121 citations · 123 across the 5 of their papers we have counts for
5 papers
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…
Learning and retrieval for warm-starting charge-self-consistent DFT+DMFT
Rishi Rao, Li Zhu
Charge-self-consistent (CSC) DFT+DMFT delivers quantitative correlated-electron physics one configuration at a time, making ensemble sampling dependent on reliable warm starts for…
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…
Predicting New Heavy Fermion Materials within Carbon-Boron Clathrate Structures
Rishi Rao, Li Zhu
Heavy fermion materials have been a rich playground for strongly correlated physics for decades. However, engineering tunable and synthesizable heavy fermion materials remains a ch…
A fingerprint based metric for measuring similarities of crystalline structures
Li Zhu, Maximilian Amsler, Tobias Fuhrer +8
Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordi…