English

Sparse random Fourier features based interatomic potentials for high entropy alloys

Materials Science 2023-12-04 v2

Abstract

Computational modeling of high entropy alloys (HEA) is challenging given the scalability issues of Density functional theory (DFT) and the non-availability of Interatomic potentials (IP) for molecular dynamics simulations (MD). This work presents a computationally efficient IP for modeling complex elemental interactions present in HEAs. The proposed random features-based IP can accurately model melting behaviour along with various process-related defects. The disordering of atoms during the melting process was simulated. Predicted atomic forces are within 0.08 eV/\unicodexC5\unicode{xC5} of corresponding DFT forces. MD simulations predictions of mechanical and thermal properties are within 7%\% of the DFT values. High-temperature self-diffusion in the alloy system was investigated using the IP. A novel sparse model is also proposed which reduces the computational cost by 94%\% without compromising on the force prediction accuracy.

Keywords

Cite

@article{arxiv.2302.06844,
  title  = {Sparse random Fourier features based interatomic potentials for high entropy alloys},
  author = {Gurjot Dhaliwal and Abu Anand and Prasanth B. Nair and Chandra Veer Singh},
  journal= {arXiv preprint arXiv:2302.06844},
  year   = {2023}
}
R2 v1 2026-06-28T08:39:31.921Z