University of California
Low-Energy, AI-Informed Phase Transitions (LEAP)
University of California
Low-Energy, AI-Informed Phase Transitions (LEAP)
The University of California has awarded $6 million to our LEAP project through its new AI Science at Scale initiative. Led by Professor Ram Seshadri at UC Santa Barbara, LEAP aims to accelerate discovery of low-energy switching materials by training specialized large language models on theory, experimental data, and simulations. By focusing on topological materials with unconventional electron behavior, our team seeks to identify promising candidates for energy-efficient chip design.Â
People:
Assistant Professor of Physics & Astronomy; Director, UCI Quantum Materials Center
Associate Professor, Chemical and Materials Engineering, UC Merced
Postdoctoral Scholar, Materials, UC Santa Barbara (Quantum Foundry / Seshadri Group)
Zhengding Hu
Postdoctoral Scholar
Computer Science & Engineering, UC San Diego.
Zhengyi Bian
Postdoctoral Scholar, UC Berkeley
zhengyi.bian@berkeley.edu
Tools and links:
Here is https://tritondft.com/, an agentic AI system for DFT calculations.