Research Description:

Our group’s research combines quantum-chemical calculations, high-throughput computing, and machine learning to accelerate the discovery of novel materials that can address global challenges in energy and sustainability.

As quantum-chemical engineers, we specifically focus on the computationally guided design of atomically programmable materials with novel electronic properties for applications in catalysis, chemical separations, and energy storage technologies. We have a complementary interest in understanding the stability and synthesizability of novel materials to guide experiments and to increase the impact of virtual screening studies. On the more fundamental side, we regularly develop and contribute to new computational tools that enable more actionable recommendations to be made in materials discovery campaigns.

Members of our group leverage recent advances in data science, atomistic computational methods, materials chemistry, inorganic chemistry, and solid-state physics to automate the exploration of materials space. To realize the full potential of our materials discovery platforms, our group is highly collaborative; we work alongside both theorists and experimentalists across disciplinary boundaries as well as with tech companies in the areas of deep learning and high-performance computing.