Laser-induced Breakdown Spectroscopy Analysis Research Articles

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.

Laser-Induced breakdown spectroscopy and Energy-Dispersive X-ray analyses for green mineral fluorite (CaF2)

Laser-induced breakdown spectroscopy (LIBS) technique was utilized to investigate the green mineral fluorite (CaF2) samples. The LIBS experiment was implemented by using Nd: YAG Laser system and a linear array CCD detector coupled with an Avantes spectrometer in an air atmosphere. The emission spectra of ten various fluorite samples were studied. The molecular bands correspond to the green B2Σ+-X2Σ+ and orange A2Π-X2Σ systems of diatomic CaF-molecule, specifically at Δν = -1, 0, +1 sequences and the CaO diatomic molecule between 618 nm and 630 nm were detected. It was observed that the CaF-diatomic molecular emission bands exhibited stronger optical emission compared to the fluorine (F) atomic lines. Chemical composition (wt.%) analysis was acquired using CF-LIBS methodology under optically thin and local thermodynamic equilibrium (LTE) conditions. Our CF-LIBS studies revealed that Ca (50–60%) and F (30–40%) were the major elements, while C (3–5%) and O (2–5%) were minor elements present in all samples. For comparison, we employed energy-dispersive X-ray (EDX) technique to study the essential elemental composition (wt.%). The results achieved from CF-LIBS were found to be in good agreement to that obtained from the EDX technique. To validate CF-LIBS results, the calibration curve method was employed using the validated samples (S3, S5, and S7). Furthermore, we utilized a principal component analysis (PCA) technique on the LIBS spectral data to classify the fluorite samples.

Rapid and accurate determination methods based on data fusion of laser-induced breakdown spectra and near-infrared spectra for main elemental contents in compound fertilizers

Compound fertilizer occupies a dominant position in the structure of fertilizer products in China. The contents of nitrogen, phosphorus and potassium are the key indicators affecting the fertilization efficiency and the price of compound fertilizers. Laser-induced breakdown spectroscopy (LIBS) and near-infrared spectroscopy (NIRS) are two rapid analytical techniques suitable for online monitoring of the above components in compound fertilizer. However, accurate LIBS analysis needs to overcome matrix effects and interference from environmental elements, and NIRS also has the limitation of not being able to directly detect inorganic components in compound fertilizers. The combination of LIBS and NIRS techniques, namely LIBS-NIRS data fusion, has the potential to reduce interferences in the detection of single spectroscopic techniques and further improve the analysis accuracy. This study compared the LIBS-NIRS data fusion methods under different optimization conditions, and found that CARS-OPF (competitive adaptive reweighted sampling combined with outer product fusion) and CARS-EWF (competitive adaptive reweighted sampling combined with equal weight fusion) are two effective intermediate data fusion methods which can achieve better quantitative analysis results than single spectroscopic methods. The root mean square errors of prediction (RMSEP) for nitrogen, phosphorus, and potassium contents in compound fertilizers by using CARS-OPF are 0.901, 0.693, and 1.52, respectively, and the RMSEP for those indicators by using CARS-EWF are 0.934, 0.719, and 1.60, respectively. In these two methods, the LIBS and NIRS characteristic variables of compound fertilizers are firstly screened by CARS algorithm, and then intermediate data fusion was carried out by using equal weight fusion or outer product fusion. Redundant variables in the original data can be well removed in the data fusion process to ensure the accuracy of the analysis. Therefore, the combined methods of LIBS-NIRS based on CARS-OPF and CARS-EWF could be well applied to the rapid and accurate detection of main elemental contents in compound fertilizers.

An approach for measurement of the magnetic field near the surface of plasma-facing components in tokamak by laser induced breakdown spectroscopy based on Zeeman effect

Laser-induced breakdown spectroscopy (LIBS) has been demonstrated to diagnose the surface element distribution of plasma-facing components (PFCS) in fusion devices. However, the magnetic field intensity and polarity near the wall surface change frequently and cannot be measured in real time, which will affect the analytical accuracy of LIBS results. The determination of the strength and polarity direction of the magnetic field near the surface will be conducive to the quantitative analysis of LIBS and provide valuable information for the distribution of the magnetic field near the surface of PFCs. In this work, the effects of magnetic fields on the characteristics of laser-induced Mo plasma, such as the ablation depth and mass, the spatio-temporal evolution behavior of spectrum and the plasma parameters, were first systematically investigated. The different phenomenon of continuum radiation, Mo I line and Mo II line under the magnetic field were mutually verified by optical emission spectroscopy and fast plasma imaging methods. Meanwhile, an approach for measurement of the magnetic field intensity and polarity near the surface of PFCS by LIBS method has been proposed and investigated. When the magnetic field polarity is changed, the spatial distribution profile of Mo spectrum will drift in the opposite direction affected by of the Lorentz force, which realizes the measurement of magnetic field polarity. Moreover, the splitting distance of Mo I line caused by Zeeman effect with the variable magnetic fields were preliminarily calculated. The experimental values of splitting distance agree well with the theoretical values that calculated by the known magnetic field strength. These results confirm the feasibility of measuring the magnetic field intensity and polarity of PFCs surface by LIBS approach.

Combined in situ XRF–LIBS analyses as a novel method to determine the provenance of central Mediterranean obsidians

This work presents a new calibration method for determining the provenance of obsidian artefacts based on the combined use of XRF and laser-induced breakdown spectroscopy (LIBS). At first, obsidian samples collected from the main Mediterranean sources were characterized using portable XRF and LIBS systems. After data treatment, elemental information was used to carry out principal component analysis (PCA) for each technique. Rb, Sr, Zr, Y and Fe elements, detected by using XRF, were found to be the key parameters enabling obsidians discrimination. Likewise, LIBS data helped differentiating the analysed patterns by the intensity of their main elemental components (Ca, Al, Mg and K). After selecting the key parameters detected by each technique, a new data matrix combining XRF and LIBS data was finally built. According to PCA results, the discrimination of Mediterranean sources based on combined XRF–LIBS data ensured a higher reliability over mono-analytical models, by increasing the Euclidean distance between sources projections over three-dimensional principal components plots. Knowing that the representativeness of elemental data could be compromised by the presence of superficial degradation products or deposition patinas, a shot-to-shot comparison of in-depth LIBS analyses is finally proposed as a method to disclose whether the spot under analysis was superficially contaminated or altered. Thus, the proposed strategy based on the combined use of portable XRF and LIBS spectrometers could be particularly useful for the in situ analysis of obsidian artefacts that underwent superficial alteration or could be covered by patina products.Graphical abstract

Different Hybrid Prediction's Machine Learning Algorithms for Quantitative Analysis in Laser-Induced Breakdown Spectroscopy

Different Hybrid Prediction's Machine Learning Algorithms for Quantitative Analysis in Laser-Induced Breakdown Spectroscopy

Feasibility of laser-induced breakdown spectroscopy to elucidate elemental changes in human tooth ankylosis

Tooth ankylosis is a pathological condition associated with the loss of physiological tooth mobility when the firm fusion between the alveolar bone and the tooth root occurs. Causes of dental ankylosis are uncertain, so the analysis of elemental distribution in ankylotic and surrounding tissues could provide additional information about its initiation and progression. Here, we used Laser-Induced Breakdown Spectroscopy (LIBS) to determine differences in the mineral composition among ankylotic tissue, bone, and dental tissue taking advantage of its high throughput and multi-elemental capability. Elemental imaging was performed with a spatial resolution of 30 μm to evaluate the distribution of carbon, calcium, magnesium, phosphorus, and strontium in human tooth. To further verify the difference in the mineral composition of ankylotic tissue, the semi-quantitative content of these elements was compared within the region of interest. We revealed a significant increase in calcium, magnesium, and phosphorus contents in the ankylotic tissues. However, the contents of magnesium and phosphorus were not significantly changed. This finding suggests a mineral disbalance only of just certain elements in the tooth-bone interface area during the spread of ankylosis associated with an intense calcification of connective tissue. This paper brings a feasibility study and shows the way of LIBS data interpretation. We propose that the LIBS analysis on a micro-scale can contribute to the understanding of ankylotic tissue composition and can distinguish even small differences of carbon, calcium, magnesium, phosphorus, and strontium contents on the tooth-bone boundary during the initiation of ankylosis. Therefore, it represents a new useful tool for their future, more extensive analyses.

Quantification of alloying elements in steel targets: The LIBS 2022 regression contest

We present the results of the regression contest organized for the LIBS 2022 conference. While the motivation and design of the contest are briefly presented, the work focuses on the methodologies of the three best-performing teams. The employed spectral preprocessing strategies, choice of regression models and its optimization are detailed for each team separately. The aim of the contest reflects the long-term challenges faced by quantitative laser-induced breakdown spectroscopy (LIBS) analysis. Thus, the contest was designed with the purpose of providing a transparent platform for comparing and evaluating the large range of data processing tools available in the LIBS literature. Namely, the contest consisted of the quantification of two major (Cr, Ni) and two minor (Mn, Mo) elements in 15 steel targets. For constructing an appropriate regression model, spectra of 42 targets were provided. The spectra were collected using a commercially available laboratory-based LIBS system and made publicly available. The contest lasted 53 days during which the teams did not receive feedback. In total, 21 teams participated out of which the three best-performing methodologies are presented here. A single linear partial least squares model and two artificial neural network regression models are presented. The corresponding feature selection strategies included emission line selection, spectral range selection, and automatized wavelength selection. Various spectral normalization strategies and data augmentation strategies are also presented.

Rapid Analysis of Muscovites on a Lithium Pegmatite Prospect by Handheld LIBS

Laser-induced breakdown spectroscopy (LIBS) is a technology for compositional analysis that is particularly effective for light elements, particularly Li, which is a critical commodity for emerging green technologies. This study undertook analysis by handheld LIBS of muscovite from the drill core, outcrop, and soil on the Carolina Lithium Prospect (CLP) in Gaston County, North Carolina (USA), which lies within the Carolina Tin-Spodumene Belt (CTSB). Abundances of the alkali elements Li, K, and Rb were determined for more than 130 muscovites from the Li-rich pegmatites to track the degree of pegmatite fractionation as a pathfinder for spodumene mineralization. Across the CTSB and including the CLP, muscovite Li contents vary over an order of magnitude, ranging from 0.04 to 0.74 wt. %, with their K/Rb ratios varying between 63 and 8, features that together document the highly evolved character of pegmatites within the CTSB district. On average, muscovite Li contents are greater in spodumene-bearing pegmatites at 0.21 ± 0.12 wt. % than for common quartz-feldspar pegmatites at 0.14 ± 0.08 wt. %. Although overlapping substantially in the middle portions of their distributions, muscovite K/Rb ratios are biased toward low values for spodumene-bearing pegmatites (X- = 21 ± 6) compared to those for quartz-feldspar pegmatites (X- = 33 ± 9). This study provides a framework for the use of LIBS analysis of muscovite in outcrop, drill core, and soil samples as an analytical tool for in-field and on-site geochemical analysis during Li pegmatite exploration and prospect evaluation.

Nano objects evaluation for nanoparticle enhanced laser induced breakdown spectroscopy analysis of polymers using a handheld device

Polymer additives are essential to provide essential properties to the plastic materials. Some of the mainly employed additives contain metals essential to measure like Sb, Pb or P. Laser Induced Breakdown Spectroscopy suffers a lack of sensitivity for these elements and especially when using handheld devices. The recent developments in Nanoparticles Enhanced Laser Induced Breakdown Spectroscopy (NELIBS) have led to improvement of signals mainly in conductive materials. In this work we prepared and evaluate nano-objects with different shapes and size to improve element signals on plastic samples. Ellipsoid, bipyramids and spheres increased significantly sensitivity of most additives i.e. P, Sb, Mg and Pb. The obtained gold ellipsoids nano-objects were of small dimensions and gave best signal enhancement. The NELIBS also increased the CaF molecular band signal by a factor of 2. These results indicate that the NELIBS can be used in quantitative analytical application for plastics even for difficult elements like fluorine.

Evaluation of spectral collection strategies for identification of Dalbergia spp. using handheld laser‐induced breakdown spectroscopy

AbstractThe 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.

In-situ measurement of hydrogen on airless planetary bodies using laser-induced breakdown spectroscopy

Remote-sensing observations on the surface of airless bodies, such as the Moon and asteroids, have confirmed the presence of hydrogen-bearing materials. However, their spatial distributions at small scales (mm–m) and depth profiles have great uncertainties. In-situ analyses of hydrogen-bearing materials with laser-induced breakdown spectroscopy (LIBS) have been proposed to resolve these problems, as the footprint of LIBS ablation is small (≲1 mm) and can penetrate into the subsurface by excavating the surface layer. Nevertheless, the measurement accuracy of hydrogen with LIBS on airless and hydrous planetary bodies has not been evaluated because it requires extensive calibration using hydrogen-rich geologic materials under a high-vacuum condition. In addition, whether hydrogen occurs as hydroxyl or ice has been difficult to ascertain via LIBS analysis because molecular information is typically lost in the ablation plasma. To resolve these problems, we conducted two experiments. First, compressed powders of rocks were measured by LIBS under vacuum (<3 × 10−2 Pa) to evaluate the calibration accuracies and detection limits in rocks and compacted soils on airless bodies. Several geostandards including basalts and feldspars were doped with various concentrations of hydroxyls (Mg(OH)2 and Ca(OH)2) to prepare hydrogen-rich samples up to 15 wt% in H2O-equivalent concentration (wt%H2O). Our results show that the hydrogen concentration can be accurately calibrated from the LIBS spectra by using multivariate models or matrix-matched calibration curves (i.e., calibration using samples with comparable bulk elemental abundances), facilitating the correction of significant matrix effects observed in the intensities of the 656 nm Hα line. We obtained a measurement accuracy of ±0.9 wt%H2O in the 0–12 wt%H2O range via matrix-matched calibration. This level of accuracy is sufficient for many planetary and resource exploration applications, such as designing hardware and operation for mining water on the Moon. We estimate the 2σ limit of detection (LOD) to be 0.4 wt%H2O based on the average of all samples, although better LODs were obtained for some individual matrix (e.g., 0.2 wt%H2O for basalt/feldspar–Ca(OH)2 mixtures). Such LOD shows that exploitable ice on the Moon can be detected with 2σ confidence by LIBS. Second, we demonstrate that the molecular structure of hydrogen can be distinguished by operating LIBS in tandem with heating lasers. In this method, the samples are heated prior to LIBS analysis using a continuous-wave laser with adjusted fluence and duration. Our results indicate that ice and hydroxyl can be distinguished because the Hα lines of ice-bearing samples decrease after the laser heating due to sublimation, but those of hydroxyl-bearing samples are retained. In addition, we report an enhancement of hydrogen emission from loose powders, suggesting that hydrogen in lunar soils may be measured with higher sensitivity. The results of this study show that LIBS is a versatile and powerful tool for accurate stand-off measurement of hydrogen-bearing materials on airless planetary bodies.

Laser-based techniques for the non-invasive characterisation of grisaille paints on stained-glass windows

Grisaille was the first paint applied on stained-glass panels, used in Europe since the twelfth century. Historical written sources described the use of iron and copper together with a high lead-silica base glass in the grisailles production. This project aims to study the evolution of the grisaille paint composition throughout time and the changes in the raw materials used in their production using non-destructive and non-invasive techniques. To achieve this objective, 23 grisaille samples dated from the 13th to the twentieth centuries from nine different countries (Portugal, Poland, United Kingdom, Sweden, Norway, Belgium, Low Countries, Germany, and France) were studied by means of micro particle-induced X-ray emission (μ-PIXE), micro energy dispersive X-ray fluorescence (μ-EDXRF), laser-induced breakdown spectroscopy (LIBS), laser-induced fluorescence (LIF), non-linear optical microscopy (NLOM) in the modality of multiphoton excitation fluorescence (MPEF) and optical microscopy (OM). The results showed that it was possible to identify compositional differences and patterns throughout the samples when compared with literature results. The preference for using copper in central and south-central European countries and the addition of new compounds (CoO, Cr2O3, MnO) as colouring agents since the nineteenth century was verified. The LIBS analyses allow the identification of boron on two samples, confirming the change of base glass components since the seventeenth century. The NLOM-MPEF showed the capability of this technique to measure the grisaille paint layers’ thickness. This non-invasive multi-analytical and complementary approach proves itself efficient in identifying changes in the grisaille’s composition throughout time, which can be interpreted as changes in the raw materials and manufacture used in the production of these paint materials.

A plasma self-confinement method induced by mutual extrusion of shock waves for liquid analysis of LIBS

To overcome the problems of poor plasma stability and low measurement repeatability caused by fluctuation and sputtering of liquid, a method called plasma self-confinement is proposed for liquid measurement by laser-induced breakdown spectroscopy (LIBS) in this work. With the help of shadow images, it was found that the liquid target could be returned to a calm state in a very short time, and the plasma back shock wave could be suppressed effectively. A quantitative analysis of the sodium chromate solution showed that the self-absorption could be reduced and the repeatability and sensitivity could be improved by plasma self-confinement mode LIBS when compared with liquid sheet mode LIBS.

Discrimination of tooth composition through temporally shaped femtosecond laser-induced breakdown spectroscopy

Dental caries has attracted widespread concern because of its universality. However, the current diagnosis of dental caries depends largely on naked eyes and dentists' experience, which causes considerable randomness and inaccuracy in the diagnosis. In this study, temporally shaped double pulse (DP) femtosecond laser-induced breakdown spectroscopy (LIBS) has been used for tooth composition detection for the first time. Under the laser fluence of 20 J/cm2, the spectra intensity for DP LIBS with a pulse delay of 200 ps was 13 times higher than that of single pulse. For further prediction, the detection model based on DP LIBS and partial least squares discrimination analysis could discriminate dentin, enamel, and caries with a prediction accuracy of above 90%. This method may provide rapid and accurate feedback to dentists for real-time diagnosis in the future.

Using Femtosecond Laser Light-Activated Materials: The Biomimetic Dentin Remineralization Was Monitored by Laser-Induced Breakdown Spectroscopy.

Introduction: The purpose of this study is to investigate and compare the effects of the antimicrobial agents Moringa oleifera and bioactive glass nanoparticles activated by femtosecond laser light on the biomimetic dentin remineralization using teeth having carious dentin ICDAS code 3. Methods and Materials: A total of 27 dentin surface samples were divided into three groups: the first group was treated with a Moringa oleifera extract, while the second group was treated with bioactive glass nanoparticles, and as for the control group, the third group received no additional agent. All groups were subjected to femtosecond laser light at three different wavelengths: 390 nm, 445 nm, and 780 nm. The photoactivation of each sample was achieved using the femtosecond laser light for 5 min with an average power rating of 300 mW, a pulse duration of 100 fs, and a pulse repetition rate of 80 Hz. The mineral content of the samples was obtained and analyzed using the laser-induced breakdown spectroscopy (LIBS). The LIBS analysis was conducted with the following laser light parameters: average power of ~215 mW, wavelength of 532 nm, pulse duration of 10 ns, and a pulse repetition rate of 10 Hz. Results: Most studied samples exhibited a relative increase in the mineral content that may enhance biomimetic remineralization. Moringa oleifera photoactivated by femtosecond laser light at 445 nm achieved a significant increase in mineral content. Conclusion: Using the femtosecond laser light to activate the relatively cheap and commercially available antimicrobial agent Moringa oleifera supports the strategy of minimal invasive approaches for the treatment and biomimetic remineralization of carious dentin ICDAS code 3.

Using biospeckle and LIBS techniques with artificial intelligence to monitor phthalocyanine-gold nanoconjugates as a new drug delivery mediator for in vivo PDT

Photodynamic therapy (PDT) is a promising treatment method that generates reactive oxygen species by exciting a photosensitizer in the presence of light. The positive treatment outcome of PDT is enhanced by the photosensitizer’s ability to get out quickly from normal tissue. This study non-destructively evaluated the biocompatibility of novel synthesized phthalocyanine-gold nanoconjugates (Pc-Au NCs) as a drug delivery mediator for in vivo PDT. We first proposed a novel noncontact and safe biospeckle optical imaging technique to visualize the quantitative changes in the internal dynamics of biological tissue in response to PDT treatment. Second, laser-induced breakdown spectroscopy (LIBS) was utilized to emphasize the accumulation of gold nanoparticles (Au NPs) within the normal and cancerous tissue, which in turn verifies the cytotoxic and treatment effects of the Pc-Au NCs. The biospeckle images and LIBS spectra were obtained from tumor and normal tissues of male BALB/c malignancy-bearing mice before and after exposure to PDT. Then, they were statistically treated via different artificial intelligence techniques. For biospeckle analysis, the proposed method was established from the combination of second and higher-order statistical features extracted from the gray-level co-occurrence matrix (GLCM) and local contrast analysis (LCA), respectively, through principal component analysis (PCA). Regarding LIBS analysis, the powerful, most popular ensemble sequential learning algorithm Adaptive Boost was implemented on highly uncorrelated variables extracted from the raw spectra. The results, confirmed by the histological investigation, indicated the potential of the biospeckle and LIBS statistical properties in demonstrating the efficiency of the Pc-Au NCs as a drug delivery mediator for in vivo PDT.

Plasma ion emission enhancements of Zr using microwave-enhanced laser-induced breakdown spectroscopy

In nuclear debris decommissioning, remote analysis using laser-induced breakdown spectroscopy (LIBS) guarantees the in-situ measurement of nuclear fuel debris inside the unit core. For nuclear fuel debris analysis, the detailed ion emission of Zr is essential owing to the proximity of the emission lines to U isotopes. In this study, Zr ion emissions were analyzed using microwave-enhanced LIBS with microlasers and standard yttrium aluminum garnet (YAG) lasers at different laser wavelengths (1064 nm and 532 nm). When the microwave expanded the microlaser-produced plume, the plasma emission and signal-to-noise ratio (SNR) enhancement were sustained for more than 1.0 ms, allowing analysis of ion emission. The results showed that ion emission was sustained by microwaves at the same rate as atomic emission. The ionization effects of microwaves on the LIBS analysis were revealed in the high-resolution spectrum measurements with resolving powers of 50,000–150,000. The enhancement coefficient, SNR, and intensity ratio Zr II/Zr I confirmed enhanced ionization using microwaves. At shorter laser wavelengths, microwaves suggestively increased ion emissions.

Geochemical identification and classification of cherts using handheld laser induced breakdown spectroscopy (LIBS) supported by supervised machine learning algorithms

The elemental analysis of cherts is very important for understanding their geological history, formation and origin. In this work, chert samples collected from a mining complex located in the Gargano promontory (Apulia, Italy) have been investigated by laser-induced breakdown spectroscopy (LIBS) using a commercial handheld (h) LIBS instrument. In order to discriminate chert samples according to their mining site, the broadband LIBS spectra acquired on the specimens were subjected to multivariate data analysis. In particular, machine learning (ML) algorithms, including discriminant analysis (DA), support vector machine (SVM), and k-nearest neighbors (KNN), were applied to the data set from the averaged LIBS spectra of each sample dimensionally reduced by principal components analysis (PCA). Among the classifiers tested, the highest accuracy (72.34%) in identifying the chemical features of five different chert suites and discriminating their sources was achieved by Leave-One-Out Cross-Validation (LOO-CV) using the cosine KNN ML algorithm. The exclusion of PC1, which appeared to be mainly influenced by elements featuring large intra-class variation and engraved the clusterization, allowed to improve the accuracy of the classification reaching the value of 80.85% using the linear DA algorithm. The classification and discrimination between 2 classes (1 × 1) reached a high rate of correct predictions, which implied that this discrimination could be used as a subsequent mean to confirm if the class predicted in the previously performed multiclass classification was correct. In conclusion, the results of this study demonstrated that even chemically similar geological materials could be discriminated using LIBS analysis combined with appropriate multivariate chemometric data processing, in particular with the aim of recognizing and differentiating specific geological chert sources and identifying the origin of chert archaeological artifacts.

Improving LIBS analysis of non-flat heterogeneous samples by signals mapping.

Heterogeneous material analysis by the laser-induced breakdown spectroscopy (LIBS) technique is challenging in real practice due to requirements for representative sampling and non-flat surfaces of the samples. Methods complementary to LIBS (plasma imaging, plasma acoustics, sample surface color imaging) have been introduced to improve zinc (Zn) determination in soybean grist material by LIBS. The detailed statistical study revealed that atomic/ionic lines emission and other LIBS signals were distributed normally except for acoustics signals. The correlation between LIBS and complementary signals was rather poor due to the large variability of the particle properties of soybean grist material. Still, analyte line normalization on plasma background emission was rather simple and effective for Zn analysis but required a few hundred spot samplings for representative Zn quantification. Non-flat heterogeneous samples (soybean grist pellets) were analyzed by LIBS mapping but it was demonstrated that the choice of sampling area is crucial for reliably analyte determination.