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Journal of Applied Crystallography|February 6, 2026
Machine learning approaches for crystallographic classification from synthetic 2D X-ray diffraction dataAyoub Shahnazari, Zeliang Zhang, Sachith E Dissanayake, et al.Journal of Applied Crystallography|October 9, 2025
Laboratory three-dimensional X-ray micro-beam Laue diffractionYubin Zhang, Anthony Seret, Jette Oddershede, et al.Journal of Applied Crystallography|October 9, 2025
A reference material for X-ray diffraction line profile analysisP Scardi, M D'Incau, M A Malagutti, et al.Journal of Applied Crystallography|October 9, 2025
Solving disorder in (3D) real space: a comparative study of the three-dimensional difference pair distribution function and atomic resolution holography reconstructionsJens R Stellhorn, Arianna Minelli, Emily G Meekel, et al.Journal of Applied Crystallography|October 9, 2025
Machine learning inversion from scattering for mechanically driven polymersLijie Ding, Chi-Huan Tung, Bobby G Sumpter, et al.Journal of Applied Crystallography|October 9, 2025
Nematicity and structural strain: a tight connection in Fe-based superconductorsAlberto MartinelliJournal of Applied Crystallography|August 6, 2025
Two metrics for quantifying systematic errors in diffraction experiments: systematic errors in the variance of the observed intensities and agreement factor gapJulian HennJournal of Applied Crystallography|August 6, 2025
Machine learning assisted nanobeam X-ray diffraction based analysis on hydride vapor-phase epitaxy GaNZhendong Wu, Yusuke Hayashi, Tetsuya Tohei, et al.Journal of Applied Crystallography|August 6, 2025
Opportunities for near-surface small-angle neutron scattering to probe magnetic nanostructures within thin-film volumesGrace L CauserJournal of Applied Crystallography|August 6, 2025
Small-angle X-ray scattering profile calculation for high-resolution models of biomacromoleculesKristian Lytje, Jan Skov PedersenPageof 112