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Materials identification and structural understanding from powder X-ray diffraction (PXRD) data is a long-standing challenge in materials science, fundamental to discovering and characterizing novel materials. A prerequisite for full…

Quantitative phase analysis is one of the major applications of X-ray powder diffraction. The essential principle of quantitative phase analysis is that the diffraction intensity of a component phase in a mixture is proportional to its…

Materials Science · Physics 2022-02-22 Hui Lia , Meng Hebcd , Ze Zhange

Solving crystal structures from powder X-ray diffraction (XRD) is a central challenge in materials characterization. In this work, we study the powder XRD-to-structure mapping using gradient descent optimization, with the goal of recovering…

Materials Science · Physics 2025-12-04 Nofit Segal , Akshay Subramanian , Mingda Li , Benjamin Kurt Miller , Rafael Gomez-Bombarelli

Multi-technique high resolution X-ray mapping enhanced by the recent advent of 4th generation synchrotron facilities can produce colossal datasets, challenging traditional analysis methods. Such difficulty is clearly materialized when…

Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patterns produced in…

X-ray single particle imaging involves the measurement of a large number of noisy diffraction patterns of isolated objects in random orientations. The missing information about these patterns is then computationally recovered in order to…

Image and Video Processing · Electrical Eng. & Systems 2020-05-25 Kartik Ayyer

Emerging coherent X-ray scattering patterns of single particles have shown dominant morphological signatures in agreement with predictions of the scattering model used for conventional protein crystallography. The key question is if and to…

Biomolecules · Quantitative Biology 2014-07-28 Aliakbar Jafarpour

Novel materials drive advancements in fields ranging from energy storage to electronics, with crystal structure characterization forming a crucial yet challenging step in materials discovery. In this work, we introduce \emph{deCIFer}, an…

The prediction of material structure from chemical composition has been a long-standing challenge in natural science. Although there have been various methodological developments and successes with computer simulations, the prediction of…

Materials Science · Physics 2018-05-23 Naoto Tsujimoto , Daiki Adachi , Ryosuke Akashi , Synge Todo , Shinji Tsuneyuki

The DXRD program suite consisting of a series of dynamical-theory programs is introduced for computing dynamical X-ray diffraction from single crystals. Its interactive graphic user interfaces (GUIs) allow general users to make complicated…

Optics · Physics 2025-09-29 XianRong Huang , Lahsen Assoufid

Information on the lattice parameter of single crystals with known crystallographic structure allows for estimations of sample quality and composition. In many cases it is suffcient to determine one lattice parameter or the lattice spacing…

Materials Science · Physics 2016-07-08 A. Jesche , M. Fix , A. Kreyssig , W. R. Meier , P. C. Canfield

Atom arrangement plays a critical role in determining material properties. It is, therefore, essential for materials science and engineering to identify and characterize distinct atom configurations. Currently, crystal structures can be…

Materials Science · Physics 2023-10-18 Rafał Abram , Dariusz Chrobak

Crystal structure prediction for a given chemical composition has long been a challenge in condensed-matter science. We have recently shown that experimental powder X-ray diffraction (XRD) data are helpful in a crystal structure search…

Materials Science · Physics 2023-01-30 Seiji Yoshikawa , Ryuhei Sato , Ryosuke Akashi , Synge Todo , Shinji Tsuneyuki

The robust and automated determination of crystal symmetry is of utmost importance in material characterization and analysis. Recent studies have shown that deep learning (DL) methods can effectively reveal the correlations between X-ray or…

Computational Physics · Physics 2020-05-27 Leslie Ching Ow Tiong , Jeongrae Kim , Sang Soo Han , Donghun Kim

Scientific researchers frequently use the in situ synchrotron high-energy powder X-ray diffraction (XRD) technique to examine the crystallographic structures of materials in functional devices such as rechargeable battery materials. We…

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…

Materials Science · Physics 2022-04-13 Yiqun Wang , Xiao-Jie Zhang , Fei Xia , Elsa A. Olivetti , Ram Seshadri , James M. Rondinelli

Determining crystal symmetry from powder X-ray diffraction is a central problem in materials characterization, yet multiple space groups can produce indistinguishable patterns, making automated classification difficult. We show that…

The advent of X-ray Free Electron Lasers promises the possibility to determine the structure of individual particles such as microcrystallites, viruses and biomolecules from single-shot diffraction snapshots obtained before the particle is…

Soft Condensed Matter · Physics 2010-05-06 Brian Moths , Abbas Ourmazd

Established x-ray diffraction methods allow for high-resolution structure determination of crystals, crystallized protein structures or even single molecules. While these techniques rely on coherent scattering, incoherent processes like…

Solving crystal structures from kinematical X-ray or electron diffraction patterns of single crystals requires many more diffracted beams to be recorded than there are atoms in the structure, since the phases of the structure factors can…

Materials Science · Physics 2023-02-13 Christoph T. Koch