characterize anthropogenic activities. To this end, various spectroscopy methods were used for elemental analysis including underwater laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence spectroscopy (XRF), and inductively coupled plasma – optical emission spectroscopy (ICP-OES). The results show that the LIBS was able identify the major elements Ca, Mg, and Sr. Using ICP-OES, all elements including major, minor, and trace elements were quantitatively determined. The results show that coral skeletons from Karimunjawa contain the highest concentrations of trace elements, which may be due to expanded human activities. [ABSTRACT FROM AUTHOR]

Following the successful demonstration of machine learning (ML) models for laser induced breakdown spectroscopy (LIBS) adaptation in fusion reactor fuel retention monitoring using synthetic data [Gąsior et al., Spectrochim. Acta, Part B 199, 106576 (2023)], this study focuses on implementing operability on experimental data. To achieve this, Simulated Eperimental Spectra (SES) data are generated and used for validation of a chemical composition estimation model trained on dimensionally reduced synthetic spectral data (DRSSD). Principal component analysis is employed for dimensionality reduction of both SES and DRSSD. To simulate real experimental conditions, the synthetic data, generated by a dedicated tool [M. Kastek (2022), "SimulatedLIBS," Zenodo. http://dx.doi.org/10.5281/zenodo.7369805] is processed through the transmission function of a real spectroscopy setup at IPPLM. Separate and optimized artificial neural network models are implemented for conversion and chemical composition estimation. The conversion model takes DR-SES as features and DR-SSD as targets. Validation using converted SES data demonstrates chemical composition predictions comparable to those from synthetic data, with the highest relative uncertainty increase below 40% and a normalized root-mean-square error of prediction below 7%. This work represents a significant step toward adapting ML-based LIBS for fuel and impurity retention monitoring in the walls of next-generation fusion devices. [ABSTRACT FROM AUTHOR]

We propose a nonlinear transient coupling model to study the plasma dynamics during the interaction between ultrashort laser pulses and water. We conduct a quantitative characterization of the transient optical properties, energy deposition, and dense plasma dynamics in water with near-infrared ultrashort laser pulses by simulating the spatiotemporal coupling of the laser field with the plasma while calculating the time-varying relative permittivity. The results show that the free electron density in the dense plasma exceeds ≈ 1.0 × 10 26 m − 3 , the plasma will move in the reverse direction of the laser pulse propagation, and the velocity is related to the incident laser intensity. An empirical model is established to quantify this reverse movement of dense plasma in the laser field taking into account the energy deposition. We also validate our coupling model by comparing the breakdown thresholds with experimental results and find excellent agreement. [ABSTRACT FROM AUTHOR]

Spatial confinement effects offered by a blocker on the laser-induced plasma parameters of titanium (Ti) are evaluated using the Optical Emission Spectroscopy technique. Nd:YAG (1064 nm, 10 ns) laser is used as an irradiation source. To observe the spatial confinement effects, an Al blocker at different distances of 4, 6, and 8 mm from the target is placed along the plume path. All the measurements are performed under the Ar environment at different pressures. It is observed that with increasing laser irradiance plasma parameters such as excitation temperature (Te) and electron number density (ne) increase, whereas it is vice versa true for increasing blocker distances. Without the blocker, the maximum values of Te and ne are about 7000 K and 1.4 × 1018 cm−3, respectively, at an Ar pressure of 50 Torr. A significant increase in emission intensity along with Te ≈ 9810 K and ne ≈ 2.2 × 1018 cm−3 is achieved in the presence of blocker. The results show that spatial confinement is responsible for the enhancement of Te and ne, which is attributed to the increased collisional frequency of plasma species after compression by shockwaves. The ablation pressure and shock pressure are also analytically evaluated and vary from 0.15 to 0.25 GPa and from 0.1 to 0.2 GPa, respectively, with increasing laser irradiance. With increasing blocker distances from 4 to 8 mm, the work done by reflected shockwaves to compress the plume varies from 0.02 to 0.002 mJ. [ABSTRACT FROM AUTHOR]

