activity
20222026
most citedComposition based oxidation state prediction of materials using deep learning

1 citations · 2 across the 3 of their papers we have counts for

collaborators
Showing 2026Show all

1 paper · 1 filter

cond-mat.mtrl-sci2026

Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery

Jeffrey Hu, Rongzhi Dong, Ying Feng +2

Active learning (AL) has emerged as a powerful paradigm for accelerating materials discovery by iteratively steering experiments toward promising candidates, reducing the number of…