Laser-induced breakdown spectroscopy (LIBS), part II: review of instrumental and methodological approaches to material analysis and applications to different fields

Blank sample denoising algorithm (BSDA): An effective spectral noise reduction in water sample LIBS detection

Laser-induced breakdown spectroscopy (LIBS), as an elemental composition analysis technique, has many unique advantages and great potential for applications in water detection. However, the quality of LIBS spectral signals, such as signal-to-noise ratio and stability, is often poor due to the matrix effects of water, limiting its practical performance. To effectively remove the inherent weak radiation in experimental spectral data that can be easily mistaken for noise, this paper proposes a denoising algorithm for processing spectral data using a self-built blank sample spectral database of deionized water samples, and designs a complete data processing workflow. It includes steps such as blank sample data screening, internal standard correction, blank sample correction, and spectral smoothing. Against the backdrop of marine applications, experimental spectral data for target elements Na, Mg, Ca, K, Sr, and Li were processed with this algorithm. The results show that after algorithm processing, the spectral quality was significantly improved, with the signal-to-noise ratio and detection limits of various elements improved by at least one order of magnitude. The signal-for Li increased by up to 36 times, and the detection limit for K decreased by up to 25.2 times. Additionally, tiny spectral peaks that could not be observable in the original spectral data could be effectively extracted after processing. From a technical implementation perspective, the database establishment and data process are simple and practical, with universal applicability. Therefore, this method has good potential and wide foregrounds in many other water sample LIBS detection technologies.

Enhancing biomarker detection sensitivity through tag-laser induced breakdown spectroscopy with NELIBS

Nanoparticle-enhanced laser-induced breakdown spectroscopy and Tag-LIBS are two approaches that have been shown to significantly enhance LIBS sensitivity and specificity. In an effort to combine both of these approaches, we have initiated a study on the effect of the presence of Silver nanoparticle concentrations on Europium (Eu) and Ytterbium (Yb) LIBS signals. These elements are part of metal-loaded polymers conjugated to antibodies. We observe a signal enhancement of the emission lines of about 10 and 12 times for the Europium and Ytterbium lines. This study shows that Europium and Ytterbium are enhanced differently; Europium shows enhancement for both neutral and ionized species while the Ytterbium shows enhancement only for ionized species. Additionally, we found that NPs at 0.1 mg/mL and 0.05 mg/mL achieved maximum enhancement for Eu and Yb, respectively. Based on our findings, the temperature and electron density of Eu and Yb are not significantly different for NPs concentrations, but the total signal intensity is significantly higher for optimum NP concentrations for both Eu and Yb.

Comparison of single and double pulse laser-induced breakdown spectroscopy for the detection of biomolecules tagged with photon-upconversion nanoparticles

BACKGROUND

Laser-induced breakdown spectroscopy (LIBS) is a well-recognized analytical technique used for elemental analysis. This method is gaining considerable attention also in biological applications thanks to its ability for spatial mapping and elemental imaging. The implementation of LIBS in the biomedical field is based on the detection of metals or other elements that either naturally occur in the samples or are present artificially. The artificial implementation of nanoparticle labels (Tag-LIBS) enables the use of LIBS as a readout technique for immunochemical assays. However, one of the biggest challenges for LIBS to meet immunoassay readout standards is its sensitivity.

RESULTS

This paper focuses on the improvement of LIBS sensitivity for the readout of nanoparticle-based immunoassays. First, the LIBS setup was optimized on photon-upconversion nanoparticle (UCNP) droplets deposited on the microtiter plate wells. Two collection optics systems were compared, with single pulse (SP) and collinear double pulse (DP) LIBS arrangements. By deploying the second laser pulse, the sensitivity was improved up to 30 times. The optimized SP and DP setups were then employed for the indirect detection of human serum albumin based on immunoassay with UCNP-based labels. Compared to our previous LIBS study, the detection limit was enhanced by two orders of magnitude, from 10 ng mL-1 to 0.29 ng mL-1. In addition, two other immunochemical methods were used for reference, based on the readout of upconversion luminescence of UCNPs and absorbance measurement with enzyme labels. Finally, the selectivity of the assay was tested and the practical potential of Tag-LIBS was demonstrated by the successful analysis of urine samples.

SIGNIFICANCE AND NOVELTY

In this work, we improved the sensitivity of the Tag-LIBS method by combining new labels based on UCNPs with the improved collection optics and collinear DP configuration. In the instrumental setup optimization, the DP LIBS showed better sensitivity and signal-to-noise ratio than SP. The optimizations allowed the LIBS readout to surpass the sensitivity of enzyme immunoassay, approaching the qualities of upconversion luminescence readout, which is nowadays a state-of-the-art readout technique.

Study on laser-induced breakdown spectroscopy in high-pressure helium gas environment for deep ocean applications

Laser-induced breakdown spectroscopy (LIBS) has gained wide acceptance as an in situ detection technique for elements. However, in deep-sea applications, the sensitivity of LIBS detection will be reduced due to the high-pressure environment and the nature of water. To address the negative effects of high-pressure water, this study used the method of draining the water from the sample surface by passing high-pressure helium gas, which allowed the plasma excitation environment to be converted from high-pressure water to high-pressure gas. The available spectral signals of solid samples at 60 MPa gas pressure were obtained for the first time, and the peak intensity and spectral broadening of the spectral lines at different pressures were analyzed for comparison. We found a nonlinear decrease in the spectral intensity and a gradual increase in the spectral broadening during the pressure increase. We also investigated the effect of laser energy on the intensity and width of the spectral lines in a high-pressure helium environment and found that increasing the laser energy in a high-pressure environment enhanced the spectral intensity and that the change in laser energy almost did not affect the line width. Finally, by observing the plasma images at different pressures with different energies, this study found that the laser penetrated the high-pressure helium gas in advance and leaved a column of light in the gas, and the plasma was slowly made smaller as the ambient pressure increases. This finding explained the cause of laser energy loss and demonstrated that the LIBS signal intensity can be improved by increasing the laser energy and shortening the laser transmission distance in a high-pressure gas environment.

Laser-Induced Plasmas of Plutonium Dioxide in a Double-Walled Cell

Plutonium research has been stifled by the significant number of administrative controls and safety procedures, space and instrumentation limitations in radiological gloveboxes, and the potential for personnel and equipment contamination. To address the limited number of spectroscopic studies in Pu-bearing compounds in the current scientific literature, this work presents the use of double-walled cells (DWCs) in "clean" buildings/laboratories as an alternative to research in radiological gloveboxes. This study reports the first laser-induced breakdown spectroscopy (LIBS) experiments of a PuO2 pellet contained within a DWC, where the formation of elemental (atomic and ionic) species as well as the evolution from elemental to molecular products (PuxOy) was measured. Raman spectroscopy was also used to characterize the surface of the ablated pellet and the particulates deposited on the window of the inner cell. The full width half-maximum of the T2g band enabled us to obtain an estimate of the temperature at the pellet surface after the ablation pulse and the particulates based on the crystal lattice disorder. Particulates deposited on the window of the DWC during laser ablation were characterized using scanning electron microscopy, where molten irregular particulates and spheroids were observed. This exciting research conducted in a DWC describes our initial attempts to incorporate LIBS in the arsenal of spectroscopic tools for nuclear forensics applications.