We report here the effect of the magnetic field on plasma parameters and the surface structuring of the Cu alloy after fs laser irradiation. A Ti:Sapphire (800 nm, 35 fs, 1 KHz) laser is employed at various irradiances (0.011–0.117 PW/cm2) to generate plasma. A Transvers Magnetic Field (TMF) of strength 1.1 T is employed for plasma confinement. All the measurements were performed with and without TMF. The Cu plasma parameters, i.e., excitation temperature (Texc) and electron number sensity (ne), determined by laser-induced breakdown spectroscopy analysis, are higher in the presence of TMF. This magnetic field confinement of Cu plasma was studied analytically by evaluating thermal beta (βt), directional beta (βd), confinement radius (Rb), and diffusion time (td). To correlate Cu-alloy plasma parameters with surface modifications, field emission scanning electron microscope analysis is performed. It reveals the formation of low-spatial-frequency laser-induced periodic surface structures (LIPSSs) and high-spatial-frequency LIPSSs, along with agglomers and nano-rims formation. Distinct and well-defined structures are observed in the presence of a magnetic field. It is concluded that controlled surface structuring can be achieved through magnetic confinement, which enhances key plasma parameters. The technique has the potential for enhancing the fabrication of nano-gratings and field emitters, where spatial uniformity is critically important. [ABSTRACT FROM AUTHOR]

This article reports on an advanced level physical laboratory experiment designed for college level undergraduate education and for scholars who need specialized training on using and interpreting Laser-Induced Breakdown Spectroscopy. The technical principle, experimental operation and sample preparation of Laser-Induced Breakdown Spectroscopy are introduced in detail. A presentation and discussion of the use of Laser-Induced Breakdown Spectroscopy in the traceability of four common samples is emphasized. Combining Laser-Induced Breakdown Spectroscopy with Machine Learning, two distinct datasets are constructed through the extraction of spectral features. Dimensionality reduction of spectral data is performed using Linear Discriminant Analysis, while the Random Forest model is employed for provenance classification. Finally, the interpretability of the Random Forest model is leveraged to explore the contributions of different spectral elements to provenance tracing. Results demonstrated the system's effectiveness in not only accurately identifying ash types but also in elucidating the influential chemical components, offering significant implications for material analysis and environmental monitoring. On an educational standpoint, this paper will allow any reader, in particular, undergraduate and graduate students, to gain a better understanding of the theory and practice of Laser-Induced Breakdown Spectroscopy and machine learning. [ABSTRACT FROM AUTHOR]

• Samples of thin gold and black resin were found in an ancient Egyptian tomb. • LIBS is used to analyze black resin and gold in embalming remains. • Spectroscopic results revealed butemen and not pure gold. • EDX measurements of the same samples validated the LIBS results. Laser-induced breakdown spectroscopy (LIBS) has recently been considered one of archaeology's most preferred analytical techniques because of its simplicity; it does not need sample preparation, is fast, is a quasi-nondestructive analytical technique, and is cost-effective. Besides, LIBS can perform stratigraphic measurements, which are of significant interest in cultural heritage samples. Such pros facilitate utilizing LIBS in situ, e.g., in museums and excavation sites. In the present work, LIBS has been used to analyze black resin remains and gold fragments used in mummification and collected from the Ptahemwia tomb in the vicinity of Djoser's Step Pyramid at Sakkara. The IR (1064 nm) and the UV (355 nm) laser wavelengths have been used in the LIBS measurements. The results revealed both samples' emission line intensity dependence on the laser wavelength. In this regard, elements such as Na, Ca, Mo, and CN (molecular band) for black resin and Au, Ag, and Cu for gold samples were detected as significant elements. It has been found that the detection sensitivity achieved by the LIBS technique was higher when using the UV laser. This is crucial in detecting rare earth elements REE (Y, La) and/or minor elements (Nb, Zr) in the samples under study. Furthermore, the energy-dispersive X-ray (EDX) analysis has been used to validate the LIBS results for the same samples. In agreement with what is reported in the literature, the LIBS and the EDX spectroscopic results showed that the black resin investigated in the present study is bitumen in its composition. [Display omitted] [ABSTRACT FROM AUTHOR]

The detection of lanthanum (La) is crucial for the extraction of rare earth minerals. As a real-time, in-situ detection technique, laser-induced breakdown spectroscopy (LIBS) is adversely affected by severe matrix effects, leading to the poor performance of univariate analysis in La analysis in geological samples. Here, a multivariate regression model based on bidirectional long short-term memory (BiLSTM) neural network integrated with LIBS (BiLSTM-LIBS) is proposed to enhance the quantitative analysis of La in rare earth minerals. To demonstrate the superiority of this approach, we compare the results with traditional univariate analysis techniques. The linear correlation coefficient is increased from about 0.969 to 0.999 by the BiLSTM-LIBS model, while the RMSEC is reduced from about 1.294 to 0.491 ppk. The mean relative error for test data is 5.85%, and the root means square error of prediction is 0.397. These results indicate that the combination of LIBS technology and BiLSTM neural network effectively reduces the impact of matrix effects, providing an available route for accurate determination of La in rare earth minerals. [ABSTRACT FROM AUTHOR]

The illegal timber trade has significant impact on the survival of endangered tropical hardwood species like Dalbergia spp. (rosewood), a world‐wide protected genus from the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Due to increased threat to Dalbergia spp., and lack of action to reduce threats, port of entry analysis methods are required to identify Dalbergia spp. Handheld laser‐induced breakdown spectroscopy (LIBS) has been shown to be capable of identifying species and establishing provenance of Dalbergia spp. and other tropical hardwoods, but analysis methods for this work have yet to be investigated in detail. The present work investigates five well‐known algorithms—partial least squares discriminant analysis (PLS‐DA), classification and regression trees (CART), k‐nearest neighbor (k‐NN), random forest (RF), and support vector machine (SVM)—two training/test set sampling regimes, and data collection at two signal‐to‐noise (S/N) ratios to assess the potential for handheld LIBS analyses. Additionally, imbalanced classes are addressed. For this application, SVM and RF yield near identical results (though RF takes nearly 100 longer to compute), while the S/N ratio has a significant effect on model success assuming all else is equal. It was found that forming a training set with replicate low S/N analyses can perform as well as higher precision training sets for true prediction, even if the predicted samples have low signal to noise! This work confirms handheld LIBS analyzers can provide a viable method for classification of hardwood species, even within the same genus. The illegal timber trade has significant impact on the survival of endangered tropical hardwood species like Dalbergia spp. Handheld laser‐induced breakdown spectroscopy has been shown capable of identifying species and establishing provenance of tropical hardwoods, including Dalbergia. This work investigates collection strategies at two S/N ratios and balanced classed, across two training/test set sampling regimes, five established classification algorithms for 60 total analyses. It was found that support vector machines and random forests yield κ > 0.9 and that more data collected at higher S/N can yield better true prediction. [ABSTRACT FROM AUTHOR]

The document is a contents list for the Journal of Analytical Atomic Spectrometry. It includes the ISSN, cover image, and inside cover image for the current issue. The contents list also provides information on various articles and papers featured in the journal, covering topics such as atomic spectrometry updates, in situ online detection of atmospheric particulate matter, high-sensitivity analysis of trace elements in water, and other related subjects. The journal aims to connect the world with the chemical sciences and is published by The Royal Society of Chemistry. [Extracted from the article]

Femtosecond laser-ablation spark-induced breakdown spectroscopy (fs-LA-SIBS) and out-of-bag random forest regression (OOB-RFR) were developed for accurate quantitative analysis of the elements manganese (Mn), chromium (Cr), and nickel (Ni) in steel alloys. A femtosecond laser operating at 1 kHZ was used as the laser ablation source and a spark discharge unit was utilized to enhance the peak intensity of atomic emission. The characteristic lines of Mn, Cr, and Ni elements in steel alloys were determined using the NIST database. The two hyperparameters ntree and mtry of RFR were optimized through OOB error, and the OOB-RFR model was obtained. In the experiment, the predictive performance of OOB-RFR, support vector machine (SVM) regression, and partial least squares regression (PLS) on steel alloy spectral data was compared and analyzed. The results indicate that the OOB-RFR model exhibits lower computational iterations and higher performance than other models in regression prediction of Mn, Cr, and Ni elements. In the OOB-RFR model, the root mean square error (RMSE), the average relative error (MRE) and the coefficient of determination (R2) of Mn, Cr, and Ni elements in the training samples were 0.0051, 0.0018 and 0.9976, respectively, and the RMSE, MRE and R2 of the three elements in testing samples were 0.0018, 0.0009 and 0.9369, respectively. Therefore, the combination of the fs-LA-SIBS technique and OOB-RFR has great potential in the rapid determination of elements in steel and even in the metallurgical field. [ABSTRACT FROM AUTHOR]

