Description du sujet de thèse

The precise design of photoluminescent materials with well-defined photoemission colors is essential for various applications, including LED technology, biomedicine, telecommunications, and anticounterfeiting. In certain cases, maintaining a stable color under changing environmental conditions is critical. For example, in LED technology, phosphors must retain their emission color across different temperatures and excitation wavelengths. Conversely, some applications benefit from phosphors that exhibit significant color shifts in response to specific stimuli. This is particularly useful for photoluminescent thermometers in biomedicine, where emission color changes with temperature, or for anticounterfeiting, where phosphors display distinct colors under different excitation wavelengths.
High-entropy materials (HEMs) represent a fascinating and rapidly evolving class of materials that are attracting increasing interest in materials science. Their unique structure, characterized by high disorder where multiple elements occupy the same crystallographic site, gives these materials exceptional properties such as enhanced mechanical strength, high-temperature stability, and excellent corrosion resistance. However, the photoluminescence properties of these materials remain largely unexplored despite their potential for various applications.
As part of the ANR AI-Unclon project, the goal of the PhD student will be to use a robotic platform and machine learning (ML) tools to prepare new inorganic phosphors in a high-throughput manner. The collected data will be used to predict and simulate the evolution of photoluminescence colors based on the composition of high-entropy materials. These materials, which exhibit variability in their emissions under different excitation energies and significant changes in their luminescence properties depending on synthesis conditions, are particularly promising for applications such as anti-counterfeiting, LED lighting, and displays.
At the Institut des Matériaux de Nantes Jean Rouxel, the PhD student will be responsible for collecting and analyzing experimental data using a robotic platform dedicated to the synthesis and characterization of inorganic materials. This position offers a unique opportunity to gain interdisciplinary experience in materials science, and artificial intelligence.

Contexte de travail

The Institut des Matériaux de Nantes Jean Rouxel (https://www.cnrs-imn.fr/) brings together more than 150 researchers and doctoral students. Through the design and characterization of new materials, the laboratory's approach aims to optimize a wide range of properties for applications such as photovoltaic cells, fuel cells, batteries for electric vehicles, nanotechnologies, and optical materials like LEDs. The MIOPS team, where the work will be conducted, specializes in the synthesis and characterization of inorganic and organic-inorganic hybrid materials with optical, optoelectronic, or magnetic properties. The contract is funded by ANR.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.