Development of a statistical mechanics based method to explore in physically relevant ways the ways in which colloidal particles interact. Efficient design of particle interactions for self assembly in a variety of systems.
Stochastic studies of dislocation mobility in BCC alloys
Nuclear & Radiological Engineering at Georgia Tech George W. Woodruff School of Mechanical Engineering
Professor Qi’s research fields are investigations of the mechanical and chemical properties of materials by applying theoretical and computational tools, including first-principles calculations, atomistic simulations and multiscale modeling. His major research interests are quantitative understanding of the intrinsic electronic/atomistic mechanisms for the mechanical deformation, phase transformation and chemical degradation (corrosion/oxidation) of advanced alloys and other structural/functional materials. Currently he is focusing on the studies of deformation defects and interfaces in materials under extreme conditions, such as high stress and/or chemically active environment, where the materials behaviors and properties can be dramatically different than those predicted by classical theories and models. He is also developing the numerical methods to integrate these electronic/atomistic results with large-scale simulations and experimental characterizations in order to design materials with improved mechanical performances and chemical stabilities.
Don Siegel is an Associate Professor affiliated with the Mechanical Engineering Department and the Department of Material Science and Engineering. His research targets the discovery, characterization, and understanding of novel materials for energy-related applications. These efforts primarily employ atomic scale modeling to predict thermodynamic properties and kinetics. These data provide the necessary ingredients for identifying performance limiting mechanisms and for the “virtual screening” of candidate compounds having desired properties. Prof. Siegel is currently exploring several varieties of energy storage materials, lightweight structural alloys, and materials suitable for use in carbon capture applications.
Thornton’s research focuses on computational and theoretical investigations of the evolution of microstructures and nanostructures during processing and operation of materials. These investigations facilitate the understanding of the underlying physics of materials and their performance, which will aid us in designing advanced materials with desirable properties and in developing manufacturing processes that would enable their fabrication. The topics include growth and coarsening of precipitates, evolution of morphologically and topologically complex systems, microstructure-based simulations of electrochemical systems such as batteries, and self-assembly of quantum dots and other nanoscale phenomena during heteroepitaxy of semiconductors. These projects involve advanced computational methods and large-scale simulations performed on high-performance computational platforms, and insights provide a means for material design and optimization.
His group uses first-principles computational methods and high-performance computing resources to predictively model the structural, electronic, and optical properties of bulk materials and nanostructures. The goal is to understand, predict, and optimize the properties of novel electronic, optoelectronic, photovoltaic, and thermoelectric materials.