The AXEAP2 program for K β X-ray emission spectra analysis using artificial intelligence

• Published in: Journal of synchrotron radiation Vol. 30; no. 5; pp. 923 - 933
• Main Authors: Hwang, In-Hui, Kelly, Shelly D., Chan, Maria K. Y., Stavitski, Eli, Heald, Steve M., Han, Sang-Wook, Schwarz, Nicholas, Sun, Cheng-Jun
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.09.2023; International Union of Crystallography (IUCr); International Union of Crystallography
• Subjects: Artificial intelligence; AXEAP; Data analysis; Data processing; electron interaction; Electron spin; Electronic structure; Electrons; Emission analysis; Emission spectra; genetic algorithm; Genetic algorithms; Machine learning; MATERIALS SCIENCE; Oxidation; Parameters; Research Papers; spin state; Synchrotrons; Transition metals; Unsupervised learning; XES; AXEAP; genetic algorithm; electron interaction; spin state; XES
• ISSN: 1600-5775; 0909-0495; 1600-5775
• DOI: 10.1107/S1600577523005684

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the ta...