Date: July 26, 2019 ǀ 14:00-15:00
Location: Faculty Club (4th Floor), TUM Institute for Advanced Study, Lichtenbergstrasse 2 a, 85748 Garching, Tel +49.89.289.10550
Organization: TUM-IAS and Rudolf Diesel Industry Fellow Dr. Filippo Maglia (BMW Group)
Admission is free. No registration required.
Title: Computational discovery of materials for energy conversion and storage from transport properties of ions, electrons and phonons.
Speaker: Prof. Boris Kozinsky, Harvard University, School of Engineering and Applied Sciences, 29 Oxford Street, Cambridge, MA 02138 (bkoz@seas.harvard.edu).
Boris Kozinsky is Associate Prof. at the Harvard School of Engineering and Applied Sciences since 2018. He studied at MIT for his B.S. degrees in Physics, Mathematics, and Electrical Engineering and Computer Science, and received his PhD degree in Physics also from MIT in 2007. He then established and led the atomistic computational materials science team at Bosch Research in Cambridge MA before moving to Harvard. He works at the intersection of fundamental physics of materials properties, efficient computational algorithms, and data-intensive informatics approaches. His group develops and uses atomistic and electronic structure computations and machine learning algorithms for understanding and distilling the design rules governing quantum-level microscopic effects, particularly ionic, electronic and thermal transport in materials for energy applications. His work on development and application of computational methods led to fundamental advances and over 50 patents applications in a wide range of materials systems, including 1D and 2D materials, piezoelectrics, thermoelectrics, batteries, super-ionic conductors, catalysts, and functional polymers.
Abstract: Design of next-generation energy technologies requires deep understanding of atomic-level mechanisms that govern the core materials functions. In this talk I will illustrate how new atomistic first-principles computational methods, when made fast and automatic, can accelerate discovery of new materials.
The first example will focus on atomistic-level understanding of ionic transport mechanisms and design principles for enabling high ionic conductivity in solid-state battery electrolytes. Strong ion-ion interaction, geometric frustration, disorder and collective motion are emerging as common themes in recent investigations of super-ionic materials. I will present our recent efforts to gain mechanistic understanding of the influence of correlation, disorder and frustration on ionic transport in solid polymer and ceramic electrolyte materials. We find that ionic dynamics in polymer electrolytes is strongly influenced by the host polymer dynamics and the strong coupling between mobile component species and the host polymer. In the domain of inorganic electrolytes, we investigate how and why disordered materials have vastly different transport properties than their crystalline counterparts, aiming to develop design rules for optimization.
In the second example I will introduce a novel simplified approach for computing electronic transport properties of complex semiconductors and low-dimensional quantum materials. This method allowed us to discover new thermoelectric alloy compositions with leading performance and stability. The computational approach achieves good accuracy and transferability while greatly reducing complexity and computation cost compared to existing methods. The first-principles calculations of the electron-phonon coupling demonstrate that the energy dependence of the electron relaxation time varies significantly with chemical composition and carrier concentration, suggesting that it is necessary to go beyond the commonly used approximations to search and optimize materials' composition, carrier concentration, and microstructure.