Self-Calibrated Laser-Induced Breakdown Spectroscopy for the Quantitative Elemental Analysis of Suspended Volcanic Ash

Real-time analysis of fine ash in volcanic plumes, which represent magma fragments expelled from the crater during explosive eruptions, is a valuable tool for volcano monitoring and hazard assessment. To obtain the chemical characterization of the juvenile pyroclastic material emitted in volcanic plumes, many analytical techniques can be used. Among them, laser-induced breakdown spectroscopy (LIBS) is the one that can most easily be adapted to advanced applications in extreme environments. In this paper, LIBS experiments based on self-calibrated approaches are used to determine the elemental composition of suspended volcanic ash. To simulate the conditions of dispersed volcanic ash in the atmosphere, different sizes of volcanic ash samples are suspended in the air by laser-induced shockwaves in a dedicated chamber, and a parametric study is carried out to establish the optimal experimental conditions for recording usable plasma emission spectra for each ash size. The quantitative analysis is performed using a self-calibrated analytical method, including calibration-free LIBS, which is based on the calculation of the spectral radiance of a uniform plasma in local thermodynamic equilibrium. The method accounts intrinsically for self-absorption since it modifies the intensity of spectral lines and thus leads to an underestimation of the elemental fraction. An intensity calibration of the spectra based on the measurements of Fe lines intensities was also used in this work to deduce the apparatus response from the spectrum itself and avoid the use of standard calibration lamps. Results demonstrate the potential of real-time measurements of elemental fractions in volcanic ash with good agreement with the literature composition.

Plasma parameters correction method based on plasma image-spectrum fusion for matrix effect elimination in LIBS

Matrix effect is one of the obstacles that hinders the rapid development of laser-induced breakdown spectroscopy (LIBS), and it is currently a hot, challenging, and focal point in research. To eliminate the matrix effect, this study proposed a plasma parameters correction method based on plasma image-spectrum fusion (PPC-PISF). This method corrects the total number density, plasma temperature, and electron number density variations caused by matrix effect using effective features in plasma images and spectra. To verify the feasibility of this method, experiments were conducted on pressed and metal samples, and the results were compared with those corrected by image-assisted LIBS (IA-LIBS). For the pressed samples, after correction by PPC-PISF, the R2 of the calibration curves all improved to above 0.993, the average root-mean-square error (RMSE) decreased by 41.05%, and the average relative error (ARE) decreased by 59.35% evenly in comparison to IA-LIBS. For the metal samples, after correction by PPC-PISF, the R2 of the calibration curves all increased to above 0.997. Additionally, the RMSE decreased by 29.63% evenly, the average ARE decreased by 38.74% compared to IA-LIBS. The experimental results indicate that this method is an effective method for eliminating the matrix effect, promoting the further development of LIBS in industrial detection.

CF-LIBS based elemental analysis of Saussurea simpsoniana medicinal plant: a study on roots, seeds, and leaves

The plant Saussurea Simpsoniana, which has been used in traditional medicine for its biocompatibility and abundant nutrients, offers a wide range of remedies. Local communities effectively utilize medicines derived from the plant's roots to treat various ailments such as bronchitis, rheumatic pain, and abdominal and nervous disorders. In this study, we present an elemental analysis of the chemical composition (wt%) of this medicinal plant using the laser-induced breakdown spectroscopy (LIBS) technique. In the air atmosphere, an Nd:YAG (Q-switched) laser operating at a wavelength of 532 nm is utilized to create plasma on the sample's surface. This laser has a maximum pulse energy of approximately 400 mJ and a pulse duration of 5 ns. A set of six miniature spectrometers, covering the wavelength range of 220-970 nm, was utilized to capture and record the optical emissions emitted by the plasma. The qualitative analysis of LIBS revealed the presence of 13 major and minor elements, including Al, Ba, C, Ca, Fe, H, K, Li, Mg, Na, Si, Sr, and Ti. Quantitative analysis was performed using calibration-free laser-induced breakdown spectroscopy (CF-LIBS), ensuring local thermodynamical equilibrium (LTE) and optically thin plasma condition by considering plasma excitation temperature and electron number density. In addition, a comparison was made between the results obtained from CF-LIBS and those acquired through energy-dispersive X-ray spectroscopy (EDX) analysis.

Mechanical stirring: Novel engineering approach for in situ spectroscopic analysis of melt at high temperature

This paper proposes a novel engineering approach to control molten metals at high temperatures considering the industrial environment of such materials. To reduce analysis time and cost, in-line analysis techniques are more advantageous as they provide real-time information about melt composition. For this reason, recent research works focus on the development of new devices based on LIBS (Laser Induced Breakdown Spectroscopy). These devices allowed for analyzing impurities inside molten metals with great performance. However, improvements related to the immersion probe conception are still required. Indeed, the previous design used bubbling inside the melt, leading to spatial instabilities of the surface analyzed by LIBS. The solution presented here is mechanical stirring by innovative rotary blades which will be a part of an immersion LIBS probe. Their rotation will generate a representative, renewed, and stable surface that will be targeted by spectroscopic techniques in general and particularly by LIBS laser for molten metal monitoring at high temperatures. This solution was validated using experimental tests based on particle imaging velocimetry (PIV) in water at room temperature and then applied to silicon melt at high temperatures. To do so, it was necessary to design a system that allows the introduction of the blade in the melt and controls its rotation.

A Novel LIBS Sensor for Sample Examinations on a Crime Scene

In this work, we present a compact LIBS sensor developed for characterization of samples on a crime scene following requirements of law enforcement agencies involved in the project. The sensor operates both in a tabletop mode, for aside measurements of swabbed materials or taken fragments, and in handheld mode where the sensor head is pointed directly on targets at the scene. The sensor head is connected via an umbilical to an instrument box that could be battery-powered and contains also a color camera for sample visualization, illumination LEDs, and pointing system for placing the target in focus. Here we describe the sensor's architecture and functionalities, the optimization of the acquisition parameters, and the results of some LIBS measurements. On nano-plotted traces at silica wafer and in optimized conditions, for most of the elements the detection limits, in term of the absolute element masses, were found to be below 10 picograms. We also show results obtained on some representative materials, like fingerprints, swabbed soil and gunshot residue, varnishes on metal, and coated plastics. The last, solid samples were used to evaluate the depth profiling capabilities of the instrument, where the recognition of all four car paint layers was achieved.

Extended total number density compensation for uranium determination by laser-induced breakdown spectroscopy

BACKGROUND

Variations in plasma properties among spectra and samples lead to significant signal uncertainty and matrix effects in laser-induced breakdown spectroscopy (LIBS). To address this issue, direct compensation for plasma property variations is considered highly desirable. However, reliably compensating for the total number density variation is challenging due to inaccurate spectroscopic parameters. For reliable compensation, a total number density compensation (TNDC) method was presented in our recent work, but its applicability is limited to simple samples because of its strict assumptions. In this study, we propose a new pre-processing method, namely extended TNDC (ETNDC), to reduce signal uncertainty and matrix effects in the more complex analytical task of uranium determination.

RESULTS

ETNDC reflects the total number density variation with a weighted combination of spectral lines from all major elements and incorporates temperature and electron density compensation into the weighting coefficients. The method is evaluated on yellow cake samples and combined with regression models for uranium determination. Using the typical validation set and line combination, the mean relative standard deviation (RSD) of U II 417.159 nm in validation samples decreases from 4.92% to 2.27%, and the root mean square error of prediction (RMSEP) and the mean RSD of prediction results decrease from 4.81% to 1.93% and from 1.92% to 1.56%, respectively. Furthermore, the results of 10 validation sets and 216 line combinations show that ETNDC outperforms baseline methods in terms of average performance and robustness.

SIGNIFICANCE

For the first time, ETNDC explicitly addresses the temperature and electron density variations while compensating for the total number density variation, where the inaccurate spectroscopic parameters are avoided by fitting related quantities using concentration information. The method demonstrates effective and robust improvement in signal repeatability and analytical performance in uranium determination, facilitating accurate quantification of the LIBS technique.

