Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces

Article English OPEN
Li, Zhenwei ; Kermode, James R. ; De Vita, Alessandro (2015)

We present a molecular dynamics scheme which combines first-principles and machine-learning (ML) techniques in a single information-efficient approach. Forces on atoms are either predicted by Bayesian inference or, if necessary, computed by on-the-fly quantum-mechanical (QM) calculations and added to a growing ML database, whose completeness is, thus, never required. As a result, the scheme is accurate and general, while progressively fewer QM calls are needed when a new chemical process is encountered for the second and subsequent times, as demonstrated by tests on crystalline and molten silicon.
  • References (40)
    40 references, page 1 of 4

    Basel, Klingelbergstrasse 80, CH-4056 Basel, Switzerland. [1] M. C. Payne, M. P. Teter, D. C. Allan, T. Arias, and

    J. Joannopoulos, Rev. Mod. Phys. 64, 1045 (1992). [2] K. Burke, J. Chem. Phys. 136, 150901 (2012). [3] R. Car and M. Parrinello, Phys. Rev. Lett. 55, 2471 (1985). [4] E. Hernández, M. J. Gillan, and C. M. Goringe, Phys. Rev.

    B 55, 13485 (1997). [5] J. M. Soler, E. Artacho, J. D. Gale, A. García, J. Junquera,

    14, 2745 (2002). [6] C.-K. Skylaris, P. D. Haynes, A. A. Mostofi, and M. C.

    Payne, J. Chem. Phys. 122, 084119 (2005). [7] D. R. Bowler and T. Miyazaki, Rep. Prog. Phys. 75, 036503

    (2012). [8] N. Hine, P. Haynes, A. A. Mostofi, C.-K. Skylaris, and M.

    Payne, Comput. Phys. Commun. 180, 1041 (2009). [9] F. Ercolessi and J. B. Adams, Europhys. Lett. 26, 583 (1994). [10] M. Z. Bazant, E. Kaxiras, and J. F. Justo, Phys. Rev. B 56,

    8542 (1997). [11] Y. Mishin, D. Farkas, M. J. Mehl, and D. A. Papaconstan-

    topoulos, Phys. Rev. B 59, 3393 (1999). [12] A. C. T. van Duin, S. Dasgupta, F. Lorant, and W. A.

    Goddard, J. Phys. Chem. A 105, 9396 (2001). [13] P. Tangney and S. Scandolo, J. Chem. Phys. 117, 8898 (2002). [14] M. Finnis, Interatomic forces in condensed matter, in

  • Metrics
    No metrics available