Abstract

Boosted by machine learning and neural network representations, ab-initio molecular dynamics gives new insight on the microscopic mechanisms of the ferroelectric phase transition. These studies reveal unforeseen effects of long-range strain fields and provide an atomic scale understanding of chemical disorder effects. The approach opens also the way to bottom-up multiscale formulations that do not require empirical parameterization. Examples from recent work in my group will illustrate these concepts. 

Biography

Professor Roberto Car is a world-renowned theoretical physicist acclaimed for foundational contributions to condensed matter physics and physical chemistry. He received his degree from Milan Technical University in 1971, followed by postdoctoral research at the University of Milan, École Polytechnique Fédérale de Lausanne (EPFL), and IBM’s Thomas J. Watson Research Center. He became Professor of Condensed Matter Physics at the University of Geneva in 1991, concurrently directing its Institute for Computational Materials Physics (IRRMA). Since 1999, he has served as Professor of Chemistry and Physics at Princeton University.

Professor Car is celebrated for co-developing the revolutionary Car-Parrinello molecular dynamics method with Michele Parrinello, which transformed computational simulations of materials and molecules. His pioneering work spans electronic structure theory, ab initio dynamics, and simulations of liquids and solids. His scientific leadership is recognized by memberships in the American Physical Society, Royal Society of Chemistry, and U.S. National Academy of Sciences (2016), and honors including the Hewlett-Packard Europhysics Prize (1990), APS Raman Prize (1995), Dirac Medal (2009), and ACS Award in Theoretical Chemistry (2016).