Since 2017, IFPEN has fully entered the race for accelerated design of new materials with models creating links between synthesis and effective properties. Its AI and materials teams propose new tools for the numerical generation and characterization of materials microstructures.
This approach realistically considers the microstructure to capture morphological and topological details at scales of interest. Numerical models link to synthesis or processing parameters, and estimate textural and usage properties. In this talk, we will discuss the general ideas of this approach, examples of multi-scale microstructures, and some recent work on numerical textural characterizations such as tortuosity and deep learning accelerated physisorption simulation.