Biography: I am a professor in the Department of Physics and Astronomy at Brigham Young University (BYU).
Before coming to BYU, I was an assistant professor at Northern Arizona University (NAU). Prior to my academic
appointments, I worked in the Solid State Theory Group with Alex Zunger at the National Renewable Energy Laboratory. I recieved
a Ph.D. from Univ. of California, Davis under Barry M. Klein.
Teaching: I love teaching anything in physics curriculum, but my primary teaching-related interests are computational physics and scientific computing, solid-state physics, general education science (such as BYU's PS100 course), group-theory, statistical and thermal physics, and advanced mathematical physics.
Research: My research foci include high-throughput computational materials science, developing algorithms for alloy modeling, thermodynamic simulations, lattice-configuration enumeration, and using compressive sensing for building physical models. I am a co-developer of the UNCLE code for cluster expansion modeling.
High-throughput computational materials science (HTCMS) applies quantum-mechanical calculations (Density-Functional Theory, DFT) to a vast number of potential structures and materials combinations to build databases of results that can then be mined, either directly or machine learning techniques, to find promising new materials that can be verified in the laboratory. HTCMS requires extensive computing facilities, an automatic framework for generating, storing, and analyzing the results, and state of the art DFT codes. (See aflowlib.org and this review in Nature Materials.)
Alloy modeling in my group utilizes HTCMS and cluster expansion. CE-flash: An automatic framework combined with a Bayesian-inference-based compressive sensing algorithm for model building has made it possible to generate alloy models at an unprecedented rate and without any human interaction.
In collaboration with Rodney Forcade, we developed an efficient algorithm for enumerating derivative superstructures of any lattice. This has immediate application in lattice-gas models like the cluster expansion but has been used to generate trial structures for high-throughput and combinatorial searches by other groups. It can also be applied to special quasirandom structure generation and site-occupancy disorder studies.
Our group is currently funded by the NSF-DMR (World Materials Network program and ACI fellowship), a DOD Multidisciplinary university research initiative (MURI) award, and by NETL. We are looking for postdocs and and Ph.D. students.