A noise-robust data assimilation method for crystal structure determination using powder diffraction intensity

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 e-Zn(OH)(2) to determine its effectiveness in the data assimilation method.

Automated summary

Crystal structure prediction for a given chemical composition has been a challenge. Recent research has shown that experimental powder x-ray diffraction data can be helpful in crystal structure search, even when they are insufficient on their own. By assimilating XRD data into the simulation using a penalty function, the success rate and noise robustness can be improved.