Bayesian estimation to identify crystalline phase structures for X-ray diffraction pattern analysis
| Autor: | Ryo Murakami, Yoshitaka Matsushita, Kenji Nagata, Hayaru Shouno, Hideki Yoshikawa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Science and Technology of Advanced Materials: Methods, Vol 4, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 27660400 2766-0400 |
| DOI: | 10.1080/27660400.2023.2300698 |
| Popis: | ABSTRACTCrystalline 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|