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MB-Fit: Software infrastructure for data-driven many-body potential energy functions
Ethan F Bull-Vulpe1, Marc Riera1, Andreas W Götz2
1Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA.
The Journal of Chemical Physics
|October 2, 2021
Summary
MB-Fit automates the development of accurate many-body potential energy functions (MB-PEFs) for molecular simulations. This software enables predictive modeling of molecules across different phases, enhancing computational chemistry research.
Area of Science:
- Computational chemistry
- Molecular modeling
- Quantum mechanics
Background:
- Many-body potential energy functions (MB-PEFs) integrate quantum mechanical and physics-based models for high accuracy.
- Accurate MB-PEFs are crucial for describing molecular interactions across gas, liquid, and solid phases.
Purpose of the Study:
- To present MB-Fit, a software infrastructure for automated development of MB-PEFs.
- To support the TTM-nrg (Thole-type model energy) and MB-nrg (many-body energy) theoretical frameworks.
- To facilitate predictive computer simulations for generic molecules.
Main Methods:
- Developed MB-Fit software for automated MB-PEF generation.
- Integrated data-driven short-range and physics-based long-range interactions.
- Provided interface with MBX software for energy and force calculations.
Main Results:
- MB-Fit enables automated development of TTM-nrg and MB-nrg potential energy functions.
- The software seamlessly interfaces with the MBX many-body energy and force calculator.
- Demonstrated accuracy of MB-PEFs, especially within the MB-nrg framework.
Conclusions:
- MB-Fit will enable routine predictive computer simulations of generic molecules in various phases.
- Facilitates modeling of quantum isomeric equilibria, solvation, molecular crystals, and phase diagrams.
- Advances the application of many-body methods in computational molecular science.
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