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Extending the accuracy of the SNAP interatomic potential form.

Mitchell A Wood1, Aidan P Thompson1

  • 1Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA.

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|July 2, 2018
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Summary
This summary is machine-generated.

A new quadratic Spectral Neighbor Analysis Potential (SNAP) offers higher accuracy for interatomic simulations than the linear form. This enhanced classical potential provides improved accuracy with only a small increase in computational cost.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Condensed Matter Physics

Background:

  • The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential.
  • It models atomic energy based on bispectrum components of neighboring atoms.
  • Existing SNAP potentials use a linear formulation.

Purpose of the Study:

  • To introduce and evaluate an extended SNAP potential form.
  • This extension incorporates quadratic terms into the bispectrum components.
  • The goal is to enhance accuracy while managing computational expense.

Main Methods:

  • Developed a quadratic extension of the SNAP interatomic potential.
  • Compared the accuracy and computational cost against the linear SNAP form.
  • Utilized extensive training data for tantalum structures.
  • Performed a robust cross-validation analysis to assess potential quality.

Main Results:

  • The quadratic SNAP form significantly increases accuracy compared to the linear SNAP.
  • This improvement in accuracy is achieved with only a modest rise in computational cost.
  • The quadratic SNAP form requires more training data to prevent overfitting, similar to neural network potentials.
  • Cross-validation confirmed the high quality of the new potential form.

Conclusions:

  • The quadratic SNAP potential represents a significant advancement in classical interatomic potentials.
  • It offers a more accurate description of atomic interactions than the linear SNAP.
  • This improved accuracy comes with manageable computational overhead, making it suitable for large-scale simulations.