3 papers
cond-mat.mtrl-sci2026
Dataset-aware entropy-maximized active learning for machine-learned interatomic potentials
Meiyan Wang, Rishi Rao, Li Zhu
We present an active learning framework for efficiently generating training data for machine-learned interatomic potentials (MLIPs). The method combines local entropy-driven molecu…
cond-mat.mtrl-sci2026
Physics-Constrained Self-Energy Warm Starts for Charge-Self-Consistent DFT+DMFT: Application to Iron at Core Conditions
Rishi Rao, Li Zhu
Charge self-consistent DFT+DMFT quantitatively captures dynamical electronic correlations in real materials, but its cost precludes the large-scale thermodynamic sampling required…
cond-mat.str-el2024
Phase transitions of correlated systems from graph neural networks with quantum embedding techniques
Rishi Rao, Li Zhu
Correlated systems represent a class of materials that are difficult to describe through traditional electronic structure methods. The computational demand to simulate the structur…