Computational Materials Science

The proliferation of computing power is enabling exciting new approaches to the characterization and design of materials.

Computational methods already play a central role in many materials studies and will only become more pervasive as computer power advances in the decades ahead. We are engaged in the development and application of methods to compute the atomic and electronic structure of materials. Recent applications include materials for electronic applications, nano-electromechanics and energy. We are also leveraging new developments in statistics and machine learning to understand complex simulations and accelerate the design of materials.   

Assistant Professor Evan Reed's group is engaged in theory and modeling of materials using atom-based methods. Recent focus of the research is:

• Monolayer and few layer materials (i.e. graphene, MoS₂) for electronics, NEMS and energy applications.
• Materials at conditions of high temperatures, electromagnetic fields and pressures, including shock compression.
• Materials informatics and machine learning to understand complex simulations and predict materials properties.