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arXiv · 2309.14785

Bayesian inference to identify crystalline structures for XRD

Ryo Murakami·Yoshitaka Matsushita·Kenji Nagata·Hayaru Shouno·Hideki Yoshikawa
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Abstract

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.

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Ryo Murakami, Yoshitaka Matsushita, Kenji Nagata, Hayaru Shouno, Hideki Yoshikawa. 2023-09-26. Bayesian inference to identify crystalline structures for XRD. https://arxiv.org/abs/2309.14785

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