LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

By Aidan P. Thompson, Hasan Metin Aktulga, R. Berger, Dan S. Bolintineanu, W. M. Brown, P. Crozier, P. J. I. Veld, Axel Kohlmeyer, S. Moore, T. D. Nguyen and 5 more. Computer Physics Communications, 2022

1,155 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a928228cc5f44fd6e34bb1f29acef1257414a620

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Simon L. Batzner
2. Albert Musaelian
3. Anders Johansson
4. Lixin Sun
5. Boris Kozinsky
6. Cameron J. Owen
7. Mordechai Kornbluth
8. Ilyes Batatia

Citations in the corpus

• Learning local equivariant representations for large-scale atomistic dynamics (2022, methodology): “Molecular Dynamics simulations were performed in LAMMPS [65] using the pair style pair allegro implemented in the Allegro interface, available at https://github.com/mir-group/pair_allegro .”