- Developing generative models to overcome difficulties in modeling complex interface structures.
- Aiming to understand the nature of short-range order of alloys in hydrogen environments to provide new insight into hydrogen embrittlement.
- Developing predictive models of the coupled magnetic and structural phase transformations in magnetic shape memory alloys.
- Characterizing wide-band gap materials using first-principles approaches.
- Investigating the link between vibrational dynamics and superionic diffusion.
- Modeling disordered systems to investigate defects in energy materials.
- High-throughput screening of novel thermoelectrics.
- Designing computational workflows to screen promising thermoelectric materials.
- Using few-shot and generative machine learning methods to accelerate materials design.
Background
The group focuses on fundamental problems at the intersection of materials science, mechanics, and condensed matter physics. They use computation, modeling, and simulation to gain insight into the predictive relationships between structure and function, enabling materials discovery, design, and optimization. Their interests include materials for energy conversion and storage, thermoelectrics, solid oxide fuel and electrolysis cells, and wide band gap semiconductors for power electronics.
Miscellany
The group is dedicated to providing a welcoming, respectful, and inclusive environment. They value strong relationships, mentoring, close collaboration, and diverse perspectives as they work towards creating a sustainable and healthy future through robust, transparent science.