Abstract
Apart from radiation, which constitutes the primary source of information in laser-induced breakdown spectroscopy, the process is accompanied by secondary processes such as shock wave generation and sound emission. In this manuscript, we explore the possibility of relating plasma properties with the sound from the shock waves in multiple materials, from metals to minerals. By analyzing the behavior of shock wave sound from homogeneous reference metallic targets, we investigate the relation between plasma properties and sound signal, demonstrating that distinct materials and plasma characteristics correspond to distinct plasma sound fingerprints. © Published under licence by IOP Publishing Ltd.

Abstract
While laser-induced breakdown spectroscopy is often used as a standalone technique, recent years saw an increasing interest in their combination with additional techniques towards multimodal sensing solutions capable of enhancing the capabilities of this technological solution. In this work, we try to identify possible synergies that arise from merging the analysis of laser-induced breakdown spectroscopy with that from a hyperspectral scanning of the sample, comparing it with the performance of standalone solutions. Having investigated the multimodal approach for a case study involving the identification of lithium minerals, our preliminary results demonstrate that while both solutions can provide reasonable results for qualitative mineral identification, they feature advantages and disadvantages that shall be taken into further consideration. Nevertheless, when working in collaboration, the results enclosed suggest that an integrated tandem solution can be an interesting tool for material analysis for research and industrial applications, combining the best of both instruments. © Published under licence by IOP Publishing Ltd.

Abstract
The possibility to map the element distribution on a sample surface is one of the interesting applications of laser-induced breakdown spectroscopy that has been extensively explored in recent years. In this manuscript, we explore the combination of photogrammetry and LIBS techniques for the creation of a three-dimensional model of the map of the elements on the surface of the sample. Using a dedicated photogrammetry solution and software, we reconstruct the three-dimensional model of the mineral sample whose mesh is later exploited for the interactive interpretation of the results. Then, making use of Paraview software, which integrates production algorithms and computing performance in a unified solution for scientific purposes, we establish a process pipeline that allows the creation of an interactive three-dimensional model with the spatial distribution of the target elements on top of the sample surface. Our results demonstrate that combining these two techniques can give us a valuable resource for better qualitative analysis and insight, providing an innovative three-dimensional modeling solution that may open the door to a new range of possibilities, from quality control technology involving alloys and mechanical parts to interactive teaching environments for geo and biosciences, just to name a few examples. © Published under licence by IOP Publishing Ltd.

Abstract
Spectral imaging is a broad term that refers to the use of a spectroscopy technique to analyze sample surfaces, collecting and representing spatially referenced signals. Depending on the technique utilized, it allows the user to reveal features and properties of objects that are invisible to the human eye, such as chemical or molecular composition. However, the interpretability and interaction with the results are often limited to screen visualization of two-dimensional representations. To surpass such limitations, augmented reality emerges as a promising technology, assisted by recent developments in the integration of spectral imaging datasets onto three-dimensional models. Building on this context, this work explores the integration of spectral imaging with augmented reality, aiming to create an immersive toolset to increase the interpretability and interactivity of the results of spectral imaging analysis. The procedure follows a two-step approach, starting from the integration of spectral maps onto a three-dimensional models, and proceeding with the development of an interactive interface to allow immersive visualization and interaction with the results. The approach and tool developed present the opportunity for a user-centric extension of reality, enabling more intuitive and comprehensive analyses with the potential to drive advancements in various research domains.

Abstract
Management and reuse of wood waste can be a challenging process due to the frequent presence of hazardous contaminants. Conventional detection methods are often limited by the need for excessive sample preparation and lengthy and expensive analysis. Laser-induced Breakdown Spectroscopy (LIBS) is a rapid and micro- destructive technique that can be a promising alternative, providing in-situ and real-time analysis, with minimal to no sample preparation required. In this study, LIBS imaging was used to analyze wood waste samples to determine the presence of contaminants such as As, Ba, Cd, Cr, Cu, Hg, Pb, Sb, and Ti. For this analysis, a methodology based on detecting three lines per element was developed, offering a screening method that can be easily adapted to perform qualitative analysis in industrial contexts with high throughput operations. For the LIBS experimental lines selection, control and reference samples, and a pilot set of 10 wood wastes were analysed. Results were validated by two different X-ray Fluorescence (XRF) systems, an imaging XRF and a handheld XRF, that provided spatial elemental information and spectral information, respectively. The results obtained highlighted LIBS ability to detect highly contaminated samples and the importance of using a 3-line criteria to mitigate spectral interferences and discard outliers. To increase the dataset, a LIBS large-scale study was performed using 100 samples. These results were only corroborated by the XRF-handheld system, as it provides a faster alternative. In particular cases, ICP-MS analysis was also performed. The success rates achieved, mostly above 88 %, confirm the capability of LIBS to perform this analysis, contributing to more sustainable waste management practices and facilitating the quick identifi- cation and remediation of contaminated materials.

Abstract
Combining data from different sensing modalities has been a promising research topic for building better and more reliable data-driven models. In particular, it is known that multimodal spectral imaging can improve the analytical capabilities of standalone spectroscopy techniques through fusion, hyphenation, or knowledge distillation techniques. In this manuscript, we focus on the latter, exploring how one can increase the performance of a Laser-induced Breakdown Spectroscopy system for mineral classification problems using additional spectral imaging techniques. Specifically, focusing on a scenario where Raman spectroscopy delivers accurate mineral classification performance, we show how to deploy a knowledge distillation pipeline where Raman spectroscopy may act as an autonomous supervisor for LIBS. For a case study concerning a challenging Li-bearing mineral identification of spodumene and petalite, our results demonstrate the advantages of this method in improving the performance of a single-technique system. LIBS trained with labels obtained by Raman presents an enhanced classification performance. Furthermore, leveraging the interpretability of the model deployed, the workflow opens opportunities for the deployment of assisted feature discovery pipelines, which may impact future academic and industrial applications.