NRT-DESE: Computational Materials Education and Training - Bridging Methods and Applications (COMET)

NRT-DESE: Computational Materials Education and Training - Bridging Methods and Applications (COMET)

The discovery of new materials offers solutions to pressing technological problems facing our society. This National Science Foundation Research Traineeship (NRT) award prepares Ph.D. students at Pennsylvania State University with the skills to contribute to national efforts to discover and develop advanced materials with greater efficiency and lower cost. Density functional theory, a theory based in quantum mechanics that can accurately predict materials properties, is a core pillar of the effort. Addressing a need for density functional theory literacy across science and engineering, the program will bridge a gap between fundamental advances in density functional theory and its application for materials design. As capstone projects, trainees will learn to develop online teaching materials that will be available worldwide. Through internships with industry, interdisciplinary team projects, and international workshops, trainees will develop the combination of fundamental and applied research on a variety of tools that will promote collaborative innovation---across industry and academia, and across the globe.

This program involves faculty from three colleges and six departments focused on interdisciplinary research on oxide interfaces, nanomaterials, organic electronics, and force-field development. The research and training will provide graduate students with a firm foundation in density functional theory based computational materials science in all its aspects, ranging from the development of density functional theory methods to its direct use to solve problems in materials science, to its integration into multi-scale modeling involving theory, empirical force-field development, and simulations. Additionally, this program will develop new coursework as well as a Computational Materials Science track within the Computational Science graduate minor and establish a professional development seminar series that will ultimately be available to all science and engineering graduate students.