Laser Ablation Plasmas and Spectroscopy for Nuclear Applications

The development of measurement methodologies to detect and monitor nuclear-relevant materials remains a consistent and significant interest across the nuclear energy, nonproliferation, safeguards, and forensics communities. Optical spectroscopy of laser-produced plasmas is becoming an increasingly popular diagnostic technique to measure radiological and nuclear materials in the field without sample preparation, where current capabilities encompass the standoff, isotopically resolved and phase-identifiable (e.g., UO and UO2 ) detection of elements across the periodic table. These methods rely on the process of laser ablation (LA), where a high-powered pulsed laser is used to excite a sample (solid, liquid, or gas) into a luminous microplasma that rapidly undergoes de-excitation through the emission of electromagnetic radiation, which serves as a spectroscopic fingerprint for that sample. This review focuses on LA plasmas and spectroscopy for nuclear applications, covering topics from the wide-area environmental sampling and atmospheric sensing of radionuclides to recent implementations of multivariate machine learning methods that work to enable the real-time analysis of spectrochemical measurements with an emphasis on fundamental research and development activities over the past two decades. Background on the physical breakdown mechanisms and interactions of matter with nanosecond and ultrafast laser pulses that lead to the generation of laser-produced microplasmas is provided, followed by a description of the transient spatiotemporal plasma conditions that control the behavior of spectroscopic signatures recorded by analytical methods in atomic and molecular spectroscopy. High-temperature chemical and thermodynamic processes governing reactive LA plasmas are also examined alongside investigations into the condensation pathways of the plasma, which are believed to serve as chemical surrogates for fallout particles formed in nuclear fireballs. Laser-supported absorption waves and laser-induced shockwaves that accompany LA plasmas are also discussed, which could provide insights into atmospheric ionization phenomena from strong shocks following nuclear detonations. Furthermore, the standoff detection of trace radioactive aerosols and fission gases is reviewed in the context of monitoring atmospheric radiation plumes and off-gas streams of molten salt reactors. Finally, concluding remarks will present future outlooks on the role of LA plasma spectroscopy in the nuclear community.

Interpreting convolutional neural network classifiers applied to laser-induced breakdown optical emission spectra

Laser-induced breakdown spectroscopy (LIBS) is a well-established industrial tool with emerging relevance in high-stakes applications. To achieve its required analytical performance, LIBS is often coupled with advanced pattern-recognition algorithms, including machine learning models. Namely, artificial neural networks (ANNs) have recently become a frequently applied part of LIBS practitioners' toolkit. Nevertheless, ANNs are generally applied in spectroscopy as black-box models, without a real insight into their predictions. Here, we apply various post-hoc interpretation techniques with the aim of understanding the decision-making of convolutional neural networks. Namely, we find synthetic spectra that yield perfect expected classification predictions and denote these spectra class-specific prototype spectra. We investigate the simplest possible convolutional neural network (consisting of a single convolutional and fully connected layers) trained to classify the extended calibration dataset collected for the ChemCam laser-induced breakdown spectroscopy instrument of the Curiosity Mars rover. The trained convolutional neural network predominantly learned meaningful spectroscopic features which correspond to the elements comprising the major oxides found in the calibration targets. In addition, the discrete convolution operation with the learnt filters results in a crude baseline correction.

Microstructure Formations Resulting from Nanosecond and Picosecond Laser Irradiation of a Ti-Based Alloy under Controlled Atmospheric Conditions and Optimization of the Irradiation Process

This paper presents a study and comparison of surface effects induced by picosecond and nanosecond laser modification of a Ti6Al4V alloy surface under different ambient conditions: air and argon- and nitrogen-rich atmospheres. Detailed surface characterization was performed for all experimental conditions. Damage threshold fluences for picosecond and nanosecond laser irradiation in all three ambient conditions were determined. The observed surface features were a resolidified pool of molten material, craters, hydrodynamic effects and parallel periodic surface structures. Laser-induced periodic surface structures are formed by multi-mode-beam nanosecond laser action and picosecond laser action. Crown-like structures at crater rims are specific features for picosecond Nd:YAG laser action in argon-rich ambient conditions. Elemental analysis of the surfaces indicated nitride compound formation only in the nitrogen-rich ambient conditions. The constituents of the formed plasma were also investigated. Exploring the impact of process control parameters on output responses has been undertaken within the context of laser modification under different environmental conditions. Parametric optimization of the nanosecond laser modification was carried out by implementing an advanced method based on Taguchi's parametric design and multivariate statistical techniques, and optimal settings are proposed for each atmosphere.

Highly Precise Laser-Induced Breakdown Spectroscopy Analysis of Major Mineral Nutrients in Edible Salts Using Miniaturized Salt Ponds and Alternating Laser-Ablation Data Sampling

In this work, we applied a hydrophilicity-enhanced solid substrate and an alternating laser-ablation data sampling (ALADS) scheme to improve laser-induced breakdown spectroscopy (LIBS) measurement precision and demonstrated the performance in analyzing K, Mg, Ca, and S contained in commercially available edible salt products. Five edible salt products from Australia, Bolivia, France, and South Korea were dissolved in water and a tiny volume of each solution was dropped on the solid substrate, that is, a miniaturized salt pond. After being dried, the residual salt crystals distributed still inhomogeneously, but the homogeneity could be significantly improved in comparison with that from typical drop-and-dry methods. The ALADS scheme was applied to extract three precise measurements from 9798 single-shot LIBS spectra covering the entire salt pond. The measurements obtained by ALADS were found to agree well with one another regardless of the inhomogeneous distribution of salt crystals. As a result, the measurement precision was proved remarkably. Limits of detection for K, Mg, Ca, and S were estimated to be 0.64, 1.7, 14, and 530 mg/kg, respectively, which are enough to analyze those elements contained in salts typically at the level of 100 parts per million (ppm) to ∼3 wt% for the purpose of salt quality assessment.

Recent advances and applications of laser-based imaging techniques in food crops and products: a critical review

To meet the growing demand for food quality and safety, there is a pressing need for fast and visible techniques to monitor the food crop and product production processing, and to understand the chemical changes that occur during these processes. Herein, the fundamental principles, instruments, and characteristics of three major laser-based imaging techniques (LBITs), namely, laser-induced breakdown spectroscopy, Raman spectroscopy, and laser ablation-inductively coupled plasma-mass spectrometry, are introduced. Additionally, the advances, challenges, and prospects for the application of LBITs in food crops and products are discussed. In recent years, LBITs have played a crucial role in mapping primary metabolites, secondary metabolites, nanoparticles, toxic metals, and mineral elements in food crops, as well as visualizing food adulteration, composition changes, pesticide residue, microbial contamination, and elements in food products. However, LBITs are still facing challenges in achieving accurate and sensitive quantification of compositions due to the complex sample matrix and minimal laser sampling quantity. Thus, further research is required to develop comprehensive data processing strategies and signal enhancement methods. With the continued development of imaging methods and equipment, LBITs have the potential to further explore chemical distribution mechanisms and ensure the safety and quality of food crops and products.

