Crystalline phase structure is essential for understanding the performance
and properties of a material. Therefore, this study identified and quantified
the crystalline phase structure of a sample based on the diffraction pattern
observed when the crystalline sample was irradiated with electromagnetic waves
such as X-rays. Conventional analysis necessitates experienced and
knowledgeable researchers to shorten the list from many candidate crystalline
phase structures. However, the Conventional diffraction pattern analysis is
highly analyst-dependent and not objective. Additionally, there is no
established method for discussing the confidence intervals of the analysis
results. Thus, this study aimed to establish a method for automatically
inferring crystalline phase structures from diffraction patterns using Bayesian
inference. Our method successfully identified true crystalline phase structures
with a high probability from 50 candidate crystalline phase structures.
Further, the mixing ratios of selected crystalline phase structures were
estimated with a high degree of accuracy. This study provided reasonable
results for well-crystallized samples that clearly identified the crystalline
phase structures