About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
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Symposium
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Bridging Scale Gaps in Multiscale Materials Modeling in the Age of Artificial Intelligence
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Presentation Title |
UF3: Fast and Interpretable MLIP for High-Performance Molecular Dynamics |
Author(s) |
Ajinkya C. Hire, Hendrik Krass, Stephen Xie, Jason Gibson, Michael MacIsaac, Sung Hoon Jung, Matthias Rupp, Richard Hennig |
On-Site Speaker (Planned) |
Ajinkya C. Hire |
Abstract Scope |
Ultra-fast forcefield (UF3) is a fast and interpretable machine-learned interatomic potential (MLIP) that expresses many-body energy as a function of effective two- and three-body potential. In this talk, I will present the LAMMPS implementation of UF3 MLIP for both CPUs and GPUs. Our benchmark simulations show that UF3 outperforms state-of-the-art MLIPs in terms of molecular dynamics speed for potentials of similar accuracy. UF3 also scales efficiently with respect to the number of atoms in the simulation on GPUs. I will also outline our UltraFast workflow of fitting UF3 potentials to genetic algorithm-generated ab-initio data using the Nb-Sn system as an example, highlighting the data efficiency of UF3. The UltraFast workflow allows the development of an MLIP in less than two minutes on a single core machine from a dataset consisting of 4300 structures and 80000 forces. This short featurization and training times enable the rapid optimization of model hyperparameters. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, |