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In this paper, we propose a Bayesian spectral deconvolution considering the properties of peaks in different energy domains. Bayesian spectral deconvolution regresses spectral data into the sum of multiple basis functions. Conventional…

Understanding the relationship between atomic structure (order) and chemical composition (chemistry) is critical for advancing materials science, yet traditional spectroscopic techniques can be slow and damaging to sensitive samples.…

Materials Science · Physics 2025-08-29 Mridul Kumar , Yevgeny Rakita

Simulation of spectra of x-ray absorption spectroscopy (XAS) at the L-edge is a well-established and reliable computational tool that, in combination with experimental measurements, reveals details about the local electronic structure and…

Materials Science · Physics 2021-07-29 Johann Lueder

We present a reciprocal-space pseudopotential scheme for calculating X-ray absorption near-edge structure (XANES) spectra. The scheme incorporates a recursive method to compute absorption cross section as a continued fraction. The continued…

Condensed Matter · Physics 2009-11-07 Mathieu Taillefumier , Delphine Cabaret , Anne-Marie Flank , Francesco Mauri

Interpretation of x-ray absorption near-edge structure (XANES) experiments is often done via analyzing the role of particular atoms in the formation of specific peaks in the calculated spectrum. Typically, this is achieved by calculating…

Condensed Matter · Physics 2009-11-07 Ondrej Sipr

Identifying local structural motifs and packing patterns of molecular solids is a challenging task for both simulation and experiment. We demonstrate two novel approaches to characterize local environments in different polymorphs of…

Materials Science · Physics 2024-04-02 Daisuke Kuroshima , Michael Kilgour , Mark E. Tuckerman , Jutta Rogal

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…

The advent of massive data repositories has propelled machine learning techniques to the front lines of many scientific fields, and exploring new frontiers by leveraging the predictive power of machine learning will greatly accelerate big…

Materials Science · Physics 2020-05-05 Matthew R. Carbone , Mehmet Topsakal , Deyu Lu , Shinjae Yoo

Most machine learning (ML) models in Materials Science are developed by global geometric features, often falling short in describing localized characteristics, like molecular adsorption on materials. In this study, we introduce a local…

Materials Science · Physics 2023-11-21 Yifan Li , Yihan Wu , Yuhang Han , Qujie Lyu , Hao Wu , Xiuying Zhang , Lei Shen

We report an interpretation method for deep learning models that allows us to handle high-dimensional spectral data in materials science. The proposed method uses feature extraction and clustering analysis to categorize materials into…

Materials Science · Physics 2025-10-21 Akira Takahashi , Yu Kumagai , Arata Takamatsu , Fumiyasu Oba

Speckle patterns produced by coherent X-ray have a close relationship with the internal structure of materials but quantitative inversion of the relationship to determine structure from speckle patterns is challenging. Here, we investigate…

X-ray absorption spectroscopy at the L-edge probes transitions of 2p-electrons into unoccupied d-states. Applied to transition metal atoms, this experimental technique can provide valuable information about the electronic structure of…

Materials Science · Physics 2021-02-03 Johann Lueder

A central challenge in computational catalysis is the identification of low-energy and chemically plausible adsorption configurations, as these directly affect adsorption energies, reaction pathways, and catalytic performance. Existing…

Materials Science · Physics 2026-05-07 Yifan Li , Arravind Subramanian , Xiaoqing Liu , Qiujie Lyu , Sergey Kozlov , Lei Shen

Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing…

Computer Vision and Pattern Recognition · Computer Science 2016-11-11 Boyu Wang , Kevin Yager , Dantong Yu , Minh Hoai

The lack of theoretical understanding of X-Ray Absorption Near Edge Structure (XANES) spectroscopy makes the development of analysis tools for its study a necessity. Here, an algorithm for judicious choice of local minima and maxima points…

Materials Science · Physics 2020-07-01 Rafael Monteiro , Itsuki Miyazato , Keisuke Takahashi

X-ray spectroscopy is one of the most powerful tools to access structure and properties of matter in different states of aggregation as it allows to trace atomic and molecular energy levels in course of various physical and chemical…

Chemical Physics · Physics 2019-06-12 Sergey I. Bokarev , Oliver Kühn

Progress in functional materials discovery has been accelerated by advances in high throughput materials synthesis and by the development of high-throughput computation. However, a complementary robust and high throughput structural…

Materials Science · Physics 2021-11-30 Jiadong Dan , Xiaoxu Zhao , Shoucong Ning , Jiong Lu , Kian Ping Loh , N. Duane Loh , Stephen J. Pennycook

Resonant X-ray scattering (RXS) is a spectroscopy where both the power of site selective diffraction and the power of local absorption spectroscopy regarding atomic species are combined. By virtue of the dependence on the core level state…

Materials Science · Physics 2007-11-12 Yves Joly , Elena S. Nazarenko , José-Emilio Lorenzo , Sergio Di Matteo , Calogero R. Natoli

Recording atomic-resolution transmission electron microscopy (TEM) images is becoming increasingly routine. A new bottleneck is then analyzing this information, which often involves time-consuming manual structural identification. We have…

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…