Computational Materials Science and Design Research Group

The Computational Materials Science and Design (CMSD) research group at Mines is headed by Prof. Garritt J. Tucker. The CMSD group integrates high-performance computing and theory to discover the fundamental structure-property relationships of materials that will enable the predictive design of advanced materials with tunable properties. Of particular interest are materials where defects and interfacial-driven properties can be effectively tuned or controlled to enable property enhancement, such as nanocrystalline alloys, multicomponent laminates, materials for energy storage, 2D materials, and hierarchical metals. At the core of the CMSD group approach is to develop collaborations and programs that effectively mesh computation with experiment to tailor functional materials.

Recent work by Prof. Tucker and his group has provided unprecedented understanding into a new defect in layered materials that influences not only the strength of the material, but also other advantageous properties such as strain reversibility and kinking non-linear elastic response. Their work has also addressed many outstanding questions regarding grain boundary properties and structure in metals, and extended this idea to modeling realistic material microstructures. A significant focus has been on providing a fundamental understanding of the mechanics and physics of nanocrystalline alloys – quantifying the roles of grain boundaries, dislocations, and twinning.

CMSD research has recently highlighted how microstructural features can be altered to systemically tailor the operative nanoscale deformation mechanisms within metallic materials. Prof. Tucker’s research group leverages a number of computational methods to research materials and their properties, such as density functional theory, atomistic modeling (e.g., Molecular Dynamics and Statics), phase-field models, and a number of multiscale modeling approaches. Beyond those traditional computational methods, Prof. Tucker and his research group also employ innovative post-processing tools for data analysis and visualization, and pursue novel informatics techniques to build predictive methodologies for materials design.