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X-ray Absorption Spectroscopy (XAS) is a powerful technique for probing local atomic environments, yet its interpretation remains limited by the need for expert-driven analysis, computationally expensive simulations, and element-specific…

Machine Learning · Computer Science 2025-08-27 Yufeng Wang , Peiyao Wang , Lu Wei , Lu Ma , Yuewei Lin , Qun Liu , Haibin Ling

In recent years, rapid progress has been made in developing artificial intelligence (AI) and machine learning (ML) methods for x-ray absorption spectroscopy (XAS) analysis. Compared to traditional XAS analysis methods, AI/ML approaches…

The increasing volume and complexity of X-ray absorption spectroscopy (XAS) data generated at synchrotron facilities worldwide require robust infrastructure for data management, sharing, and analysis. This paper introduces the XAS Database…

Databases · Computer Science 2025-09-18 Denis Spasyuk

Earth-abundant iron is an essential metal in regulating the structure and function of proteins. This study presents the development of a comprehensive X-ray Absorption Spectroscopy (XAS) database focused on iron-containing proteins,…

Biomolecules · Quantitative Biology 2025-09-24 Yufeng Wang , Peiyao Wang , Lu Wei , Emerita Mendoza Rengifo , Dali Yang , Lu Ma , Yuewei Lin , Qun Liu , Haibin Ling

X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing the local chemical environment of absorbing atoms. However, analyzing XAS data presents significant challenges, often requiring extensive,…

Materials Science · Physics 2025-04-16 Shubha R. Kharel , Fanchen Meng , Xiaohui Qu , Matthew R. Carbone , Deyu Lu

This chapter introduces the use of X-ray absorption spectroscopy (XAS) in studying the local electronic and atomic structure of high-entropy materials. The element selectivity of XAS makes it particularly suitable to address the challenges…

Materials Science · Physics 2024-11-12 Alexei Kuzmin

Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental…

X-ray absorption spectroscopy (XAS) is a commonly-employed technique for characterizing functional materials. In particular, x-ray absorption near edge spectra (XANES) encodes local coordination and electronic information and machine…

X-ray absorption spectroscopy (XAS) is a powerful and well established technique with sensitivity to elemental and chemical composition. Despite these advantages, its implementation has not kept pace with the development of ultrafast pulsed…

A novel method and experimental configuration are proposed that allow the collection of high-quality X-ray absorption spectroscopy (XAS) data in transmission mode on a standard laboratory diffractometer. This configuration makes use of…

Instrumentation and Detectors · Physics 2025-09-23 Milen Gateshki , Charalampos Zarkadas , Detlef Beckers

X-ray Absorption Spectroscopy (XAS) is a widely used X-ray diagnostic method. While synchrotrons have large communities of XAS users, its use on X-Ray Free Electron Lasers (XFEL) facilities has been rather limited. At a first glance, the…

Instrumentation and Detectors · Physics 2020-05-05 M. Harmand , M. Cammarata , M. Chollet , A. G Krygier , H. T. Lemke , D. Zhu

X-ray absorption near edge structure (XANES) is an essential tool for elucidating the atomic-scale, local three-dimensional (3D) structure of given materials and molecules. The rapid computation of XANES based on molecular 3D structures…

Chemical Physics · Physics 2026-02-24 Fei Zhan , Zhi Geng

X-ray absorption spectroscopy (XAS) is a premier technique for materials characterization, providing key information about the local chemical environment of the absorber atom. In this work, we develop a database of sulfur K-edge XAS spectra…

X-ray absorption fine structure (XAFS) and x-ray emission spectroscopy (XES) are advanced x-ray spectroscopies that impact a wide range of disciplines. However, unlike the majority of other spectroscopic methods, XAFS and XES are…

We report the development of XASdb, a large database of computed reference X-ray absorption spectra (XAS), and a novel Ensemble-Learned Spectra IdEntification (ELSIE) algorithm for the matching of spectra. XASdb currently hosts more than…

Choosing a suitable deep learning architecture for multimodal data fusion is a challenging task, as it requires the effective integration and processing of diverse data types, each with distinct structures and characteristics. In this…

Machine Learning · Computer Science 2025-01-22 Abdelmadjid Chergui , Grigor Bezirganyan , Sana Sellami , Laure Berti-Équille , Sébastien Fournier

We present exa-AMD, an open-source, high-performance framework designed for accelerated materials discovery on modern supercomputers. exa-AMD overcomes key computational bottlenecks in large-scale structure prediction through task-based…

Materials Science · Physics 2025-12-11 Weiyi Xia , Maxim Moraru , Ying Wai Li , Cai-Zhuang Wang

X-ray absorption near edge structure (XANES) spectroscopy is a powerful technique for characterizing the chemical state and symmetry of individual elements within materials, but requires collecting data at many energy points which can be…

Applied Physics · Physics 2025-04-25 Ming Du , Mark Wolfman , Chengjun Sun , Shelly D. Kelly , Mathew J. Cherukara

Panoramic X-ray is a simple and effective tool for diagnosing dental diseases in clinical practice. When deep learning models are developed to assist dentist in interpreting panoramic X-rays, most of their performance suffers from the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Zijian Cai , Xinquan Yang , Xuguang Li , Xiaoling Luo , Xuechen Li , Linlin Shen , He Meng , Yongqiang Deng

Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "multimodal" machine learning framework that unifies…

Materials Science · Physics 2026-02-03 Shun Muroga , Hideaki Nakajima , Taiyo Shimizu , Kazufumi Kobashi , Kenji Hata
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