Materials Science · Physics
Large-scale atomistic simulation of dislocation core structure in face-centered cubic metal with Deep Potential method
Fenglin Deng, Hongyu Wu, Ri He, Peijun Yang +1
2022-09-13
Materials Science · Physics
Efficiency, Accuracy, and Transferability of Machine Learning Potentials: Application to Dislocations and Cracks in Iron
Lei Zhang, Gábor Csányi, Erik van der Giessen, Francesco Maresca
2023-11-07
Materials Science · Physics
Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries
Nada Alghamdi, Paolo de Angelis, Pietro Asinari, Eliodoro Chiavazzo
2026-04-10
Materials Science · Physics
Machine Learned Potential for High-Throughput Phonon Calculations of Metal-Organic Frameworks
Alin Marin Elena, Prathami Divakar Kamath, Théo Jaffrelot Inizan, Andrew S. Rosen +2
2025-02-28
Chemical Physics · Physics
DFT Accuracy on Crystal Structure Prediction with Machine Learning Interatomic Potentials
Laurence I. Midgley, Chen Lin, J. Harry Moore, Flaviano Della Pia +7
2026-05-29
Materials Science · Physics
MACE Foundation Models for Lattice Dynamics: A Benchmark Study on Double Halide Perovskites
Jack Yang, Ziqi Yin, Lei Ao, Sean Li
2025-10-22
Materials Science · Physics
Atomic cluster expansion force field based thermal property material design with density functional theory level accuracy in non-equilibrium molecular dynamics calculations over sub-million atoms
Takumi Araki, Shinnosuke Hattori, Toshio Nishi, Yoshihiro Kudo
2023-09-21
Materials Science · Physics
Atomic cluster expansion for quantum-accurate large-scale simulations of carbon
Minaam Qamar, Matous Mrovec, Yury Lysogorskiy, Anton Bochkarev +1
2023-06-13
Materials Science · Physics
Atomic Cluster Expansion for a General-Purpose Interatomic Potential of Magnesium
Eslam Ibrahim, Yury Lysogorskiy, Matous Mrovec, Ralf Drautz
2023-05-08
Materials Science · Physics
A Comparative Study of Molecular Dynamics Approaches for Simulating Ionic Conductivity in Solid Lithium Electrolytes
Dounia Shaaban Kabakibo, Félix Therrien, Yoshua Bengio, Michel Côté +3
2026-03-31
Materials Science · Physics
Benchmarking Universal Machine Learning Interatomic Potentials for Supported Nanoparticles: Decoupling Energy Accuracy from Structural Exploration
Jiayan Xu, Abhirup Patra, Amar Deep Pathak, Sharan Shetty +2
2026-03-26
Chemical Physics · Physics
PyGSC: A Python tool for correcting Kohn-Sham orbital energies by mitigating the delocalization error of density functional approximations
Zipeng An, Xiaolong Yang, Xiao Zheng, Weitao Yang
2026-04-07
Chemical Physics · Physics
MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry
Ilyes Batatia, William J. Baldwin, Domantas Kuryla, Joseph Hart +9
2026-02-24
Atomic and Molecular Clusters · Physics
Machine-Learned Potential Energy Surfaces for Free Sodium Clusters with Density Functional Accuracy: Applications to Melting
Balasaheb J. Nagare, Sajeev Chacko, Dilip. G. Kanhere
2023-09-19
Chemical Physics · Physics
A symmetry-preserving and transferable representation for learning the Kohn-Sham density matrix
Liwei Zhang, Patrizia Mazzeo, Michele Nottoli, Edoardo Cignoni +2
2025-03-12
Materials Science · Physics
Achieving Empirical Potential Efficiency with DFT Accuracy: A Neuroevolution Potential for the $\alpha$-Fe--C--H System
Fan-Shun Meng, Shuhei Shinzato, Zhiqiang Zhao, Jun-Ping Du +3
2025-10-23
Chemical Physics · Physics
How Accurate Are DFT Forces? Unexpectedly Large Uncertainties in Molecular Datasets
Domantas Kuryla, Fabian Berger, Gábor Csányi, Angelos Michaelides
2025-10-23
Machine Learning · Computer Science
Accelerating Long-Term Molecular Dynamics with Physics-Informed Time-Series Forecasting
Hung Le, Sherif Abbas, Minh Hoang Nguyen, Van Dai Do +2
2025-10-03
Materials Science · Physics
Geometries of edge and mixed dislocations in bcc Fe from first principles calculations
Michael R. Fellinger, Anne Marie Z. Tan, Louis G. Hector, Dallas R. Trinkle
2018-12-05