382 citations · 383 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025★ 1 cited
Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems
Hossein Tahmasbi, Andreas Knüpfer, Thomas D. Kühne +1
The rapid emergence of universal Machine Learning Interatomic Potentials (uMLIPs) has transformed materials modeling. However, a comprehensive understanding of their generalization…
physics.chem-ph2018★ 382 cited
i-PI 2.0: A Universal Force Engine for Advanced Molecular Simulations
Venkat Kapil, Mariana Rossi, Ondrej Marsalek +23
Progress in the atomic-scale modelling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomi…