Welcome to the group of Philippe Sautet

Professor Sautet invites talented and qualified individuals to apply for undergraduate, graduate (MS and PhD) and post-doc positions in his laboratory at UCLA.

Research

Our group investigates materials for catalysts, batteries, and electronics using advanced computational chemistry methods. We employ first-principles calculations (DFT), molecular simulations (MD, MC), machine learning techniques (MLIPs, ML-based property prediction) and physics informed techniques (CE) to gain molecular-level insights into material behavior and chemical processes. Our research is driven by applications in the sustainable transformation of energy and resources.

Dr. Dongxiao Chen got selected for the IDRE Postdoctoral Fellowship which is awarded to exceptional early career researchers. Congratulations Dongxiao!

Size- and Facet-Dependent Behavior of Electron Storage at the Au/Anatase TiO₂ Interface under Ambient Conditions from Machine Learning by Qianyu Liu et al. is published in ACS Catalysis.

On the Mechanism of Reactive Sorption of H₂S on CuO (111) and (1̅11) Surfaces: A First-Principles Study by David Jiang et al. is published in Physical Chemistry Chemical Physics.

Contact

Sautet Lab at UCLA