Cited by 1,302Machine Learning in Materials ScienceAdvanced Chemical Physics StudiesHigh-pressure geophysics and materials

Ab initio random structure searching

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Pickard, Chris J, Needs, R J·2011·Journal of Physics: Condensed Matter

Abstract

It is essential to know the arrangement of the atoms in a material in order to compute and understand its properties. Searching for stable structures of materials using first-principles electronic structure methods, such as density-functional-theory (DFT), is a rapidly growing field. Here we describe our simple, elegant and powerful approach to searching for structures with DFT, which we call ab initio random structure searching (AIRSS). Applications to discovering the structures of solids, point defects, surfaces, and clusters are reviewed. New results for iron clusters on graphene, silicon clusters, polymeric nitrogen, hydrogen-rich lithium hydrides, and boron are presented.

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Crossref · 10.1088/0953-8984/23/5/053201

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  • The problem of obtaining a complete yet concise description of a molecular or condensed-phase structure is central to many modelling techniques.

    “The problem of obtaining a complete yet concise description of a molecular or condensed-phase structure is central to many modelling techniques, including the sampling of rare events 15 and the search for stable structures 2,16,17 .”

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Research works printed but not linked: 2

  1. Wales D J 2003 Energy Landscapes (Cambridge: Cambridge University Press)
  2. Shi Y H and Eberhart R 1998 CEC 1998: Proc. IEEE Congr. on Evolutionary Computation (Piscataway, NJ) p 69

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Authors
Pickard, C. J., & Needs, R. J.
Affiliations
  • University College London (GB)
  • University of Cambridge (GB)
Venue
Journal of Physics: Condensed Matter
Published
2011-01-05
Volume
23
Issue
5
Pages
053201
ISSN
  • 0953-8984 (ISSN-L)
  • 1361-648X
OpenAlex
W2139062161
Cited by
1,302
References
133
Citations by year
2026: 78 · 2025: 115 · 2024: 105 · 2023: 103 · 2022: 88 · 2021: 136 · 2020: 172 · 2019: 78 · 2018: 91 · 2017: 80 · 2016: 63 · 2015: 59 · 2014: 57 · 2013: 35 · 2012: 28
FWCI
20.85
Type
journal article
Language
en
Open access
Locations
  • Journal of Physics Condensed Matter (publishedVersion)
  • PubMed (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • arXiv (Cornell University)
Funders
Engineering and Physical Sciences Research Council (EP/G007489/2, EP/F032773/1)
Topics
  • Physical Sciences › Materials Science › Materials Chemistry › Machine Learning in Materials Science
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
  • Physical Sciences › Earth and Planetary Sciences › Geophysics › High-pressure geophysics and materials
Keywords
ab initio random structure searching, structure discovery, density functional theory, point defects, surfaces, clusters, silicon clusters, polymeric nitrogen, boron

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