Detection of heavy metals in environmental water is important in addressing water pollution. In this study, a simple and effective strategy was proposed that utilized femtosecond laser-induced breakdown spectroscopy (fs-LIBS) to investigate the effect of titration number in dry droplet pretreatment on an Al substrate for detecting trace elements in aqueous solutions. This method aimed to enhance signals for highly sensitive detection of trace metal elements in liquid samples. Cr, Pb, and Cu were detected in water solutions with 1, 2, and 4 titration numbers. The limit of detection (LOD) was calculated for Cr, Pb, and Cu at 1, 2, and 4 titrations, respectively. The LODs for Cr, Pb, and Cu obtained by 4 titration numbers were 0.19, 1.40, and 0.24 ng mL−1, respectively. The calculated R2 for Cr, Cu was > 0.99 and for Pb > 0.98, which were satisfactory results and demonstrated the feasibility of using increased titration times in dry droplet pretreatment for analyzing liquid samples. Applying increased titration numbers in high-performance signal enhancement undoubtedly elevates the sensitivity of fs-LIBS analysis methods to a new level. [ABSTRACT FROM AUTHOR]

This study explores the application of laser-induced breakdown spectroscopy (LIBS) to classify steel samples, which gives a novel idea of utilizing the matrix effect. In engineering applications, carbon-steel, which has the same elemental composition, is usually processed into different microstructures through heat treatment processes. It results in the steel having different element distribution characteristics at the microscopic scale, and is considered to be one of the reasons for the matrix effect in the LIBS field. In this study, the matrix effect of LIBS spectra is used as the feature for microstructure classification of carbon-steel. According to this idea, our study introduces a rapid classification method of LIBS spectra using the random projection (RP) technique in convolutional neural networks (CNNs), which has achieved the accuracy of 99% in 25 seconds. The experimental results show that the dimensionality reduction without spectral preprocessing by the RP-CNN method enhances the impact of matrix effect. This study provides an efficient deep learning method for similar LIBS spectra obtained from steel samples with different microstructures, which has great potential in the LIBS application of engineering material evaluation. [ABSTRACT FROM AUTHOR]

The main objective of this review is to provide a brief overview of some new directions and trends in the field of atmospheric particulate matter detection by laser-induced breakdown spectroscopy (LIBS) in recent years. Particulate matter, which is tiny solid or liquid particles suspended in the air, is a major form of air pollution and has important implications for both air quality and human health. Realizing real-time online detection of particulate matter is of great significance. LIBS is an atomic emission spectroscopy technique that uses a laser to excite a sample to produce plasma, and the composition and content of elements are determined by analyzing the resulting spectrum. The rapid detection and multi-element analysis of LIBS show its unique advantages in the detection of atmospheric particulate matter. To illustrate the new progress of LIBS technology in the field of atmospheric particulate matter detection, several typical cases are listed in this review, including liquid aerosol monitoring, isotope detection, indoor particulate matter detection, and industrial scene particulate matter detection. [ABSTRACT FROM AUTHOR]

Serum contains rich elemental information, and the elemental analysis of the serum using laser-induced breakdown spectroscopy (LIBS) can help with the diagnosis and treatment of cancer. In this work, serum specimens from breast cancer patients were used as samples, and the elements Mg, Ca, and K were analyzed using LIBS. Silver nanoparticles (Ag NPs) were introduced to enhance spectral emission intensities, and this technique is known as nanoparticle-enhanced LIBS (NELIBS). An Ag NP-coated filter paper (Ag NP paper) substrate was prepared and was compared with silicon and aluminum substrates for NELIBS analysis. The Ag NP paper substrate showed lower spectral intensity variances and better elemental distribution uniformity due to the reduced coffee-ring effect compared with silicon and aluminum substrates. The enhanced effect of the Ag NP paper was optimized by adjusting serum volume and Ag NPs concentration. It was found that Mg, Ca, and K required different optimal conditions for spectral enhancement. The highest enhancement factors (EF) for Mg, Ca, and K were 1.85, 1.76, and 3.10, respectively. The electron temperature (Te) and electron number density (Ne) of NELIBS plasmas were measured using the Boltzmann plot and Stark broadening methods and compared with those of the normal LIBS plasmas. The Te and Ne of the NELIBS and normal LIBS samples were generally comparable with each other. Higher Ag NP concentrations led to lower Te values for NELIBS plasmas. [ABSTRACT FROM AUTHOR]

