3 papers
physics.chem-ph2026
Multitask learning with semiempirical orbital charges enables sample-efficient MLIPs
Ihor Neporozhnii, Sjoerd Hoogland, Oleksandr Voznyy
Machine learning interatomic potentials (MLIPs) require generating computationally expensive, large-scale training datasets to accurately simulate materials and molecules. Incorpor…
cond-mat.mtrl-sci2025
High-magnitude, spatially programmable, and sustained strain engineering of 2D semiconductors
Boran Kumral, Pedro Guerra Demingos, Peter Serles +13
Crystalline two-dimensional (2D) semiconductors often combine high elasticity and in-plane strength, making them ideal for strain-induced tuning of electronic characteristics, akin…
cond-mat.mtrl-sci2024
Open Catalyst Experiments 2024 (OCx24): Bridging Experiments and Computational Models
Jehad Abed, Jiheon Kim, Muhammed Shuaibi +17
The search for low-cost, durable, and effective catalysts is essential for green hydrogen production and carbon dioxide upcycling to help in the mitigation of climate change. Disco…