Quantitative analysis of EXAFS data sets using deep reinforcement learning

Quantitative analysis of EXAFS data sets using deep reinforcement learning

Abstract Extended X-ray absorption fine structure (EXAFS) serves as a unique tool for accurately characterizing the local structural properties surrounding specific atoms. However, the quantitative analysis of EXAFS data demands significant effort. Artificial intelligence (AI) techniques, including...

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Bibliographic Details
Main Authors: Eun-Suk Jeong, In-Hui Hwang, Sang-Wook Han
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Artificial intelligence
Reinforcement learning
Extended X-ray absorption fine structure
Machine learning
Local structural property
Online Access:https://doi.org/10.1038/s41598-025-94376-5
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https://doi.org/10.1038/s41598-025-94376-5

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