A Simple Laser-Induced Breakdown Spectroscopy Method for Quantification and Classification of Edible Sea Salts Assisted by Surface-Hydrophilicity-Enhanced Silicon Wafer Substrates

Salt, one of the most commonly consumed food additives worldwide, is produced in many countries. The chemical composition of edible salts is essential information for quality assessment and origin distinction. In this work, a simple laser-induced breakdown spectroscopy instrument was assembled with a diode-pumped solid-state laser and a miniature spectrometer. Its performances in analyzing Mg and Ca in six popular edible sea salts consumed in South Korea and classification of the products were investigated. Each salt was dissolved in water and a tiny amount of the solution was dropped and dried on the hydrophilicity-enhanced silicon wafer substrate, providing homogeneous distribution of salt crystals. Strong Mg II and Ca II emissions were chosen for both quantification and classification. Calibration curves could be constructed with limits-of-detection of 87 mg/kg for Mg and 45 mg/kg for Ca. Also, the Mg II and Ca II emission peak intensities were used in a k-nearest neighbors model providing 98.6% classification accuracy. In both quantification and classification, intensity normalization using a Na I emission line as a reference signal was effective. A concept of interclass distance was introduced, and the increase in the classification accuracy due to the intensity normalization was rationalized based on it. Our methodology will be useful for analyzing major mineral nutrients in various food materials in liquid phase or soluble in water, including salts.

Assessing the shooting distance of lead-free ammunition regardless of composition using Laser Induced Breakdown Spectroscopy

At present, it is challenging to accurately determine firearm shooting distances in the case that lead-free ammunition is involved, largely because different manufacturers use different primer compositions. Laser-induced breakdown spectroscopy (LIBS) allows the simultaneous detection of multiple elements with high sensitivity and so may represent a solution to this problem. Previous studies have, in fact, demonstrated that LIBS can be used to determine shooting distances when working with gunshot residues from conventional ammunition based on scanning fabric surfaces. The present study confirms that the shooting distance can be ascertained using LIBS to detect copper originating from the ammunition casing and projectile but not the primer on fabric surfaces. This estimation can be performed regardless of the primer composition of lead-free ammunition.

Key points

Evaluation of gunshot residue from lead-free ammunition using scanning electron microscopy-energy dispersive X-ray analysis indicated that 40% of the particles contained copper.The iForenLIBS system allowed the detection of copper-containing particles on fabric surfaces after firing at different distances with high sensitivity.Laser-induced breakdown spectroscopy can determine the shooting distance of lead-free ammunition through copper detection even in ammunition that does not used this element in the primer.This technique can generate density maps allowing the evaluation of short, medium, and long-range shooting distances.

Detection of Off-Gassed Products From Molten Salts Using Laser-Induced Breakdown Spectroscopy

The detection of off-gassed sodium from molten sodium nitrate (NaNO3) at temperatures between 330 °C and 505 °C and off-gassed calcium from molten lithium chloride-potassium chloride eutectic (LKE) mixtures at 510 °C with laser-induced breakdown spectroscopy (LIBS) was demonstrated. NaNO3 and LKE samples were melted in a custom-built crucible that promoted the generation of off-gassed products from the molten sample. The off-gassed products were analyzed with a LIBS system designed to probe the high-temperature environment. Na D emission lines, Na(I)588.99 nm and Na(I) 589.59 nm, were detected from the NaNO3 samples after reaching a temperature threshold, which indicated the occurrence of phase change. In LKE mixtures, the detection of Ca impurities at a concentration of 78 mg/kg was possible using the emission lines Ca(II) 393.66 nm and Ca(II) 395.85 nm. This work demonstrates the real-time monitoring capabilities of LIBS in high-temperature environments that simulate the conditions of molten salt reactors.

Mobile Laser-Induced Breakdown Spectroscopy for Future Application in Precision Agriculture-A Case Study

In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.

Spatiotemporal Plasma-Particle Characterization of Dry Aerosols Using Nanosecond, Femtosecond, and Filament Laser-Produced Plasmas

The ability to rapidly characterize dry aerosols in air using laser-induced breakdown spectroscopy (LIBS) with femtosecond laser pulses promises advancement towards real-time atmospheric sampling and standoff capabilities. Of particular interest is the ability to apply LIBS in the context of low-particle loaded environments where discrete particle interactions must be observed within the sampling volume of the laser-produced plasma (LPP). In this study, dry nanoparticles in suspension are generated from a standard solution and sampled in air using Q-switched nanosecond (ns-) pulses, short-focus (SF) femtosecond (fs-) pulses, and filaments. Short time-gated plasma images are captured to observe spatially and temporally varying discrete plasma-particle interactions, which is shown to influence early air breakdown behavior and subsequent plasma evolution. Along with images, photo-multiplier tube (PMT) measurements are conducted where strong spatiotemporal dependencies are exhibited by the collected emission signal on particle proximity and plasma expansion behavior. Finally, conditional analysis is performed on LIBS measurements to determine associated sampling probabilities and filter out spectra with poor or absent emission peaks with an adaptive threshold algorithm.

Multi-Spectroscopic Characterization of MgO/Nylon (6/6) Polymer: Evaluating the Potential of LIBS and Statistical Methods

The potential of using laser-induced breakdown spectroscopy (LIBS) in combination with various other spectroscopic and statistical methods was assessed for characterizing pure and MgO-doped nylon (6/6) organic polymer samples. The pure samples, obtained through a polycondensation chemical technique, were artificially doped with MgO prior to analysis for comparative purposes. These artificially doped samples served as crucial reference materials for comparative analysis and reference purposes. The LIBS studies were performed under local thermodynamic equilibrium (LTE) and optically thin plasma conditions. To assess the structural crystallinity of the nylon (6/6) polymer samples, X-ray diffraction (XRD) analysis, and Fourier transform infrared (FTIR) spectroscopy were employed to detect functional groups such as N-H, C-H, and C-N in the adsorbent polyamide nylon sample. Additionally, diffuse reflectance spectroscopy (DRS) analysis was conducted to investigate the effects of doping and temperature on the band gap and material reflectance across different sample temperatures. Chemical compositional analysis was performed using X-ray photoelectron spectroscopy (XPS) with the carbon C1s peak at 248.8 eV serving as a reference for spectrum calibration, along with energy-dispersive X-ray (EDX) analysis, which demonstrated good agreement between the techniques. To validate the different methodologies, the results obtained from CF-LIBS and EDX were compared with those from the standard inductively coupled plasma mass spectrometry (ICP-MS) technique. Finally, for classification analysis, principal component analysis (PCA) was applied to the LIBS spectral data at different sample temperatures (25 °C, 125 °C, 225 °C, and 325 °C). The analyses demonstrated that the combination of LIBS with PCA, along with other methods, presents a robust technique for polymer characterization.

Explorative Data Analysis Methods: Application to Laser-Induced Breakdown Spectroscopy Field Data Measured on the Island of Vulcano, Italy

One of the strengths of laser-induced breakdown spectroscopy (LIBS) is that a large amount of data can be measured relatively easily in a short time, which makes LIBS interesting in many areas, from geomaterial analysis with portable handheld instruments to applications for the exploration of planetary surfaces. Statistical methods, therefore, play an important role in analyzing the data to detect not only individual compositions but also trends and correlations. In this study, we apply two approaches to explore the LIBS data of geomaterials measured with a handheld device at different locations on the Aeolian island of Vulcano, Italy. First, we use the established method, principal component analysis (PCA), and second we adopt the principle of the interesting features finder (IFF), which was recently proposed for the analysis of LIBS imaging data. With this method it is possible to identify spectra that contain emission lines of minor and trace elements that often remain undetected with variance-based methods, such as PCA. We could not detect any spectra with IFF that were not detected with PCA when applying both methods to our LIBS field data. The reason for this may be the nature of our field data, which are subject to more experimental changes than data measured in laboratory settings, such as LIBS imaging data, for which the IFF was introduced first. In conclusion, however, we found that the two approaches complement each other well, making the exploration of the data more intuitive, straightforward, and efficient.

