Richard G. Hennig
Assistant Professor of Materials Science and Engineering
Address:
126 Bard Hall
Department of Materials Science and Engineering
Cornell University
Ithaca, NY 14853-1501
Phone: 607-255-6429
Fax: 607-255-2365
E-mail: rhennig@cornell.edu
Professor Hennig received his Diploma in Physics at the University of Göttingen in 1997 and his Ph.D. in Physics from Washington University in St. Louis in 2000. After working as a postdoctoral researcher and research scientist at Ohio State University, he joined the faculty of the Department of Materials Science and Engineering at Cornell in 2006.
Current Research
Professor Hennig’s research in computational materials science focuses on atomistic studies of defects, phase transitions, electronic properties and mechanical behavior of materials. We aim to develop computational techniques that both accurately predict materials properties and provide an estimate of their accuracy and to apply these methods to accelerated materials development and enhanced understanding of the effect of atomic-scale processes on meso and macroscale behavior. Our strengths are atomic multi-scale simulations that combine highly accurate quantum mechanical methods such as density functional theory and quantum Monte Carlo with efficient molecular dynamics simulations and saddle-point techniques.
Research Projects
Our research in computational materials science focuses on atomistic studies of defects, phase transitions, electronic properties and mechanical behavior of materials. To be useful in materials and device design, materials modeling must accurately predict crucial microscopic behavior with scales of Angstrom and nanoseconds, and feed mesoscale models to predict macroscopic response of devices on time scales up to decades. We aim to develop computational techniques that both accurately predict materials properties and provide an estimate of their accuracy and to apply these methods to accelerated materials development and enhanced understanding of the effect of atomic-scale processes on meso and macroscale behavior. The flexible approaches we employ range from efficient molecular dynamics simulations to more accurate density-functional techniques to highly accurate quantum Monte-Carlo methods. We systematically combine these methods to both increase the accuracy and efficiently scan the phase space to discover the evolution of defects and phases in materials. Current projects range from modeling martensitic transformations in transition metals, to mantle minerals under pressure, to defects in organic and compound semiconductors.