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Title: An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs

An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has been applied to the case of LiFePO 4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO 4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.
Authors:
 [1] ;  [2] ;  [1] ;  [1] ;  [1] ;  [3] ;  [4] ;  [2] ;  [5]
  1. Xiamen Univ. (China)
  2. Univ. of Science and Technology of China, Hefei (China). International Center for Quantum Design of Functional Materials (ICQD)
  3. Iowa State Univ., Ames, IA (United States)
  4. Ames Lab., Ames, IA (United States)
  5. (United States)
Publication Date:
Report Number(s):
IS-J 9356
Journal ID: ISSN 1932-7447
Grant/Contract Number:
2016YFA0202601; 21233004; AC02-07CH11358
Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry. C
Additional Journal Information:
Journal Volume: 121; Journal Issue: 21; Journal ID: ISSN 1932-7447
Publisher:
American Chemical Society
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
OSTI Identifier:
1368041

Zhu, Zizhong, Wu, Ping, Wu, Shunqing, Xu, Linhan, Xu, Yixu, Zhao, Xin, Wang, Cai-Zhuang, Ho, Kai-Ming, and Iowa State Univ., Ames, IA. An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs. United States: N. p., Web. doi:10.1021/acs.jpcc.7b02486.
Zhu, Zizhong, Wu, Ping, Wu, Shunqing, Xu, Linhan, Xu, Yixu, Zhao, Xin, Wang, Cai-Zhuang, Ho, Kai-Ming, & Iowa State Univ., Ames, IA. An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs. United States. doi:10.1021/acs.jpcc.7b02486.
Zhu, Zizhong, Wu, Ping, Wu, Shunqing, Xu, Linhan, Xu, Yixu, Zhao, Xin, Wang, Cai-Zhuang, Ho, Kai-Ming, and Iowa State Univ., Ames, IA. 2017. "An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs". United States. doi:10.1021/acs.jpcc.7b02486. https://www.osti.gov/servlets/purl/1368041.
@article{osti_1368041,
title = {An Efficient Scheme for Crystal Structure Prediction Based on Structural Motifs},
author = {Zhu, Zizhong and Wu, Ping and Wu, Shunqing and Xu, Linhan and Xu, Yixu and Zhao, Xin and Wang, Cai-Zhuang and Ho, Kai-Ming and Iowa State Univ., Ames, IA},
abstractNote = {An efficient scheme based on structural motifs is proposed for the crystal structure prediction of materials. The key advantage of the present method comes in two fold: first, the degrees of freedom of the system are greatly reduced, since each structural motif, regardless of its size, can always be described by a set of parameters (R, θ, φ) with five degrees of freedom; second, the motifs could always appear in the predicted structures when the energies of the structures are relatively low. Both features make the present scheme a very efficient method for predicting desired materials. The method has been applied to the case of LiFePO4, an important cathode material for lithium-ion batteries. Numerous new structures of LiFePO4 have been found, compared to those currently available, available, demonstrating the reliability of the present methodology and illustrating the promise of the concept of structural motifs.},
doi = {10.1021/acs.jpcc.7b02486},
journal = {Journal of Physical Chemistry. C},
number = 21,
volume = 121,
place = {United States},
year = {2017},
month = {5}
}