Quantitative elemental mapping of biological tissues by laser-induced breakdown spectroscopy using matrix recognition

The present study demonstrates the importance of converting signal intensity maps of organic tissues collected by laser-induced breakdown spectroscopy (LIBS) to elemental concentration maps and also proposes a methodology based on machine learning for its execution. The proposed methodology employs matrix-matched external calibration supported by a pixel-by-pixel automatic matrix (tissue type) recognition performed by linear discriminant analysis of the spatially resolved LIBS hyperspectral data set. On a swine (porcine) brain sample, we successfully performed this matrix recognition with an accuracy of 98% for the grey and white matter and we converted a LIBS intensity map of a tissue sample to a correct concentration map for the elements Na, K and Mg. Found concentrations in the grey and white matter agreed the element concentrations published in the literature and our reference measurements. Our results revealed that the actual concentration distribution in tissues can be quite different from what is suggested by the LIBS signal intensity map, therefore this conversion is always suggested to be performed if an accurate concentration distribution is to be assessed.

Medical application of laser-induced breakdown spectroscopy (LIBS) for assessment of trace element and mineral in biosamples: Laboratory and clinical validity of the method

BACKGROUND

Biomedical application is based on the use of LIBS-derived data on chemical contents of tissues in diagnosis of diseases, forensic investigation, as well as a mechanism for providing online feedback for laser surgery. Although LIBS has certain advantages, the issue of correlation of LIBS-derived data on chemical element content in different human and animal tissues with other methods, and especially ICP-MS, remains pertinent. The objective of the present review was to discuss the application of laser-induced breakdown spectroscopy (LIBS) for elemental analysis of human biosamples or tissues from experimental models of human diseases.

METHODS

A systematic search in the PubMed-Medline, Scopus, and Google Scholar databases using the terms laser-induced breakdown spectroscopy, LIBS, metals, trace elements, minerals, and names of particular chemical elements was performed up through 25 February, 2023. Of all extracted studies only those dealing with human subjects, human tissues, in vivo animal and in vitro cell line models of human diseases were reviewed in detail.

RESULTS

The majority of studies revealed a wide number of metals and metalloids in solid tissues including teeth (As, Ag, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Ni, P, Pb, Sn, Sr, Ti, and Zn), bones (Al, Ba, Ca, Cd, Cr, K, Mg, Na, Pb, Sr), and nails (Al, As, Ca, Fe, K, Mg, Na, P, Pb, Si, Sr, Ti, Zn). At the same time, LIBS was also used for estimation of trace element and mineral content in hair (Ca, Cu, Fe, K, Mg, Na, Zn), blood (Al, Ca, Co, Cd, Cu, Fe, Mg, Mn, Ni, Pb, Si, Sn, Zn), cancer tissues (Ca, Cu, Fe, Mg, K, Na, Zn) and other tissues. Single studies revealed satisfactory correspondence between quantitative LIBS and ICP-OES/MS data on the level of As (81-93 %), Pb (94-98 %), Cd (50-94 %) in teeth, Cu (97-105 %), Fe (117 %), Zn (88-117 %) in hair, Ca (97-99 %), Zn (90-95 %), and Pb (61-82 %) in kidney stones. LIBS also estimated specific patterns of trace element and mineral content associated with multiple pathologies, including caries, cancer, skin disorders, and other systemic diseases including diabetes mellitus type 2, osteoporosis, hypothyroidism, etc. Data obtained from in situ tissue LIBS analysis were profitably used for discrimination between tissue types.

CONCLUSIONS

Taken together, the existing data demonstrate the applicability of LIBS for medical studies, although further increase in its sensitivity, calibration range, cross-validation, and quality control is required.

Long-wave infrared laser-induced breakdown spectroscopy of complex gas molecules in the vicinity of a laser-induced plasma

Vibration-rotation signatures of intact water and complex organic molecules in vapor phase were detected, identified, and mode-assigned in the long-wave infrared emissions of laser-induced plasma. Time resolved long-wave infrared emissions were also studied to assess the temporal behaviors of these gaseous molecular emitters. The temperatures of these molecular vapors in the hot and transient vapor-plasma plume of the laser-induced plasma were estimated to be well above room temperatures during their existence. The temperatures of the water vapors in the vapor-plasma plume were found to be evolving with time and ranging from > 2700 K at 10 µs to ∼ 1500 K at 200 µs after plasma initiations using HITRAN/HAPI based molecular spectral analysis. The observations in the present study comprise (to our knowledge) the first direct evidence of hot water and intact complex organic gas molecules in the vicinity of the laser-induced plasma. The findings presented in this work serve as an important step forward in improving the understanding of the thermodynamic characteristics (such as temperatures and phases) of intact complex molecules in a hot and intricate system such as the vapor-plasma plume of a laser-induced plasma, which is essential in both fundamental studies of plasmas and of laser-induced plasma based analytical applications.

Phosphorus quantification in soil using LIBS assisted by laser-induced fluorescence

Quantification and monitoring of phosphorus in soil plays a critical role in environmentally friendly agriculture, especially in mitigation of phosphorus leakages to water systems and subsequent risk for eutrophication. On the other hand, deficiency in phosphorus would lead to problems in development and growth of cultivated crops. Therefore, monitoring and quantification of phosphorus status in soil is essential. In this work, laser-induced breakdown spectroscopy assisted by laser-induced fluorescence (LIBS-LIF) is introduced for quantification of readily soluble phosphorus in soil and compared to the analytical performance of the conventional LIBS method. Mineral soils with variable phosphorus status were used for the analysis. The calibration curves are plotted to evaluate the detection limit of the soluble phosphorus. Compared results demonstrate improvement in detection limit from 3.74 mg/kg to 0.12 mg/kg for clay soil and from 10.94 mg/kg to 0.27 mg/kg for silt loam/loam soil in LIBS and LIBS-LIF measurements, respectively. For the LIBS-LIF measurement, detection limits are comparable with established chemical soil analyses. The proposed method would substantially reduce required sample preparation and laboratory work compared with conventional phosphorus quantification. In addition, as the calibration curves demonstrate that the calibration for soluble phosphorus holds within a soil type, LIBS-LIF has the potential to be used for high throughput soil analysis.

Adversarial Data Augmentation and Transfer Net for Scrap Metal Identification Using Laser-Induced Breakdown Spectroscopy Measurement of Standard Reference Materials

In this study, we propose a transfer learning-based classification model for identifying scrap metal using an augmented training dataset consisting of laser-induced breakdown spectroscopy (LIBS) measurement of standard reference material (SRMs) samples, considering varying experimental setups and environmental conditions. LIBS provides unique spectra for identifying unknown samples without complicated sample preparation. Thus, LIBS systems combined with machine learning methods have been actively studied for industrial applications such as scrap metal recycling. However, in machine learning models, a training set of the used samples may not cover the diversity of the scrap metal encountered in field measurements. Moreover, differences in experimental configuration, where laboratory standards and real samples are analyzed in situ, may lead to a wider gap in the distribution of training and test sets, dramatically reducing the performance of the LIBS-based fast classification system for real samples. To address these challenges, we propose a two-step Aug2Tran model. First, we augment the SRM dataset by synthesizing spectra of unobserved types through attenuation of dominant peaks corresponding to sample composition and generating spectra depending on the target sample using a generative adversarial network. Second, we used the augmented SRM dataset to build a robust real-time classification model with a convolutional neural network, which is further customized for the target scrap metal with limited measurements through transfer learning. For evaluation, SRMs of five representative metal types, including aluminum, copper, iron, stainless steel, and brass, are measured with a typical setup to form the SRM dataset. For testing, scrap metal from actual industrial fields is experimented with three different configurations, resulting in eight different test datasets. The experimental results show that the proposed scheme produces an average classification accuracy of 98.25% for the three experimental conditions, as high as the results of the conventional scheme with three separately trained and executed models. Additionally, the proposed model improves the classification accuracy of arbitrarily shaped static or moving samples with various surface contaminations and compositions, and even for differing ranges of charted intensities and wavelengths. Therefore, the proposed Aug2Tran model can be used as a systematic model for scrap metal classification with generalizability and ease of implementation.

