Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal crystal...
X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Vibrational Spectra of the "One-Mode" (Y<sub>1-<i>x</i></sub>La<i><sub>x</sub></i>)<sub>2</sub>O<sub>3</sub> Solid Solution Ceramics.

Materials (Basel, Switzerland)·2026
Same author

Machine Learning Tackles the Challenge of Powder X-ray Diffraction Indexing for All Crystal Systems.

Journal of chemical information and modeling·2025
Same author

Knowledge, attitudes, and practices of endoscopy among gastroenterologists in diagnosis and management of inflammatory bowel disease in China: a multicenter cross-sectional study.

BMC gastroenterology·2024
Same author

Global research status and trends of enteric glia: a bibliometric analysis.

Frontiers in pharmacology·2024
Same author

Mn- and Yb-Doped BaTiO<sub>3</sub>-(Na<sub>0.5</sub>Bi<sub>0.5</sub>)TiO<sub>3</sub> Ferroelectric Relaxor with Low Dielectric Loss.

Materials (Basel, Switzerland)·2023
Same author

Balancing Between Polarization and Conduction Loss toward Strong Electromagnetic Wave Absorption of Hard Carbon Particles with Morphology Heterogeneity.

ACS applied materials & interfaces·2022

Related Experiment Video

Updated: Jul 14, 2026

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
10:12

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

Published on: June 19, 2018

Insights into the Indexing of Powder X-ray Diffraction from a Robust Transformer Deep Learning.

Ke Shu1, Wei-Xin Yan1, Huai-Hai Li1

  • 1State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China.

Journal of Chemical Information and Modeling
|July 13, 2026
PubMed
Summary

A new AI framework, AIdex-R2, accurately determines crystal structures from powder X-ray diffraction (PXRD) data. This transformer-based method excels in challenging cases, improving crystal structure determination.

More Related Videos

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography
09:00

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography

Published on: September 29, 2019

Related Experiment Videos

Last Updated: Jul 14, 2026

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
10:12

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

Published on: June 19, 2018

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography
09:00

Visualization of Failure and the Associated Grain-Scale Mechanical Behavior of Granular Soils under Shear using Synchrotron X-Ray Micro-Tomography

Published on: September 29, 2019

Area of Science:

  • Crystallography
  • Materials Science
  • Artificial Intelligence

Background:

  • Powder X-ray diffraction (PXRD) is crucial for determining unknown crystal structures.
  • Indexing challenges arise with low-symmetry, large unit cells, and imperfect data.
  • Current heuristic methods lack robustness for complex crystal structures.

Purpose of the Study:

  • To develop an advanced AI framework for robust PXRD indexing.
  • To jointly infer extinction groups and unit cell parameters from diffraction data.
  • To overcome limitations of traditional heuristic indexing methods.

Main Methods:

  • A transformer-based end-to-end framework, AIdex-R2, was developed.
  • The model performs joint inference of extinction groups and unit cell parameters.
  • Input data consists of sequences of low-angle diffraction reflections.

Main Results:

  • AIdex-R2 achieved ~98.5% top-5 accuracy for extinction group identification.
  • Cell parameter prediction (indexing) showed a ~1.44% mean absolute percentage error.
  • Indexing success rate exceeded ~90% under realistic data perturbations.

Conclusions:

  • AIdex-R2 demonstrates superior performance over classical algorithms in speed and accuracy.
  • The AI model provides insights into the PXRD indexing 'black box'.
  • This framework enhances the determination of unknown crystal structures from PXRD data.