10:12Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
Physical Properties Of Minerals II: Polymineralic Analysis
08:26Cell Culture on Silicon Nitride Membranes and Cryopreparation for Synchrotron X-ray Fluorescence Nano-analysis
09:51Atom Probe Tomography Studies on the Cu(In,Ga)Se2 Grain Boundaries
06:19Constructing and Visualizing Models using Mime-based Machine-learning Framework
07:26Synthesis and Microdiffraction at Extreme Pressures and Temperatures
You might also read
Articles linked to this work by shared authors, journal, and citation graph.
Updated: Jan 20, 2026

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
Published on: June 19, 2018
Ka Hung Chan1,2, Xinyue Huang1, Nobumichi Tamura2
1Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Hong Kong.
A new physics-informed machine learning (PIML) method enhances synchrotron X-ray microdiffraction. This approach achieves nanoscale grain mapping resolution for nanocrystals, overcoming previous limitations.
Area of Science:
Background:
Purpose of the Study:
Main Methods:
Main Results:
Conclusions: