Advanced chemometric methodologies on single shot hyphenated LIBS data for rapid and reliable characterization of plastic classes.

BACKGROUND: Plastic Solid Waste (PSW) sorting is a procedure of paramount importance in the mechanical recycling process of plastics waste. The major limitation of the techniques relying on physical properties of plastics is the time taken for analysis and poor accuracy. Spectroscopy has been shown to be a suitable method in plastic sorting due to its atomic and molecular characterization capabilities, and ability to give results in very short time scales. However, for practical applications it is essential to translate this technique into an automatic technology, by combining it with advanced chemometric tools which can give observer independent judgement. RESULTS: The indigenously developed bi-model Laser Induced Breakdown Spectroscopy (LIBS)-Raman system with single source and single detector can record the LIBS-Raman spectral signals in single-shot mode in a total time frame of 20 ms. Out of the combinations of Principal Component Analysis (PCA) and Partial Least Squares (PLS) with Logistic Regression (LR), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Partial Least Squares-Discriminant Analysis (PLS-DA) based classifiers, the PLS-DA based model showed the maximum classification accuracy with 95 % based on LIBS data and 100 % based on Raman data. The reliability of the model was assessed using 4-fold cross-validation which showed a sensitivity of 90.28 % and specificity of 98.29 % for predictions based on LIBS data, and 99 % sensitivity and 99.82 % specificity for predictions relying on Raman data. SIGNIFICANCE: The results show how the combination of multimodal spectroscopy with chemometric analysis enhances the applicability of spectroscopic techniques for plastic sorting. The classification model successfully classified seven types of post-consumer plastic samples based on combined LIBS and Raman data. With the home-built software for automated prediction, the system takes less than a second to predict the plastic type illustrating the potential of the method for translation to regular routine industrial applications.

Regenerative biomineralization potential of commercially available remineralizing agents as a preventive treatment approach for tooth erosion - An in vitro laser-induced breakdown spectroscopy analysis.

Context: In today's era, erosion is the most prevalent type of tooth wear. The prevention of demineralization with biomineralization is the most desired treatment. Aim: The aim of this study is to evaluate and compare the surface remineralization potential of two remineralizing agents - self-assembling peptide P11-4 (SAP P11-4) and calcium silicate plus sodium phosphate (CSSP) salts on intact and demineralized enamel using laser-induced breakdown spectroscopy (LIBS). Subjects and Methods: Sixteen maxillary premolars were decoronated and split into buccal and palatal halves embedded in acrylic resin with a total sample size of 32 designated into Group 1 (intact teeth) and Group 2 (demineralized teeth). Further subdivision into Groups 1a and 2a (SAP P11-4 group [n = 8]); Groups 1b and 2b (CSSP group [n = 8]), Group 2 was first exposed to Coca-Cola. Then, all groups were subjected to experimental LIBS. Groups 1a and 2a were treated with SAP P11-4 based product, i.e., CURODONT™ PROTECT gel. Groups 1b and 2b were treated with CSSP-based products regimen, i.e., REGENERATE Enamel Science™ Advanced Toothpaste and Advanced Enamel Serum. The LIBS assessment was redone for all groups to attain a change in Ca and P values. Statistical Analysis Used: Inferential statistics were done using Wilcoxon signed-rank test (Before-After product application) and Mann-Whitney U-test (between the groups). Results: According to the statistical evaluation there was a statistically significant difference (P < 0.05), in Ca and P values in demineralized teeth when both SAP P11-4 and CSSP groups were evaluated. Although Ca values exhibited a significant difference in intact teeth, P did not exhibit a significant difference on the application of both remineralizing agents. The remineralizing potential between the two agents, SAP P11-4 and CSSP groups. There was no statistically significant difference ( P <0.05) observed between the two agent's remineralization potential for intact and demineralized teeth. Conclusion: SAP P11-4 and CSSP have the potential to remineralize both intact and demineralized enamel. There was increased remineralization in demineralized samples subjected to erosion.

Integrated LIBS-Raman spectroscopy: A comprehensive approach to monitor microplastics and heavy metal contamination in water resources.

The increased use of plastic products and global industrial conditions have contaminated natural resources, especially water, with pollutants such as microplastics and trace elements, including heavy metals. Hence, continuous monitoring of water samples is an urgent requirement. However, the existing microplastic-heavy metal monitoring methodologies require discrete and sophisticated sampling approaches. The article proposes a multi-modal LIBS-Raman spectroscopy system for detecting microplastics and heavy metals from water resources with unified sampling and pre-processing approaches. The accomplishment of the detection process is using a single instrument by exploiting the trace element affinity of microplastics, which operates in an integrated methodology to monitor water samples for microplastic-heavy metal contamination. The polypropylene (PP), polyethylene (PE), and polyethylene terephthalate (PET) plastic types dominate the identified microplastics from different sampling spots: in an estuary formed by the Swarna River near Kalmadi (Malpe) in Udupi district, and from River Netravathi in Mangalore, Dakshina Kannada District, Karnataka, India. The detected trace elements from microplastic surfaces include heavy metals such as Al, Zn, Cu, Ni, Mn, and Cr and other elements counting Na, Mg, Ca, and Li. The system could record concentrations of trace elements down to 10 ppm, and comparing results with the conventional technique of Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) confirms the ability of the system to detect trace elements from microplastic surfaces. In addition, comparing results with direct LIBS analysis of water from the sampling site shows better results in microplastic-based trace element detection.

Development of an inter-confirmatory plastic characterization system using spectroscopic techniques for waste management.

Ever-accumulating amounts of plastic waste raises alarming concern over environmental and public health. A practical solution for addressing this threat is recycling, and the success of an industry-oriented plastic recycling system relies greatly on the accuracy of the waste sorting technique adapted. We propose a multi-modal spectroscopic sensor which combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy in a single optical platform for characterizing plastics based on elemental and molecular information to assist the plastic identification-sorting process in recycling industries. The unique geometry of the system makes it compact and cost-effective for dual spectroscopy. The performance of the system in classifying industrially important plastic classes counting PP, PC, PLA, Nylon-1 1, and PMMA is evaluated, followed by the application of the same in real-world plastics comprising PET, HDPE, and PP in different chemical-physical conditions where the system consumes less than 30 ms for acquiring LIBS-Raman signals. The evaluation of the system in characterizing commuting samples shows promising results to be applied in industrial conditions in future. The study on effect of physical-chemical conditions of plastic wastes in characterizing them using the system shows the necessity for combining multiple techniques together. The proposal is not to determine the paramount methodology to characterize and sort plastics, but to demonstrate the advantages of dual-spectroscopy sensors in such applications. The outcomes of the study suggest that the system developed herein has the potential of emerging as an industrial-level plastic waste sorting sensor.