Computational materials design : Recent advances, challenges and opportunities

Materials science continues to rely on empirical knowledge for the design of advanced engineering alloys. At the macro-scale, the lack of rigorous phenomenology limits our ability to predict material properties. At the atomistic scale, mechanisms of kinetic and mechanical phenomena such as nucleation and deformation elude us. In this talk I will highlight recent advances in computational materials science that enable the rigorous and rational design of high-performance engineering alloys across length scales. Materials used in automotive, electrochemical and high-temperature applications will be used to illustrate the crucial insights that can be gained from first-principles models. The talk will conclude with a discussion of the challenges that must be overcome to accurately predict the properties of complex materials.
Bio: Anirudh received a B.Tech. in Metallurgical and Materials Engineering from the Indian Institute of Technology, Madras, a M.S in Materials Science and Engineering from the University of Michigan, Ann Arbor and a Ph.D. in Materials from the University of California, Santa Barbara. He set up the laboratory of materials design and simulation (MADES) at EPFL in 2022. His research interests are in the computational design and discovery of advanced engineering materials.