Wang Research Group

Welcome to the Wang 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. 


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 catalytic properties, with a special focus on how to accurately capture the phonon contributions and electron-phonon coupling at surfaces, interfaces, and defects in semiconductors. The properties are calculated from density functional theory, ab initio molecular dynamics simulations aided by machine learning methods. We have interests in the following areas. 

Quantum defects 

Point defects in wide-bandgap semiconductors can act as artificial atoms in the solid state and have been demonstrated for applications in quantum computing, quantum communication, and nanoscale sensors. We aim to provide the theoretical understanding and the computational design of the structure and growth of defects in materials for quantum technologies. 

Quantum materials

2D materials with diverse material properties offer opportunities in quantum information science. Our goal is to build heterostructures of 2D materials and explore properties including the strain, interfacial charge transfer, and electron-phonon coupling that affect the quantum properties of the 2D materials.

Materials for solar energy conversion

Halide perovskites has high composition flexibility and tunable band gap, which is a potential candidate for applications in optoelectronics. We develop computational methods to calculate and propose material compositions and synthesizing conditions for better light absorption capability, thermodynamic stability, and defect tolerance of perovskites.

Thermal conductivity of semiconductor materials

With the development of high-power and high-frequency electronics, electronic packaging materials are crucial to ensure the reliability and performance of the devices. We aim to use first-principles computational methods to enhance the thermal transport properties of semiconductor materials and interfaces for electronic packaging applications. 



Computational Resource