Laser-Induced Breakdown Spectroscopy (LIBS) is an analytical technique that has the potential to detect all the elements present in the periodic table. The limit of detection can go below a few ppm and this regardless of the physical phase of the analyzed sample (solid, liquid or gas). Its simplicity of use, its rapidity to get results and its versatility provide this technique with attractive features. The technique is currently developed for applications in a large number of domains such as online control, spatial explorations and the environment. However the weakness of the LIBS technique, compared to other more conventional ones, is still its difficulty in providing reliable quantitative results, especially for inhomogeneous and complex matrix such as organic or biological materials. The work presented in this thesis includes a study of the properties of plasma induced from different organic materials. First, a study of the plasma induced on the surface of a Nylon sample at short time delays (~ns) was carried out using the time-resolved shadowgraph technique for different experimental parameters (laser energy, pulse duration, wavelength). Then, a complete diagnostics of the plasma was performed using the plasma emission spectroscopy. A detailed analysis of the emission spectra at different detection delays allowed us to determine the evolution of the temperatures of the different species in the plasma (atoms, ions and molecules). The homogeneity and the local thermodynamic equilibrium within the plasma was then experimentally checked and validated. We demonstrated that the optimisation of the signalto- noise ratio and a quantitative procedure, such as the calibration-free LIBS, can be put in place within a properly chosen detection window. In our experiments, such optimised detection configuration was further employed to record LIBS spectra from different families of polymer in order to identify and classify them. For this purpose, the chemometrics procedure of artificial neural networks (ANN) was used to process the recorded LIBS spectroscopic data. The promising results obtained in this thesis makes LIBS stand out as a potentially useful tool for real time identification of plastic materials. Finally, this work can also be considered as a base for the further studies of more complex materials such as biological tissues with LIBS.

La spectrométrie de plasma induit par laser, plus connue sous le nom de LIBS (l’acronyme du terme en anglais Laser-Induced Breakdown Spectroscopy) est une technique analytique qui permet la détection de l’ensemble des éléments du tableau périodique avec des limites de détection de l’ordre du ppm et ceci sur tous types d’échantillons qu’ils soient liquides, solides ou gazeux. Sa simplicité de mise en œuvre, sa rapidité et sa versatilité en font une technique très attractive avec un fort potentiel en termes d’applications que ce soit pour le contrôle en ligne, l’environnement ou l’exploration spatiale. Son point faible reste cependant son manque de fiabilité dans l’analyse quantitative, en particulier lors de l’étude d’échantillons hétérogènes ou de matrices complexes telles que les matrices organiques. Ce travail de thèse propose une étude des propriétés des plasmas induit par laser sur différentes familles de polymères. Une étude du plasma au temps court (~ns) par ombroscopie est tout d’abord présentée, ceci pour différents paramètres expérimentaux (énergie laser, durée d’impulsion, longueur d’onde). Un diagnostic complet du plasma par spectrométrie d’émission est ensuite détaillé pour différents délais de détection et montre que la mesure des températures des différentes espèces du plasma (atomique, ionique et moléculaire) permet de vérifier, dans certaines conditions, les hypothèses d’homogénéité et de l’équilibre thermodynamique local. Ceci permet alors la mise en place de procédures quantitatives telles que la méthode dite sans calibration (calibration free LIBS) tout en optimisant le rapport signal sur bruit de la mesure LIBS. Dans nos expériences cette optimisation est mise à profit pour l’identification de différentes familles de polymères en utilisant, pour le traitement des données de la spectroscopie LIBS, la méthode chimiométrique des réseaux de neurones artificiels. Les résultats obtenus, très prometteurs, permettent d’envisager l’utilisation de la LIBS pour l’identification en temps réel des matières plastiques sur chaine de tri. Par ailleurs et de manière plus générale, ce travail pourrait constituer une base solide pour aller étudier d’autres matériaux organiques plus complexes tels que des tissus biologiques. / Laser-Induced Breakdown Spectroscopy (LIBS) is an analytical technique that has the potential to detect all the elements present in the periodic table. The limit of detection can go below a few ppm and this regardless of the physical phase of the analyzed sample (solid, liquid or gas). Its simplicity of use, its rapidity to get results and its versatility provide this technique with attractive features. The technique is currently developed for applications in a large number of domains such as online control, spatial explorations and the environment. However the weakness of the LIBS technique, compared to other more conventional ones, is still its difficulty in providing reliable quantitative results, especially for inhomogeneous and complex matrix such as organic or biological materials. The work presented in this thesis includes a study of the properties of plasma induced from different organic materials. First, a study of the plasma induced on the surface of a Nylon sample at short time delays (~ns) was carried out using the time-resolved shadowgraph technique for different experimental parameters (laser energy, pulse duration, wavelength). Then, a complete diagnostics of the plasma was performed using the plasma emission spectroscopy. A detailed analysis of the emission spectra at different detection delays allowed us to determine the evolution of the temperatures of the different species in the plasma (atoms, ions and molecules). The homogeneity and the local thermodynamic equilibrium within the plasma was then experimentally checked and validated. We demonstrated that the optimisation of the signalto- noise ratio and a quantitative procedure, such as the calibration-free LIBS, can be put in place within a properly chosen detection window. In our experiments, such optimised detection configuration was further employed to record LIBS spectra from different families of polymer in order to identify and classify them. For this purpose, the chemometrics procedure of artificial neural networks (ANN) was used to process the recorded LIBS spectroscopic data. The promising results obtained in this thesis makes LIBS stand out as a potentially useful tool for real time identification of plastic materials. Finally, this work can also be considered as a base for the further studies of more complex materials such as biological tissues with LIBS.