IMX Seminar Series - Novel mathematics to discover novel materials

Large-scale density-functional theory (DFT) simulations are an indispensable tool to discover novel materials and occupy a noteworthy share of the world's supercomputing resources. Obtaining not only efficient, but also reliable DFT algorithms has thus become of elevated importance: at the supercomputing scale any failing simulations not only waste substantial energy resources, but these failures are also an obstacle to reliable automation and thus overall delay research outcomes. In this talk we will introduce a mathematical point of view on DFT simulations and discuss two examples where mathematical research has contributed to developing especially robust numerical methods for high-throughput screening.

Bio: Michael Herbst obtained a PhD in Theoretical Chemistry from Heidelberg University in 2018, after which he moved on to two postdoctoral research stays in Applied Mathematics. From 2019 till 2021 he worked with Éric Cancès (École des Ponts, Paris, France) and from 2021 till 2023 he stayed in the group of Benjamin Stamm (RWTH Aachen). Since March 2023 he is an assistant professor in the Institute of Mathematics and the Institute of Materials at EPFL. His current research spans broadly in the field of materials simulations concerning numerical error control and uncertainty quantification of DFT models as well as the development of efficient and robust algorithms for high-throughput materials screening.