The impact of oxidation chemistry on the emission characteristics and spatial structure of laser-produced Ce metal plasmas was investigated using laser-induced breakdown spectroscopy (LIBS) and time-resolved fast-gated imaging employing narrowband optical filters. Images of the plasma emission show that CeO coexists with atomic species in the periphery and vortex ring of the plasma plume. Image processing was also applied to combine independent monochromatic images of the plasma emission into a single merged image, culminating in a timelapse on the spatiotemporal evolution of atomic and molecular species within the plasma plume. The formation of CeO species was observed to proceed faster for plasmas generated in atmospheres containing larger concentrations of oxygen based on ratios of CeO-to-atomic emission intensities. These same ratios were shown to plateau and decrease at later times (≥25 μs), potentially indicating the depletion of CeO number densities in the plasma as the monoxide undergoes reactions to form higher polyatomic oxides. Altogether, these results provide fundamental insights into the chemical dynamics and intermixing between plasma-gas species in laser ablation cerium plasmas, advancing our understanding on optical signatures of nuclear-relevant materials to enable in-field measurement capabilities. [ABSTRACT FROM AUTHOR]

The synergy enhancement of magnetic-spatial confinement using a bar magnet pair was applied to fiber-optic laser-induced breakdown spectroscopy (FO-LIBS). By studying the plasma morphology and emission spectroscopy, the plasma temporal behaviors under free expansion, spatial confinement, and magnetic-spatial confinement have been carefully compared. Temperature distribution and pixel-to-pixel relative standard deviation (RSD) of plasma morphology under the combined effect of magnetic field and the reflected shock wave on fiber-optic laser-induced plasma were studied for the first time. The magnetic field was found to deform the plume mainly at the left and right sides, and the two high-intensity areas in FO-LIBS plasma rose from 8.7% to 13.8% and resisted being compressed together after the shock wave reflected. The magnetic-spatial confinements also demonstrated better enhancements in emission spectra than only spatial confinement, and the magnetic field tended to give around 20% and 50% additional enhancement on line intensity at the early and later stages of evolution, respectively. Besides, the self-reversed effect was significantly reduced in magnetic-spatial confinement, which can be explained by more evenly distributed temperatures calculated by spatially resolved spectra. Pixel-to-pixel RSD distribution of plasma morphology was studied, and it was found that the area of more fluctuated parts was reduced by 40% and concentrated on the left and right sides of the plasma in the magnetic field at the early stage. After the shock wave passed through, the two high-intensity areas were observed to fluctuate less due to the compression of the shock wave. Furthermore, shot-to-shot spectra fluctuation was also reduced by up to 50% under the magnetic-spatial confinement, which is consistent with the results of plasma morphology fluctuation. This study provides evidence of plasma emission signal enhancement and stabilization under magnetic-spatial confinement in the FO-LIBS system. [ABSTRACT FROM AUTHOR]

Occupational and environmental exposures, particularly those related to urban and suburban atmospheres, are increasingly linked to a range of pulmonary diseases. While diagnostic methods for these diseases are well established, analytical tools for assessing elemental contamination in lung tissue remain underutilized. This study introduces a novel framework based on laser‐induced breakdown spectroscopy (LIBS) for the in situ quantification of elemental titanium (Ti) in lung tissues from both animal models and human specimens. Rigorous validation is conducted using animal models exposed to TiO2 P25 nanoparticles and a comparative analysis with inductively coupled plasma mass spectrometry. The novel quantitative metric Svalue$S_{\text{value}}$ demonstrates robust correlation with elemental concentrations, expanding LIBS utility to volumetric organ analysis. This validated methodology is subsequently applied to human lung specimens preserved in paraffin. The research holds significant promise as a diagnostic tool for assessing exposure levels to environmental or occupational hazards, thereby offering valuable contributions to the fields of toxicology and respiratory medicine. [ABSTRACT FROM AUTHOR]

A support vector machine regression (SVMR) model that integrates data preprocessing was devised for the determination of Mo in molybdenum ores. To eliminate the negative effects of spectral fluctuations and improve the computational efficiency, the model processes original measurements through the following steps: denoising via wavelet transform smoothing (WTS), debaselining via adaptive iteratively reweighted penalized least squares (airPLS), main characteristic peak extraction, elimination of abnormal spectral data via the box plot method, and normalization via min-max scaling. In this study, 255 characteristic peaks were selected from 17,916 spectral datasets, and the total number of datasets after removing the outliers was 491. The calibration curve approach was used to establish a univariate model. The limit of detection of Mo was 0.0080 wt%. The R2 value of the calibration curve was 0.6675. Linear regression (LR) and SVMR were used to establish a multivariate analysis model. Compared to that of the calibration curve approach, the determination coefficients (RP2) of LR and SVMR increased from 0.8034 to 0.9859 and 0.9941, respectively. The range of relative errors (REP) decreased from 0.21%–67.66% to 0.48%–18.46% and 2.65%–7.44%, respectively; the mean absolute error (MAEP) was decreased from 0.0173 wt% to 0.0048 and 0.0039 wt%, respectively; and the root mean square error (RMSEP) decreased from 0.0243 wt% to 0.0065 and 0.0042 wt%, respectively. These results indicate that the integration of SVMR with data preprocessing is suitable for the determination of Mo in molybdenum ores. [ABSTRACT FROM AUTHOR]

