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Title: Curved-line search algorithm for ab initio atomic structure relaxation

Journal Article · · Physical Review B
 [1];  [2];  [2];  [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Chinese Academy of Sciences (CAS), Beijing (China). State Key Lab. of Superlattices and Microstructures
  2. Chinese Academy of Sciences (CAS), Beijing (China). State Key Lab. of Superlattices and Microstructures
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division
+ Show Author Affiliations

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. In this work, results demonstrate the superior performance of this method for metal and magnetic clusters when compared with the conventional conjugate-gradient method.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
AC02-05CH11231; AC02-05-CH11231
OSTI ID:
1544368
Alternate ID(s):
OSTI ID: 1393721
Journal Information:
Physical Review B, Vol. 96, Issue 11; ISSN 2469-9950
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

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Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY