計測インフォマティクスとデータベースの統合による客観・高速結晶構造解析

抄録

Along with the advancement of measurement technologies, a large amount of experimental crystallographic data can be obtained easily, so that objective and rapid analysis suitable for batch process is strongly required. This article introduces recent research on objective and rapid analysis of crystal structure using X-rays or electron beams. For one-dimensional X-ray diffraction pattern, non-negative linear regression （NNLS） using diffraction patterns provided by public database has achieved more objective and faster analysis than conventional manual works. With regard to two-dimensional electron and X-ray diffraction, good objective and rapid analysis was realized for several types of materials by using artificial intelligence （AI） based on convolutional neural network. On the other hand, the sparsity inherent in the diffraction pattern was found to cause a lack of information, and universal applicability of material property prediction using AI that depends on training data is still open to question. However, the fact that AI itself has the potential ability to solve complex images, a breakthrough technology for universal two-dimensional objective and rapid analysis might be found in progressing research.