The content of chromium (Cr) affects the mechanical and wear resistance of steel. Hence, the determination of Cr in steel is of great significance to determine the quality. In this study, a new method based on laser-induced breakdown spectroscopy (LIBS) combined with extreme random tree (ERT) is reported to determine Cr in steel. First, the Cr I 425.43 nm line was selected for univariate quantitative analysis. Next, multivariate analysis of Cr was performed using partial least squares regression (PLSR), random forest (RF), and ERT. The abilities of the models for the determination were validated by the fitting coefficient (R2), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and average relative error (ARE). The R2, RMSEC, RMSEP, and ARE values of ERT were 0.9984, 0.0274 wt.%, 0.0299 wt.%, and 2.43%, respectively. Compared with the univariate model, PLSR, and RF models, the R2 of ERT increased by 0.1317, 0.0306, and 0.013, respectively; RMSEC decreased by 0.0987, 0.0955, and 0.0174 wt.%; RMSEP decreased by 0.1463, 0.0876, and 0.002 wt.%; and ARE decreased by 17.88%, 16.98%, and 5.95%, respectively. The results show that combining LIBS with the ERT model for multivariate analysis improves the elemental analysis of steel. [ABSTRACT FROM AUTHOR]

The modal characteristics of dual-element coupled vertical cavity surface emitting laser (VCSEL) arrays are analyzed numerically and experimentally. A photonic crystal pattern etched into the top mirror optically defines the two elements of the array that are independently electrically biased. Using a two-dimensional complex waveguide analysis, we incorporate the effects of varying temperature and electron plasma-induced index suppression arising from asymmetric injection. The simulations are compared to experimental characterization of output power, lasing spectra, and far-field beam profile as a function of the two independent injection currents. Three distinct operating regimes are identified for the arrays: single independent local mode; a region of two modes that are primarily localized into a specific cavity; and a region of two supermodes whose fields extend across both elements. This analysis provides a physical intuition for the behavior of the dual-element coupled VCSEL array across its full operating range for emerging applications. [ABSTRACT FROM AUTHOR]

Multimodal spectral imaging offers a unique approach to the enhancement of the analytical capabilities of standalone spectroscopy techniques by combining information gathered from distinct sources. In this manuscript, we explore such opportunities by focusing on two well-known spectral imaging techniques, namely laser-induced breakdown spectroscopy, and hyperspectral imaging, and explore the opportunities of collaborative sensing for a case study involving mineral identification. In specific, the work builds upon two distinct approaches: a traditional sensor fusion, where we strive to increase the information gathered by including information from the two modalities; and a knowledge distillation approach, where the Laser Induced Breakdown spectroscopy is used as an autonomous supervisor for hyperspectral imaging. Our results show the potential of both approaches in enhancing the performance over a single modality sensing system, highlighting, in particular, the advantages of the knowledge distillation framework in maximizing the potential benefits of using multiple techniques to build more interpretable models and paving for industrial applications. [ABSTRACT FROM AUTHOR]

Effective cleaning of tin contamination on the collecting mirrors in extreme ultraviolet source is one of the key techniques to improve throughput and cost performance of extreme ultraviolet lithography. Hydrogen radicals produced in hydrogen plasma that is induced by wideband extreme ultraviolet radiation are expected to be utilized for in situ tin contamination cleaning in extreme ultraviolet sources. In this Letter, we clarified absolute density and cleaning ability of the hydrogen radicals produced by intense extreme ultraviolet pulse through ground state population density measurement by laser-induced fluorescence technique. The experimentally obtained radical parameters coincided well with simulation results and collisional radiative model. It was found that the extreme ultraviolet induced plasma was in quasi-steady state with abundant amount of hydrogen radicals in ground state. Further, it was found that the in situ tin contamination cleaning in extreme ultraviolet lithography source would become more practical with increase in operational parameters, such as extreme ultraviolet emission intensity, gas pressure, and radical production cross section. [ABSTRACT FROM AUTHOR]