Poster

Topology in ASE: enabling high-throughput data generation for classical MD

Yashasvi S. Ranawat,1 Ygor M. Jaques,1 and Adam S. Foster1,2
1Department of Applied Physics, Aalto University, Finland
2WPI Nano Life Science Institute (WPI-NanoLSI), Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan

High-throughput computational methods have catapulted discovery of materials [1]. The computational methods have relied on first-principles density functional theory (DFT) [2] to validate the results. However, for molecular dynamics (MD) at longer time-scales, and in systems with massive amount of atoms, the DFT methods are computationally intensive and, hence, infeasible. Here, classical interactions, governed by forcefields, are employed [3]. These forcefields rely on topology, like atom labels/bonds/angles/dihedrals/impropers etc, in the system to determine the forces and the energies. We introduce topology handling in ASE [4]. This allows for simpler setting up of systems with their topology data for an atomistic simulation. We apply this to prepare a database of defects on calcite [1014] surface to study their behaviour under water.

References:
  1. Curtarolo, S. et al. The high-throughput highway to computational materials design. Nature Materials 12, 191–201 (2013). doi:10.1038/nmat3568
  2. W. Kohn, A. D. Becke, and R. G. Parr, The Journal of Physical Chemistry 100, 12974 (1996). doi:10.1021/jp960669l
  3. F. F. Abraham, Advances in Physics 35, 1 (1986). doi:10.1080/00018738600101851
  4. https://gitlab.com/ase/ase/merge_requests/1321

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