TY - JOUR
T1 - A noise-robust data assimilation method for crystal structure determination using powder diffraction intensity
AU - Yoshikawa, Seiji
AU - Sato, Ryuhei
AU - Akashi, Ryosuke
AU - Todo, Synge
AU - Tsuneyuki, Shinji
N1 - Funding Information:
This work was supported by the JSPS KAKENHI Grant-in-Aid for Scientific Research on Innovative Areas “Hydrogenomics,” Grant No. JP18H05519, and Elements Strategy Initiative: To Form Core Research Centers in Japan. S.Y. was supported by the Japan Society for the Promotion of Science through the Program for Leading Graduate Schools (MERIT). R.S. performed the calculations at the Supercomputer Center at the Institute for Solid State Physics at the University of Tokyo.
Publisher Copyright:
© 2022 Author(s).
PY - 2022/12/14
Y1 - 2022/12/14
N2 - Crystal structure prediction for a given chemical composition has long been a challenge in condensed-matter science. We have recently shown that experimental powder x-ray diffraction (XRD) data are helpful in a crystal structure search using simulated annealing, even when they are insufficient for structure determination by themselves [Tsujimoto et al., Phys. Rev. Mater. 2, 053801 (2018)]. In the method, the XRD data are assimilated into the simulation by adding a penalty function to the physical potential energy, where a crystallinity-type penalty function, defined by the difference between experimental and simulated diffraction angles was used. To improve the success rate and noise robustness, we introduce a correlation-coefficient-type penalty function adaptable to XRD data with significant experimental noise. We apply the new penalty function to SiO2 coesite and ϵ-Zn(OH)2 to determine its effectiveness in the data assimilation method.
AB - Crystal structure prediction for a given chemical composition has long been a challenge in condensed-matter science. We have recently shown that experimental powder x-ray diffraction (XRD) data are helpful in a crystal structure search using simulated annealing, even when they are insufficient for structure determination by themselves [Tsujimoto et al., Phys. Rev. Mater. 2, 053801 (2018)]. In the method, the XRD data are assimilated into the simulation by adding a penalty function to the physical potential energy, where a crystallinity-type penalty function, defined by the difference between experimental and simulated diffraction angles was used. To improve the success rate and noise robustness, we introduce a correlation-coefficient-type penalty function adaptable to XRD data with significant experimental noise. We apply the new penalty function to SiO2 coesite and ϵ-Zn(OH)2 to determine its effectiveness in the data assimilation method.
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U2 - 10.1063/5.0125553
DO - 10.1063/5.0125553
M3 - Article
C2 - 36546799
AN - SCOPUS:85144452013
SN - 0021-9606
VL - 157
JO - Journal of Chemical Physics
JF - Journal of Chemical Physics
IS - 22
M1 - 224112
ER -