Discovery of novel two-dimensional nanomaterials using evolutionary algorithm – Predict_2D_NanoMat

Design of novel ultrathin 2D nanomaterials would be greatly accelerated if one could theoretically predict in silico new materials from the only knowledge of the chemical composition. USPEX, an evolutionary algorithm, provides a practical recipe for affordable first-principles prediction of complex structures (see USPEX website). Our project will develop two complementary axis: (1) search of novel 2D materials beyond graphene with special mechanical, electronic and thermoelectric properties, such as graphene-supported ultrathin metal oxides, isoelectronic MXenes/MAX and others inorganic-based non-layered compounds, (2) study of their stability in a chemical environment (i.e. H, O, F) and under high pressure, looking at their surface reconstruction and composition. In both french and chinese teams, a graduate and a postdoctoral researcher will be trained in this challenging field. The development of novel computational tools will be made freely available to academic researchers.