Atomistic modeling based on density functional theory, often combined with molecular dynamics, has been successfully employed in physics, chemistry, and materials science for about half a century. It provides a microscopic insight to interpret experimental measurements, it can unravel structure-function relations, and it enables the access to extreme conditions.
However, atomistic modeling is hampered by large computational costs, which limit the complexity and the size– in the order of few hundred atoms – accessible to accurate and predictive electronic structure methods. Conversely, the use of empirical effective potentials gives access to million atoms models but with limited accuracy and transferability.
In this talk, I will illustrate how the introduction of Artificial Intelligence (AI) has revolutionized this paradigm by bringing together accuracy, complexity, and computational efficiency. Examples will encompass the development and use of machine learning to compute nonequilibrium energy transfer in liquids, photochemistry at the air ice interface, and thermal transport in crystalline and glassy materials. Finally, I will discuss the application of AI to the discovery of new inorganic clathrates for energy applications.
Speaker Bio: Davide Donadio is a theoretical materials scientist and professor of chemistry at UC Davis. He earned his Ph.D. in 2003 at the University of Milan with a thesis on the photosensitivity and photo-elasticity of silicate glasses by electronic structure calculations and molecular dynamics simulations. As a postdoctoral researcher at ETH Zurich (Parrinello group) and UC Davis (Galli group), he studied materials at extreme conditions, crystal nucleation, nanoscale heat transport, and thermoelectric materials. From 2010 to 2015 Dr. Donadio led the Max Planck Research Group for “Theory of nanostructures” at MPIP Mainz, investigating non-equilibrium processes at the nanoscale by molecular simulations. In 2014 he was appointed Ikerbasque professor at DIPC (Donostia, Spain), and in 2015 moved to UC Davis, where he continues his research activity on crystallization, surface chemistry, and nanophononics. He is currently an associate editor of Nanoscale and Microscale Thermophysical Engineering, and he has authored 142 peer-reviewed articles, two US patents, and three book chapters.
Dr. Donadio is a University of California Hellman fellow, UC Davis Chancellor’s fellow, Res. Corp Scialog fellow, and in2022 he was elected AAAS Fellow “For distinguished contributions to the field of computational and theoretical chemistry, particularly for theoretical modeling of materials.”