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Powder diffraction is a primary structural characterization tool in materials science, yet automated phase identification remains a major bottleneck for autonomous discovery. Existing workflows rely heavily on search--match heuristics and…

Materials Science · Physics 2026-05-13 Lalit Yadav , Yongqiang Cheng , Mathieu Doucet

The open-source PyNX toolkit [Favre-Nicolin et al (2011) arXiv:1010.2641, Mandula et al (2016)] has been extended to provide tools for coherent X-ray imaging data analysis and simulation. All calculations can be executed on graphical…

General Purpose computing on Graphical Processing Units (GPGPU) has resulted in unprecedented levels of speedup over its CPU counterparts, allowing programmers to harness the computational power of GPU shader cores to accelerate other…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-20 Vani Nagarajan , Milind Kulkarni

The increasing importance of artificial intelligence and machine learning in materials research has created demand for automated, high-throughput characterization techniques capable of rapidly generating large data sets. We describe here a…

Diffusion models have recently gained popularity for accelerated MRI reconstruction due to their high sample quality. They can effectively serve as rich data priors while incorporating the forward model flexibly at inference time, and they…

Image and Video Processing · Electrical Eng. & Systems 2023-10-20 Batu Ozturkler , Chao Liu , Benjamin Eckart , Morteza Mardani , Jiaming Song , Jan Kautz

PDFgetX3 is a new software application for converting X-ray powder diffraction data to atomic pair distribution function (PDF). PDFgetX3 has been designed for ease of use, speed and automated operation. The software can readily process…

Materials Science · Physics 2013-03-15 Pavol Juhas , Timur Davis , Christopher L. Farrow , Simon J. L. Billinge

As data science and machine learning methods are taking on an increasingly important role in the materials research community, there is a need for the development of machine learning software tools that are easy to use (even for nonexperts…

Computational Physics · Physics 2020-06-26 Ryan Jacobs , Tam Mayeshiba , Ben Afflerbach , Luke Miles , Max Williams , Matthew Turner , Raphael Finkel , Dane Morgan

One of the long-standing problems in materials science is how to predict a material's structure and then its properties given only its composition. Experimental characterization of crystal structures has been widely used for structure…

Materials Science · Physics 2022-03-29 Rongzhi Dong , Yong Zhao , Yuqi Song , Nihang Fu , Sadman Sadeed Omee , Sourin Dey , Qinyang Li , Lai Wei , Jianjun Hu

Polarized Resonant Soft X-ray scattering (P-RSoXS) has emerged as a powerful synchrotron-based tool that combines principles of X-ray scattering and X-ray spectroscopy. P-RSoXS provides unique sensitivity to molecular orientation and…

Three-dimensional X-ray diffraction (3DXRD) is shown to be feasible at the I12 Joint Engineering, Environmental and Processing (JEEP) beamline of Diamond Light Source. As a demonstration, a microstructually simple low-carbon ferritic steel…

The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern…

Recent advances in materials discovery have been driven by structure-based models, particularly those using crystal graphs. While effective for computational datasets, these models are impractical for real-world applications where atomic…

Machine Learning · Computer Science 2025-07-03 Jithendaraa Subramanian , Linda Hung , Daniel Schweigert , Santosh Suram , Weike Ye

X-ray diffraction is ideal for probing sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and…

Materials Science · Physics 2025-01-10 Rachel E. Lim , Shun-Li Shang , Chihpin Chuang , Thien Q. Phan , Zi-Kui Liu , Darren C. Pagan

Understanding the processes of perovskite crystallization is essential for improving the properties of organic solar cells. In situ real-time grazing-incidence X-ray diffraction (GIXD) is a key technique for this task, but it produces large…

X-ray diffraction tomography (XDT) resolves spatially-variant XRD profiles within macroscopic objects, and provides improved material contrast compared to the conventional transmission-based computed tomography (CT). However, due to the…

Medical Physics · Physics 2019-01-04 Zheyuan Zhu , Alexander Katsevich , Shuo Pang

When a sample's X-ray diffraction pattern (XRD) is measured, the corresponding crystal structure is usually determined by searching for similar XRD patterns in the database. However, if a similar XRD pattern is not found, it is tremendously…

Materials Science · Physics 2023-08-08 Joohwi Lee , Junpei Oba , Nobuko Ohba , Seiji Kajita

Despite the huge advancement in knowledge discovery and data mining techniques, the X-ray diffraction (XRD) analysis process has mostly remained untouched and still involves manual investigation, comparison, and verification. Due to the…

We introduce a computer program to simulate the results of neutron powder-diffraction experiments at the High Flux Isotope Reactor at Oak Ridge National Laboratory. The program is freely available as a web application at…

Electron ptychography has recently achieved unprecedented resolution, offering valuable insights across diverse material systems, including in three dimensions. However, high-quality ptychographic reconstruction is computationally expensive…

Materials Science · Physics 2025-08-07 Chia-Hao Lee , Steven E. Zeltmann , Dasol Yoon , Desheng Ma , David A. Muller

The large amount of powder diffraction data for which the corresponding crystal structures have not yet been identified suggests the existence of numerous undiscovered, physically relevant crystal structure prototypes. In this paper, we…

Materials Science · Physics 2024-10-31 Abhijith S. Parackal , Rhys E. A. Goodall , Felix A. Faber , Rickard Armiento