4 papers
How Atoms Interact Within Molecules
Adil Kabylda, Malte Esders, Matteo Gori +3
Fundamental understanding of interatomic forces in molecules must emerge from quantum mechanics, yet widely used empirical force fields rely on simplified mechanistic approximation…
MBD-ML: Many-body dispersion from machine learning for molecules and materials
Evgeny Moerman, Adil Kabylda, Almaz Khabibrakhmanov +1
Van der Waals (vdW) interactions are essential for describing molecules and materials, from drug design and catalysis to battery applications. These omnipresent interactions must a…
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…
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…