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Moment Tensor Potentials: a class of systematically improvable interatomic potentials

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arxiv 1512.06054 v2 pith:HB3JP24T submitted 2015-12-18 physics.comp-ph cond-mat.mtrl-scics.NAmath.NA

classification physics.comp-phcond-mat.mtrl-scics.NAmath.NA
keywords potentialsinteratomicclassimprovablepropertiesquantum-mechanicalsystematicallyaccurate
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Density functional theory offers a very accurate way of computing materials properties from first principles. However, it is too expensive for modelling large-scale molecular systems whose properties are, in contrast, computed using interatomic potentials. The present paper considers, from a mathematical point of view, the problem of constructing interatomic potentials that approximate a given quantum-mechanical interaction model. In particular, a new class of systematically improvable potentials is proposed, analyzed, and tested on an existing quantum-mechanical database.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The structure and migration of twin boundaries in tetragonal $\beta$-Sn: an application of machine learning based interatomic potentials

    cond-mat.mtrl-sci 2025-05 conditional novelty 7.0 of 10

    New machine learning potentials for beta-tin reproduce the experimentally observed structure and growth morphology of deformation twins, showing that twin growth proceeds via double-layer twinning disconnections and l...

  2. Machine-learning interatomic potential for radiation damage and defects in tungsten

    physics.comp-ph 2019-08 accept novelty 6.0 of 10

    A new Gaussian Approximation Potential for tungsten reproduces defect, surface, liquid, and short-range repulsion energetics near DFT accuracy, making it suitable for radiation damage molecular dynamics.

  3. Prediction of Mechanical Properties and Thermodynamic Stability of Ti-N system using MTP Interatomic Potential

    cond-mat.mtrl-sci 2025-07 conditional novelty 5.0 of 10

    A moment tensor potential trained on DFT data predicts Ti-N formation energies with test RMSE 6.8 meV/atom and suggests intermediate Ti-N phases across the full composition range are thermodynamically stable.

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