Tomás José Lopes

Abstract
Imaging the spatial distribution of chemical elements at a sample surface is a common application of laserinduced breakdown spectroscopy with vast scientific and technological applications. Yet, typical imaging solutions only explore the creation of two-dimensional maps, which can limit the interpretability of the results and further diagnostics in three-dimensional settings. Within this context, this work explores the combination of spectral imaging techniques and photogrammetry to deploy a versatile solution for the creation of threedimensional spectral imaging models. First, by making use of a numerical algorithm that is able to match features in the spectral image with those of the three-dimensional model, we show how to match the mesh from distinct sensor modalities. Then, we describe a possible visualization workflow, making use of dedicated photogrammetry and visualization software to easily deploy interactive models. Overall, the results demonstrate the versatility of our approach and pave for the development of novel spectral imaging diagnostic strategies that are able to deliver better qualitative analysis and insight in the three-dimensional space.

Abstract
Fast and precise identification of minerals in geological samples is of paramount importance for the study of rock constituents and for technological applications in the context of mining. However, analyzing samples based only on the extrinsic properties of the minerals such as color can often be insufficient, making additional analysis crucial to improve the accuracy of the methods. In this context, Laser-induced breakdown spectroscopy mapping is an interesting technique to perform the study of the distribution of the chemical elements in sample surfaces, thus allowing deeper insights to help the process of mineral identification. In this work, we present the development and deployment of a processing pipeline and algorithm to identify spatial regions of the same mineralogical composition through chemical information in a fast and automatic way. Furthermore, by providing the necessary labels to the results on a training sample, we can turn this unsupervised methodology into a classifier that can be used to generalize and classify minerals in similar but unseen samples. The results obtained show good accuracy in reproducing the expected mineral regions and extend the interpretability of previous unsupervised methods with a visualization tool for cluster assignment, thus paving for future applications in contexts requiring high-throughput mineral identification systems, such as mining.

Abstract
Evaluating the efficiency of surface treatments is a problem of paramount importance for the cork stopper industry. Generically, these treatments create coatings that aim to enhance the impermeability and lubrification of cork stoppers. Yet, current methods of surface analysis are typically time-consuming, destructive, have poor representativity or rely on indirect approaches. In this work, the use of a laser-induced breakdown spectroscopy (LIBS) imaging solution is explored for evaluating the presence of coating along the cylindrical surface and in depth. To test it, several cork stoppers with different shaped areas of untreated surface were analyzed by LIBS, making a rectangular grid of spots with multiple shots per spot, to try to identify the correspondent shape. Results show that this technique can detect the untreated area along with other features, such as leakage and holes, allowing for a high success rate of identification and for its performance at different depths, paving the way for future industry-grade quality control solutions with more complex surface analysis.

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.