Quantification of nanoparticles' concentration inside polymer films using lock-in thermography

Thin nanocomposite polymer films embedding various types of nanoparticles have been the target of abundant research to use them as sensors, smart coatings, or artificial skin. Their characterization is challenging and requires novel methods that can provide qualitative as well as quantitative information about their composition and the spatial distribution of nanoparticles. In this work, we show how lock-in thermography (LIT) can be used to quantify the concentration of gold nanoparticles embedded in polyvinyl alcohol (PVA) films. LIT is an emerging and non-destructive technique that measures the thermal signature produced by an absorbing sample illuminated by modulated light with a defined frequency. Films with various concentrations of gold nanoparticles of two different sizes have been prepared by evaporation from homogeneous aqueous PVA gold nanoparticle suspensions. When the thin films were illuminated with monochromatic light at a wavelength close to the plasmonic resonance signature of the nanoparticles, the amplitude of the thermal signature emitted by the nanoparticles was recorded. The measurements have been repeated for multiple modulation frequencies of the incident radiation. We have developed a mathematical method to quantitatively relate the concentration of nanoparticles to the measured amplitude. A discussion about the conditions under which the sample thickness can be determined is provided. Furthermore, our results show how LIT measurements can easily detect the presence of concentration gradients in samples and how the model allows the measured signal to be related to the respective concentrations. This work demonstrates the successful use of LIT as a reliable and non-destructive method to quantify nanoparticle concentrations.

Response mechanism and rapid detection of phenotypic information in rice root under heavy metal stress

The root is an important organ affecting cadmium accumulation in grains, but there is no comprehensive research involving rice root phenotype under cadmium stress yet. To assess the effect of cadmium on root phenotypes, this paper investigated the response mechanism of phenotypic information including cadmium accumulation, adversity physiology, morphological parameters, and microstructure characteristics, and explored rapid detection methods of cadmium accumulation and adversity physiology. We found that cadmium had the effect of "low-promotion and high-inhibition" on root phenotypes. In addition, the rapid detection of cadmium (Cd), soluble protein (SP), and malondialdehyde (MDA) were achieved based on spectroscopic technology and chemometrics, where the optimal prediction model was least squares support vector machine (LS-SVM) based on the full spectrum (R_p=0.9958) for Cd, competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) (R_p=0.9161) for SP and CARS-ELM (R_p=0.9021) for MDA, all with R_p higher than 0.9. Surprisingly, it took only about 3 min, which was more than 90% reduction in detection time compared with laboratory analysis, demonstrating the excellent ability of spectroscopy for root phenotype detection. These results reveal response mechanism to heavy metal and provide rapid detection method for phenotypic information, which can substantially contribute to crop heavy metal control and food safety supervision.

Long-term repeatability improvement using beam intensity distribution for laser-induced breakdown spectroscopy

The relatively low measurement repeatability has long been considered as a major obstacle to the widespread use and commercialization of laser-induced breakdown spectroscopy (LIBS). Although many efforts have been made to improve the signal repeatability in the short term, how to improve the long-term signal repeatability is critical in practical applications and has rarely been studied. Moreover, the mechanisms behind the degradation of long-term repeatability are not fully revealed. This study proposes a new method to improve the long-term repeatability of LIBS measurement, which modifies the spectral intensity based on laser beam intensity distribution. It first pre-processes the beam intensity distribution profiles and spectral intensity. Then the relationship between the relative deviations of beam and spectral intensities is modelled using Partial Least Squares Regression (PLSR). The proposed method was tested on copper and silicon samples, and the spectra and laser beam intensity distribution were recorded for more than thirty days. Day-to-day variations in beam intensity distribution were observed. Such variations can lead to changes in spectral intensity, resulting in degraded signal repeatability. By modifying the spectral intensity, the long-term signal repeatability was improved. Specifically, in terms of day-mean spectral intensity, the valid correction rates were above 70% for both of copper silicon sample in most cases. Long-term RSD decreased from ∼13.5% to ∼4% for copper and decreased from ∼10.7% to 6.5% for silicon sample. These results indicate that the proposed method provides a viable method for improving the long-term repeatability of LIBS measurement.

A novel method for correcting the effect of the lens-to-sample distance change on the signal intensity in laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) is a promising technique for real-time online coal analysis. The lens-to-sample distance (LTSD) significantly affects the obtained signal intensity as well as the accuracy of the element quantitative analysis by LIBS. In this study, a new method is proposed to correct the effect of the change in LTSD on the signal intensity. A correction formula that fits the relationship between the obtained signal intensity and the deviation (d) between the LTSD and the focal length is constructed through a series of experiments based on 18 standard coal samples and validated with three types of unknown coal samples. The results show that compared with the original signal intensity in the experiments, the relative errors between the corrected signal intensity and the signal intensity when the LTSD is equal to the focal length decreased by a factor of more than ten for almost all the elements of C, H, O, and N in the three samples. In particular, when d takes -4 to 2 mm, the mean relative errors after correction are all below 10%. This indicates that the proposed method can be used to correct the signal intensity of the elements C, H, O, and N when d is -4 to 2 mm in real-time online coal analysis.

Feasibility of a Low-Power, Low-Resolution Laser-Induced Breakdown Spectroscopy Instrument for Analysis of Nickel Alloys: Quantification of the Major Alloying Elements and Classification

A simple cost-effective laser-induced breakdown spectroscopy (LIBS) instrument was used for quantification of major elements in several nickel alloys and also sorting them. A compact low-power diode-pumped solid-state laser and a miniature low-resolution spectrometer were assembled for the LIBS instrument. Material properties of the nickel alloys depend mainly on the composition of the major elements, Ni, Cr, and Fe, ranging from a few to ∼60 wt%. The emission peaks at 547.7 nm, 520.4 nm, and 438.1 nm for Ni, Cr, and Fe, respectively, were chosen for this analysis. The analytical performance was found to be enough for the quantification of Ni, Cr, and Fe in the nickel alloys. Limits of detection and accuracy were estimated to be a few weight percent (wt%) and measurement precisions were less than 10% in terms of relative standard deviation. The calibration performance of this intensity-based method was compared with that of the "ratio method" which is used in conventional optical emission spectroscopy analyses. The comparison indicates that the intensity-based method is more appropriate with the low-performance LIBS instrument that detects emission peaks of only a few major elements. Also, multivariate modeling of the six different nickel alloy samples based on the emission peak intensities of Ni, Cr, and Fe was performed using k-nearest neighbors (KNN) and linear discriminant analysis (LDA). The KNN and ordinary LDA models showed 95.0% and 98.3% classification correctness for the separate test data set, respectively. To improve classification performance further, the two-step LDA model was trained. In this approach, the two closest sample classes responsible for the decrease in the classification correctness were separately modeled in the second step to exploit their difference effectively. The two-step LDA model showed 100% correctness in classifying the test objects. Our results indicate that such a low-performance LIBS instrument can be effectively utilized for quantitative analysis of the major elements in the nickel alloys and their rapid identification or sorting in combination with an appropriate multivariate modeling algorithm.

