Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS

Guénolé J, Nöhring WG, Vaid A, Houlle F, Xie Z, Prakash A, Bitzek E (2020)


Publication Type: Journal article

Publication year: 2020

Journal

Book Volume: 175

Article Number: 109584

DOI: 10.1016/j.commatsci.2020.109584

Abstract

In atomistic simulations, pseudo-dynamical relaxation schemes often exhibit better performance and accuracy in finding local minima than line-search-based descent algorithms like steepest descent or conjugate gradient. Here, an improved version of the fast inertial relaxation engine (FIRE ) and its implementation within the open-source atomistic simulation code LAMMPS is presented. It is shown that the correct choice of time integration scheme and minimization parameters is crucial for the performance of FIRE.

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APA:

Guénolé, J., Nöhring, W.G., Vaid, A., Houlle, F., Xie, Z., Prakash, A., & Bitzek, E. (2020). Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS. Computational Materials Science, 175. https://dx.doi.org/10.1016/j.commatsci.2020.109584

MLA:

Guénolé, Julien, et al. "Assessment and optimization of the fast inertial relaxation engine (FIRE) for energy minimization in atomistic simulations and its implementation in LAMMPS." Computational Materials Science 175 (2020).

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