LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Area of Science:

• Crystallography
• Materials Science
• Computational Science

Background:

• Traditional Laue diffraction indexing methods face challenges with noisy data, weak signals, and overlapping reflections, especially for complex microstructures.
• These limitations hinder accurate crystallographic orientation determination in materials analysis.

Purpose of the Study:

• Introduce LaueMatching, a novel high-throughput algorithm for robust Laue diffraction pattern indexing.
• Overcome limitations of traditional methods by employing a direct pattern correlation approach.

Main Methods:

• Developed LaueMatching, an algorithm that compares experimental diffraction images to a library of simulated patterns.
• Bypassed explicit peak identification and fitting, common failure points in conventional techniques.
• Implemented for both CPU and GPU resources.

Main Results:

• Successfully indexed multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns.
• Validated accuracy and effectiveness on diverse experimental (Ni, Al, EuAl2O4) and simulated diffraction data.
• Demonstrated high-fidelity orientation refinement capabilities.

Conclusions:

• LaueMatching offers a robust and efficient solution for Laue diffraction indexing, particularly for complex and deformed materials.
• The direct pattern correlation approach significantly improves indexing success rates and accuracy.
• The algorithm is available for public use to advance materials characterization.