Computational Materials Group

Welcome to the Computational Materials Group! 

We are an interdisciplinary research group in the Department of Electrical and Computer Engineering at SUNY Binghamton. We are also affiliated with the Materials Science and Engineering Program.

Our group develop and apply first-principles computational methods aided by machine learning approaches to design semiconductor materials for energy conversion and quantum information applications. 

Research 

First-principles calculations allow direct mechanistic insight into the experimental observations and predictions for material composition and synthesizing conditions targeting specific applications. The materials properties we explore mainly include optical and kinetic properties, with a special focus on how to accurately capture the phonon contributions and electron-phonon coupling at surfaces, interfaces, and defects in semiconductors. These are critical factors that affect the performance and longevity of optoelectronic devices. The properties are calculated from density functional theory, ab initio molecular dynamics simulations aided by machine learning methods. We are actively hiring graduate students and postdocs to perform computational materials research and develop machine learning tools to drive the AI-aided material design and development.

Acknowledgements

Funding

Computational Resource