FAIRChem v2 UMA: Universal Interatomic Potential for Molecules, Catalysts, Materials, Vibrations, and Molecular Dynamics
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FAIRChem v2 introduces UMA, a universal machine-learning interatomic potential capable of simulating molecules, catalysis, and inorganic materials within a single framework. The tutorial demonstrates its application across computational chemistry workflows, including energy prediction, geometry optimization, vibrational analysis, surface adsorption, and molecular dynamics using GPU acceleration.
The tutorial explores FAIRChem v2 and the UMA universal machine-learning interatomic potential as a unified framework for atomistic simulation across molecular chemistry, catalysis, and inorganic materials. It configures an environment, authenticates with Hugging Face to access the gated UMA model weights, and initializes task-specific calculators for the omol, oc20, and omat domains. The same pretrained potential is applied to workflows including single-point energy and force prediction, molecular geometry optimization, spin-state comparison, reaction-energy estimation, vibrational analysis, surface adsorption, crystal-cell relaxation, equation-of-state fitting, molecular dynamics, and potential-energy surface scanning. The tutorial integrates FAIRChem with the Atomic Simulation Environment to manage atomic structures, optimizers, constraints, thermodynamic calculations, and trajectory analysis while using GPU acceleration.
- Сокращения
- UMA = Universal Machine-learning Interatomic potential — Универсальный меж-атомный потенциал машинного обучения
- ASE = Atomic Simulation Environment — Среда атомного моделирования
- GPU = Graphics Processing Unit — Графический процессор
- MD = Molecular Dynamics — Молекулярная динамика
- DFT = Density Functional Theory — Теория функционала плотности
Source: MarkTechPost —
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