A "Transforming Energy" Lecture
by Yue Qi
July 12, 2012

Abstract

Dramatic improvements have been made in computational techniques at different scales in the past few decades. This presentation briefly overviews how computational materials modeling has been integrated with research on lightweight energy storage materials in the auto industry. By transferring parameters, equations, and insights obtained from smaller to larger scales, combining and overlapping techniques has moved materials modeling into a truly multi-scale era. To improve Al alloy forming and machining, atomic simulations were integrated into aluminum high temperature forming modeling and used to guide a coating development to machine aluminum alloys. In another case, a coarse-graining approach was developed to obtain the morphologies of hydrated Nafion for fuel cells, where the network connectivity of hydrophilic domains strongly influences the proton conductivity and mechanical property of the membrane. Materials modeling did not stop at explaining existing data or confirming experimental findings, but it made an experimentally testable prediction for optimizing material structures and processing conditions before material synthesis. Predictive capability can lead to more efficient energy conversion and longer lasting materials.

Biography

Yue Qi is a staff research scientist working on computational materials sciences at the General Motors R&D Center Materials and Processes Lab. Her research spans hard coatings, lightweight alloys, proton exchange membranes, and various nano-structured materials for energy storage. She completed her B.S. degree (materials science and computer science) at Tsinghua University, China in 1996. She received her Ph.D. in materials science (minor in computer science) from California Institute of Technology in 2001. She then joined GM as a senior research scientist.

She received the 2006 GM Campbell Award for “Advances in Nano-scale Plasticity.” She was the co-recipient of 1999 Feynman Prize in Nanotechnology for Theoretical Work with T. Cagin and Prof. W. A. Goddard III (Ph.D. advisor).