3 papers
physics.soc-ph2025
AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price +65
Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, p…
physics.chem-ph2025
QCell: Comprehensive Quantum-Mechanical Dataset Spanning Diverse Biomolecular Fragments
Adil Kabylda, Sergio Suárez-Dou, Nils Davoine +2
Recent advances in machine learning force fields (MLFFs) are revolutionizing molecular simulations by bridging the gap between quantum-mechanical (QM) accuracy and the computationa…
physics.chem-ph2025
aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
Tobias Henkes, Shubham Sharma, Alexandre Tkatchenko +2
Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable referenc…