HIWAY-2-MAT: High-throughput combinatorial and autonomous pathways in Solid State Chemistry
Coordinator: Guilhem DEZANNEAU
SPMS – Structures, Propriétés et Modélisation des Solides
(UMR 8580 CentraleSupélec/CNRS/Univ. Paris Saclay)
Keywords: Combinatorial synthesis, oxides, autonomous research, low energy consumption
In recent years, original approaches have been developed to accelerate the discovery of new materials: the combinatorial route and the autonomous research route. The combinatorial route allows the production of libraries of materials formally containing several hundred or even thousands of compositions. Autonomous research involves the use of materials discovery robots including automated synthesis modules, characterization of structural and functional properties, and using AI models to choose areas to explore.
Such a combination makes it possible to explore complex multidimensional spaces to optimize the composition of materials without any human intervention. In this area of research, Europe is far behind the United States and China.
Our ambition in this focused project is to both use high-throughput combinatorial approaches and develop autonomous configurations to explore material composition spaces for low-power applications. Concretely, we will apply the proposed approaches to accelerate the discovery of oxide materials for smart windows, smart sensors, low-power lighting and electronic systems. The parallelized combinatorial path will be implemented and completed with AI models. Interactions with other targeted projects will make it possible to extend this strategy around oxides to other categories of materials. Finally, in addition to automating the discovery of new materials, this strategy should help researchers gain statistically grounded knowledge and understanding of the composition-(micro)structure-property relationship.