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

Hwang, In-Hui; Kelly, Shelly D.; Chan, Maria K. Y.; Stavitski, Eli; Heald, Steve M.; Han, Sang-Wook; Schwarz, Nicholas; Sun, Cheng-Jun

doi:10.1107/S1600577523005684

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

Journal Article · 01 August 2023 · Journal of Synchrotron Radiation (Online)

DOI: https://doi.org/10.1107/S1600577523005684 · OSTI ID:1993331

Hwang, In-Hui; Kelly, Shelly D.;

; Stavitski, Eli; Heald, Steve M.; Han, Sang-Wook; Schwarz, Nicholas; Sun, Cheng-Jun

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 task of analyzing the processed spectra remains another challenge. Although the non-resonant K β XES of 3 d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 ( AXEAP2 ), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3 d electron spin state, 3 d –3 p electron exchange force and K β emission core-hole lifetime.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE; USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)

Grant/Contract Number:: AC02-06CH11357; SC0012704

OSTI ID:: 1993331

Report Number(s):: BNL--224958-2023-JAAM; PII: S1600577523005684

Journal Information:: Journal of Synchrotron Radiation (Online), Journal Name: Journal of Synchrotron Radiation (Online) Journal Issue: 5 Vol. 30; ISSN 1600-5775; ISSN JSYRES

Publisher:: International Union of Crystallography (IUCr)Copyright Statement

Country of Publication:: Denmark

Language:: English

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

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