1.3k citations · 3.1k across the 22 of their papers we have counts for
23 papers
MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark Platform
Yuan Chiang, Tobias Kreiman, Christine Zhang +11
Machine learning interatomic potentials (MLIPs) have revolutionized molecular and materials modeling, but existing benchmarks suffer from data leakage, limited transferability, and…
A foundation model for atomistic materials chemistry
Ilyes Batatia, Philipp Benner, Yuan Chiang +85
Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much…
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner +7
The rapid adoption of machine learning (ML) in domain sciences necessitates best practices and standardized benchmarking for performance evaluation. We present Matbench Discovery,…
Designing transparent conductors using forbidden optical transitions
Rachel Woods-Robinson, Yihuang Xiong, Jimmy-Xuan Shen +6
Many semiconductors present weak or forbidden transitions at their fundamental band gaps, inducing a widened region of transparency. This occurs in high-performing n-type transpare…
Grain Boundary Effects in Dealloying Metals: A Multi-Phase Field Study
Nathan Bieberdorf, Mark D. Asta, Laurent Capolungo
A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying. The model proposed extends upon the original approach of Gesl…
The Bright Side and the Dark Side of Hybrid Organic Inorganic Perovskites
Wladek Walukiewicz, Shu Wang, Xinchun Wu +6
The previously developed bistable amphoteric native defect (BAND) model is used for a comprehensive explanation of the unique photophysical properties and for understanding the rem…