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Title: A fingerprint based metric for measuring similarities of crystalline structures

Abstract

Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not directly suitable as fingerprints to distinguish structures. In this paper, based on a characterization of the local environment of all atoms in a cell, we introduce crystal fingerprints that can be calculated easily and define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures. Finally, the new method can be a useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms, and high-throughput screenings.

Authors:
 [1];  [2];  [1];  [1];  [3];  [3];  [3]; ORCiD logo [4];  [1];  [5];  [1]
  1. Univ. of Basel (Switzerland). Dept. of Physics
  2. Univ. of Basel (Switzerland). Dept. of Physics; Northwestern Univ., Evanston, IL (United States). Dept. of Materials Science and Engineering
  3. Inst. for Advanced Studies in Basic Sciences, Zanjan (Iran)
  4. Shahid Beheshti Univ., Tehran (Iran). Physics Dept.
  5. Northwestern Univ., Evanston, IL (United States). Dept. of Materials Science and Engineering
Publication Date:
Research Org.:
Northwestern Univ., Evanston, IL (United States); Univ. of Basel (Switzerland)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); Swiss National Science Foundation (SNSF)
OSTI Identifier:
1469171
Alternate Identifier(s):
OSTI ID: 1235591
Grant/Contract Number:  
FG02-07ER46433; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 144; Journal Issue: 3; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; carbides; theoretical computer science; symmetry functions; electronic noise; machine learning; chemical elements; perovskites; classical statistical mechanics; crystal structure; potential energy surfaces

Citation Formats

Zhu, Li, Amsler, Maximilian, Fuhrer, Tobias, Schaefer, Bastian, Faraji, Somayeh, Rostami, Samare, Ghasemi, S. Alireza, Sadeghi, Ali, Grauzinyte, Migle, Wolverton, Chris, and Goedecker, Stefan. A fingerprint based metric for measuring similarities of crystalline structures. United States: N. p., 2016. Web. doi:10.1063/1.4940026.
Zhu, Li, Amsler, Maximilian, Fuhrer, Tobias, Schaefer, Bastian, Faraji, Somayeh, Rostami, Samare, Ghasemi, S. Alireza, Sadeghi, Ali, Grauzinyte, Migle, Wolverton, Chris, & Goedecker, Stefan. A fingerprint based metric for measuring similarities of crystalline structures. United States. doi:10.1063/1.4940026.
Zhu, Li, Amsler, Maximilian, Fuhrer, Tobias, Schaefer, Bastian, Faraji, Somayeh, Rostami, Samare, Ghasemi, S. Alireza, Sadeghi, Ali, Grauzinyte, Migle, Wolverton, Chris, and Goedecker, Stefan. Thu . "A fingerprint based metric for measuring similarities of crystalline structures". United States. doi:10.1063/1.4940026. https://www.osti.gov/servlets/purl/1469171.
@article{osti_1469171,
title = {A fingerprint based metric for measuring similarities of crystalline structures},
author = {Zhu, Li and Amsler, Maximilian and Fuhrer, Tobias and Schaefer, Bastian and Faraji, Somayeh and Rostami, Samare and Ghasemi, S. Alireza and Sadeghi, Ali and Grauzinyte, Migle and Wolverton, Chris and Goedecker, Stefan},
abstractNote = {Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not directly suitable as fingerprints to distinguish structures. In this paper, based on a characterization of the local environment of all atoms in a cell, we introduce crystal fingerprints that can be calculated easily and define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures. Finally, the new method can be a useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms, and high-throughput screenings.},
doi = {10.1063/1.4940026},
journal = {Journal of Chemical Physics},
number = 3,
volume = 144,
place = {United States},
year = {2016},
month = {1}
}

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Cited by: 18 works
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