Sensitive Detection of the Human Epididymis Protein-4 (HE4) Ovarian Cancer Biomarker through a Sandwich-Type Immunoassay Method with Laser-Induced Breakdown Spectroscopy

Detection of cancer before the appearance of any symptoms is crucial for successful treatment. Early detection is, however, very challenging, particularly for the types of cancer with few or no symptoms at early stages, such as epithelial ovarian cancer (EOC). Developing a user-friendly method that can detect biomarkers with sufficient selectivity, sensitivity, and reproducibility is a promising approach for overcoming the challenges of early detection of EOC. In this study, we report a sandwich-type microparticle immunoassay for sensitive detection of the HE4 biomarker with laser-induced breakdown spectroscopy. Here, we cross-linked elemental particles to a specific functional group of the targeted biomolecules based on a covalent and non-covalent linking chemistry to improve the sensitivity and selectivity of biomarker detection, in which Fe₃O₄ and SiO₂ microparticles were used to conjugate and purify the antibody-antigen in complex media. Simultaneous detection of Fe and Si from a magnetically purified assay significantly improves the HE4 biomarker's detectability, in which HE4 was detected with a limit of detection of 0.0022 pM. We also determined the coupling ratio between HE4 and silica particles using a silicon calibration curve.

Heavy Metal Detection in Fritillaria thunbergii Using Laser-Induced Breakdown Spectroscopy Coupled with Variable Selection Algorithm and Chemometrics

Environmental and health risks associated with heavy metal pollution are serious. Human health can be adversely affected by the smallest amount of heavy metals. Modeling spectrum requires the careful selection of variables. Hence, simple variables that have a low level of interference and a high degree of precision are required for fast analysis and online detection. This study used laser-induced breakdown spectroscopy coupled with variable selection and chemometrics to simultaneously analyze heavy metals (Cd, Cu and Pb) in Fritillaria thunbergii. A total of three machine learning algorithms were utilized, including a gradient boosting machine (GBM), partial least squares regression (PLSR) and support vector regression (SVR). Three promising wavelength selection methods were evaluated for comparison, namely, a competitive adaptive reweighted sampling method (CARS), a random frog method (RF), and an uninformative variable elimination method (UVE). Compared to full wavelengths, the selected wavelengths produced excellent results. Overall, RC2, RV2, RP2, RSMEC, RSMEV and RSMEP for the selected variables are as follows: 0.9967, 0.8899, 0.9403, 1.9853 mg kg−1, 11.3934 mg kg−1, 8.5354 mg kg−1; 0.9933, 0.9316, 0.9665, 5.9332 mg kg−1, 18.3779 mg kg−1, 11.9356 mg kg−1; 0.9992, 0.9736, 0.9686, 1.6707 mg kg−1, 10.2323 mg kg−1, 10.1224 mg kg−1 were obtained for Cd Cu and Pb, respectively. Experimental results showed that all three methods could perform variable selection effectively, with GBM-UVE for Cd, SVR-RF for Pb, and GBM-CARS for Cu providing the best results. The results of the study suggest that LIBS coupled with wavelength selection can be used to detect heavy metals rapidly and accurately in Fritillaria by extracting only a few variables that contain useful information and eliminating non-informative variables.

LIBS assisted PCA analysis of multiple rare-earth elements (La, Ce, Nd, Sm, and Yb) in phosphorite deposits

In the present study, the immediate detection of rare-earth elements (REEs) in phosphorite deposits has been reported using laser-induced breakdown spectroscopy (LIBS). Numerous emission lines corresponding to the REEs such as lanthanum (La), cerium (Ce), neodymium (Nd), samarium (Sm), and ytterbium (Yb), have been detected in the emission spectra of phosphorite-induced plasma plume. For the quantitative analysis, we employed the calibration-free LIBS (CF-LIBS), and Energy Dispersive X-ray (EDX) spectroscopy techniques. The results obtained using the CF-LIBS technique show excellent agreement with that obtained by EDX. Besides principal component analysis (PCA) was employed by incorporating the LIBS spectral data of rare earth phosphorite rocks samples containing La, Ce, Nd, Sm, and Yb emission lines. The first three PCs were observed using LIBS spectral data set showing a covariance (interpretation rate) up to 76.3%. This study suggests that LIBS yields a quick and very reliable qualitative and quantitative analysis of REEs in any geological ore sample.

Simultaneous measurement of carbon emission and gas temperature via laser-induced breakdown spectroscopy coupled with machine learning

A method, which can accurately measure carbon emission and gas temperature simultaneously in real-time from a laser-induced breakdown spectrum (LIBS) via machine learning, is proposed in this study. In typical, peak intensity ratios had been used to map species concentrations prior to plasma formation, after removing the broadband continuum of the spectrum; however, the dependence of these peak intensity ratios on the concentration changes with the change in gas density. Therefore, considering the fact that the strength and shape of this broadband continuum is a function of the gas density for a given optical setup, we attempted to collect a spectrum by shortening the time delay after the laser fire, such that the spectrum can contain some of the broadband continuum. Since the analytical quantification of this broadband continuum is not trivial, we employed a machine learning approach to acquire a model that simultaneously predicts the gas temperature and CO₂ concentration. The predictive performance of the model trained with spectra that contain the broadband continuum was much better than that without it; the gradient-weighted regression activation mapping (Grad-RAM) analysis revealed that the model utilizes the broadband spectrum for temperature prediction and correction of changes in peak intensity due to temperature changes in the concentration prediction process.

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

A synergetic strategy was proposed to address the critical issue in the brand characterization of Colla corii asini (Ejiao, CCA), a precious traditional Chinese medicine (TCM). In all brands of CCA, Dong'e Ejiao (DEEJ) is an intangible cultural heritage resource. Seventy-eight CCA samples (including forty DEEJ samples and thirty-eight samples from other different manufacturers) were detected by laser-induced breakdown spectroscopy (LIBS) and near-infrared spectroscopy (NIR). Partial least squares discriminant analysis (PLS-DA) models were built first considering individual techniques separately, and then fusing LIBS and NIR data at low-level. The statistical parameters including classification accuracy, sensitivity, and specificity were calculated to evaluate the PLS-DA model performance. The results demonstrated that two individual techniques show good classification performance, especially the NIR. The PLS-DA model with single NIR spectra pretreated by the multiplicative scatter correction (MSC) method was preferred as excellent discrimination. Though individual spectroscopic data obtained good classification performance. A data fusion strategy was also attempted to merge atomic and molecular information of CCA. Compared to a single data block, data fusion models with SNV and MSC pretreatment exhibited good predictive power with no misclassification. This study may provide a novel perspective to employ a comprehensive analytical approach to brand discrimination of CCA. The synergetic strategy based on LIBS together with NIR offers atomic and molecular information of CCA, which could be exemplary for future research on the rapid discrimination of TCM.

Metal micro/nanostructure enhanced laser-induced breakdown spectroscopy

This study used a femtosecond laser to ablate a Cu sample, forming a micro/nanostructural layer on the surface. And the effect of this structural layer on nanosecond laser-induced breakdown spectroscopy (LIBS) was discussed. Firstly, the effect of the micro/nanostructural layer on the intensity of laser-induced Cu plasma spectra was investigated. The micro/nanostructure could significantly enhance the spectral intensity of the Cu plasma by 82.5 times at 13.3 mJ laser energy. Secondly, the Cu plasma temperature and electron density were calculated. The micro/nanostructures could significantly increase Cu plasma temperature and electron density. Finally, the effect of micro/nanostructure surface on the spectral intensities of Pb and Cr elements in water was investigated for LIBS analysis. It was found that the detection limit of Pb and Cr trace metal elements in water was 1.85 ng/mL and 0.51 ng/mL at a lower laser energy (13.3 mJ), which was significantly better than other LIBS methods reported so far. The results show that the micro/nanostructure enhanced LIBS is a more sensitive method for detecting trace metal elements in the water.

