Artificial Intelligence for the Discovery of New Semiconductor Materials for Energy

Niveau : Master

Période : février/mars à Juillet/aout 2024

Context:

The Jean Rouxel Institute of Materials in Nantes (IMN) and the Laboratory of Digital Sciences (LS2N) are joining forces to propose a six-month internship in the field of researching new semiconductor materials for energy. This project aims to combine the expertise of IMN in machine learning for the discovery of new materials with the recognized skills of LS2N in the field of deep networks, including Graph Neural Networks (GNN).

Subject:

The project will leverage the advantages of Graph Neural Networks (GNN), machine learning algorithms capable of analyzing complex network structures, such as the atomic structures of materials. Collecting data on the properties of different semiconductor materials will be used to train a GNN model to predict their properties based on their atomic structure. Specifically, each atom will be represented as a node in the graph, and the connections between atoms will be represented by edges. This graphical representation of atomic structures will be used as input for the GNN model. The network’s output will be the prediction of semiconductor material properties associated with these atomic structures. This innovative approach will enable the rapid identification of promising candidates for semiconductor materials suitable for photovoltaic and thermoelectric applications.

Send your CV and motivation letter to

david.berthebaud@cnrs-imn.fr ; harold.mouchere@ls2n.fr