Curved-line search algorithm for ab initio atomic structure relaxation

Zhanghui Chen, Jingbo Li, Shushen Li, and Lin-Wang Wang
Phys. Rev. B 96, 115141 – Published 21 September 2017
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Abstract

Ab initio atomic relaxations often take large numbers of steps and long times to converge, especially when the initial atomic configurations are far from the local minimum or there are curved and narrow valleys in the multidimensional potentials. An atomic relaxation method based on on-the-flight force learning and a corresponding curved-line search algorithm is presented to accelerate this process. Results demonstrate the superior performance of this method for metal and magnetic clusters when compared with the conventional conjugate-gradient method.

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  • Received 30 August 2014

DOI:https://doi.org/10.1103/PhysRevB.96.115141

©2017 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Zhanghui Chen1,2, Jingbo Li2, Shushen Li2, and Lin-Wang Wang1,*

  • 1Materials Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Mail Stop 50F, Berkeley, California 94720, USA
  • 2State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, P.O. Box 912, Beijing 100083, People's Republic of China

  • *lwwang@lbl.gov

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Issue

Vol. 96, Iss. 11 — 15 September 2017

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