Influence of ambient gas on self-reversal in Li transitions relevant to isotopic analysis

Laser induced breakdown spectroscopy is a promising, rapid analysis method for the detection and quantification of Li and its isotopes needed in geochemical, nuclear, and energy storage applications. However, spectral broadening in laser produced plasmas, presence of fine and hyperfine structures, and self-reversal effects make Li isotopic analysis via laser induced breakdown spectroscopy challenging. The present study explores the influence of Ar, N₂, and He ambient gases over the pressure range of 0.05 - 100 Torr on line broadening and self-reversal of the Li I transition with the greatest isotopic shift in the VIS spectral region (i.e., ≈670.8 nm, ≈15.8 pm isotopic shift). We perform spatially and temporally resolved optical emission spectroscopy of plasmas produced via laser ablation of LiAlO₂ substrates. Our results show that the self-reversal and linewidth is reduced at lower pressures for all gases, and using optimized plasma conditions with chemometric methods, the ⁶Li/⁷Li isotopic ratios can be predicted.

Comparative Long-Wave Infrared Laser-Induced Breakdown Spectroscopy Employing 1-D and 2-D Focal Plane Array Detectors

Long-wave infrared (LWIR) emissions of laser-induced plasma on solid potassium chloride and acetaminophen tablet surfaces were studied using both a one-dimensional (1-D) linear array detection system and, for the first time, a two-dimensional (2-D) focal plane array (FPA) detection system. Both atomic and molecular infrared emitters in the vicinity of the plasma were identified by analyzing the detected spectral signatures in the infrared region. Time- and space-resolved long-wave infrared emissions were also studied to assess the temporal and spatial behaviors of atomic and molecular emitters in the plasma. These pioneer temporal and spatial investigations of infrared emissions from laser-induced plasma would be valuable to the modeling of plasma evolutions and the advances of the novel LWIR laser-induced breakdown spectroscopy (LIBS). When integrated both temporally (≥200 µs) and spatially using a 2-D FPA detector, the observed intensities and signal-to-noise-ratio (SNR) of single-shot LWIR LIBS signature emissions from intact molecules were considerably enhanced (e.g., with enhancement factors up to 16 and 3.76, respectively, for a 6.62 µm band of acetaminophen molecules) and, in general, comparable to those from the atomic emitters. Pairing LWIR LIBS with conventional ultraviolet-visible-near infrared (UV/Vis/NIR) LIBS, a simultaneous UV/Vis/NIR + LWIR LIBS detection system promises unprecedented capability of in situ, real-time, and stand-off investigation of both atomic and molecular target compositions to detect and characterize a range of chemistries.

Utilization of laser-induced breakdown spectroscopy, with principal component analysis and artificial neural networks in revealing adulteration of similarly looking fish fillets

Fish is an essential source of many nutrients necessary for human health. However, the deliberate mislabeling of similar fish fillet types is common in markets to make use of the relatively high price difference. This is a type of explicit food adulteration. In the present work, spectrochemical analysis and chemometric methods are adopted to disclose this type of fish species cheating. Laser-induced breakdown spectroscopy (LIBS) was utilized to differentiate between the fillets of the low-priced tilapia and the expensive Nile perch. Furthermore, the acquired spectroscopic data were analyzed statistically using principal component analysis (PCA) and artificial neural network (ANN) showing good discrimination in the PCA score plot and a 99% classification accuracy rate of the implemented ANN model. The recorded spectra of the two fish indicated that tilapia has a higher fat content than Nile perch, as evidenced by higher CN and C2 bands and an atomic line at 247.8 nm in its spectrum. The obtained results demonstrated the potential of using LIBS as a simple, fast, and cost-effective analytical technique, combined with statistical analysis for the decisive discrimination between fish fillet species.

Domainal Investigation of a Quartz-Fluorite Composite Using Spectroscopic Techniques

The analysis of geological samples that have several chemically diffused zones which formed under certain physico-chemical condition is difficult to achieve. The quantitative estimations of the minerals in such samples are tedious. The present work demonstrates the application of LIBS for qualitative and quantitative analyses of a quartz-fluorite composite which was procured from an amygdaloidal basalt from Deccan Traps, India. The presence of weak emission lines of F in the spectral range of 200–900 nm makes it challenging to quantify the fluorine. This study has addressed a promising alternative to quantify the fluorine using electronic bands of CaF molecules observed in the Laser-induced Breakdown Spectroscopy (LIBS) spectrum. In addition to this spectroscopic technique, the authors also have used Photoacoustic Spectroscopy (PAS) and UV-VIS spectroscopy technique to obtain molecular information from the geological sample. Principal Component Analysis (PCA) was applied to a truncated spectral region of the CaF molecule, and it showed 99% variance. Further, the obtained results with these spectroscopic techniques were compared with the results that were obtained from X-ray diffraction and Electron Probe Micro Analyzer, and they show good agreement. Thus, the LIBS technique can be promising for in situ profile section (varies from few microns to centimeters size) studies without the sample’s destruction using the point detection capability of LIBS.

Electrolyte Analysis in Blood Serum by Laser-Induced Breakdown Spectroscopy Using a Portable Laser

The fast and reliable analysis of electrolytes such as K, Na, Ca in human blood serum has become an indispensable tool for diagnosing and preventing diseases. Laser-induced breakdown spectroscopy (LIBS) has been demonstrated as a powerful analytical technique on elements. To apply LIBS to the quantitative analysis of electrolyte elements in real time, a self-developed portable laser was used to measure blood serum samples supported by glass slides and filter paper in this work. The partial least squares regression (PLSR) method was employed for predicting the concentrations of K, Na, Ca from serum LIBS spectra. Great prediction accuracies with excellent linearity were obtained for the serum samples, both on glass slides and filter paper. For blood serum on glass slides, the prediction accuracies for K, Na, Ca were 1.45%, 0.61% and 3.80%. Moreover, for blood serum on filter paper, the corresponding prediction accuracies were 7.47%, 1.56% and 0.52%. The results show that LIBS using a portable laser with the assistance of PLSR can be used for accurate quantitative analysis of elements in blood serum in real time. This work reveals that the handheld LIBS instruments will be an excellent tool for real-time clinical practice.

Laser-induced emission spectra of stainless steels and aluminum irradiated with nanopulse lasers without setting delay: potential applications to remote sensing and laser micromachining

Spectral lines from the impurities held in stainless steel and in aluminum can be clearly identified in the UV and the visible spectra when emission is laser induced. These spectroscopic lines can be initiated in metal irradiated at moderate laser optical densities of about 2.5×10⁸W/cm². In addition to the lines arising from impurities found in some metals, it was found that some spectroscopic lines from iron oxide formed during irradiation were also detected at the above-mentioned power density. It was found that lines observed from iron oxide are consistent with what is reported in the literature. The investigations reported were produced on samples at optical densities that are sufficient to create an electric field that is about 10 times the air electrical breakdown near the focal point. The results reported were obtained without setting any delay between the laser Q-switch and the data acquisition. The spectroscopic data are comparable to those shown in the literature by laser-induced breakdown spectroscopy in term of signal-to-noise ratio and are promising in detecting impurities such as heavy metals in remote sensing applications, where pulse delay is not always practical due to atmospheric conditions and power requirements. As a marking procedure is used during the investigations, the method demonstrates how spectroscopic monitoring in real time can be applied during a procedure in laser micromachining applications.