Speaker: Anton Van der Ven, Professor

Affiliation: Materials Department, UC Santa Barbara

Understanding Electrochemical Energy Storage Materials With First Principles Statistical Mechanics

The ability to predict important thermodynamic and kinetic properties of electrode and electrolyte materials from first principles is providing opportunities to explore and design new battery concepts. Electrode materials for Li, Na and Mg ion batteries undergo a series of phase transformations as a result of large changes in concentration during each charge and discharge cycle. The mechanisms of these phase transformations remain poorly understood but usually rely on a delicate interplay between cation diffusion, nucleation and interface migration. Non-intercalation reaction mechanisms in general are often accompanied by substantial hysteresis and sluggish rate capabilities. First-principles computational tools are proving invaluable as a complement to experiment in isolating crystallographic, thermodynamic and kinetic proper-ties of new electrode materials that cause hysteresis and slow charge and discharge rates. In this talk, I will illustrate how the application of first-principles statistical mechanics can generate crucial insights about dynamic processes within electrodes and enable the design of new electrochemical energy devices. The approach relies on coarse graining schemes to connect properties at the atomic and electronic scale to phenomenological descriptions of kinetic processes. I will also briefly highlight examples related to structural alloys where these approaches have proven valuable.

About the Speaker

Anton Van der Ven is professor in the Materials Department at UCSB. He obtained a Ph.D. in Materials Science from MIT and an engineering degree in Metallurgy and Applied Materials Science from the University of Louvain, Belgium. He joined the University of Michigan as an assistant professor in 2005, following a post doc at MIT, and subsequently moved to the Materials Department at UCSB in 2013. Van der Ven’s research interests are in the area of computational materials science with a focus on developing and applying first-principles statistical mechanics methods to predict properties of materials for energy storage as well as high temperature structural applications.