Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models

被引:28
|
作者
Yang, Long [1 ]
Juhas, Pavol [2 ]
Terban, Maxwell W. [3 ]
Tucker, Matthew G. [4 ]
Billinge, Simon J. L. [1 ,5 ]
机构
[1] Columbia Univ, Dept Appl Phys & Appl Math, New York, NY 10027 USA
[2] Brookhaven Natl Lab, Computat Sci Initiat, Upton, NY 11973 USA
[3] Max Planck Inst Solid State Res, Heisenbergstr 1, D-70569 Stuttgart, Germany
[4] Oak Ridge Natl Lab, Neutron Scattering Div, POB 2009, Oak Ridge, TN 37830 USA
[5] Brookhaven Natl Lab, Condensed Matter Phys & Mat Sci Dept, Upton, NY 11973 USA
来源
ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES | 2020年 / 76卷
基金
美国国家科学基金会;
关键词
pair distribution function; PDF; automated fitting; atomic structure; structure discovery; METAL-INSULATOR TRANSITIONS; X-RAY-DIFFRACTION; CRYSTAL-STRUCTURE; IN-SITU; POWDER DIFFRACTION; PHASE-TRANSITIONS; COMPUTER-PROGRAM; NANOPARTICLE FORMATION; BARIUM-TITANATE; SEARCH-MATCH;
D O I
10.1107/S2053273320002028
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both X-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto-analysis PDF experiments in the future.
引用
收藏
页码:395 / 409
页数:15
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