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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
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Summary
This summary is machine-generated.

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.

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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.