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Genetic algorithm-based geometry calibration for dynamic compression x-ray diffraction experiments
Nathan P Brown1, Tommy Ao1, Marcus D Knudson1
1Sandia National Laboratories, P.O. Box 5800, Albuquerque, New Mexico 87185, USA.
The Review of Scientific Instruments
|May 12, 2025
Summary
A new genetic algorithm method simplifies geometry calibration for dynamic compression X-ray diffraction (XRD) experiments. This approach accurately determines detector and crystal orientation in complex 3D setups without prior constraints.
Area of Science:
- Materials Science
- Crystallography
- High-Pressure Physics
Background:
- Accurate analysis of dynamic compression X-ray diffraction (XRD) data requires precise geometry calibration.
- Determining detector position, orientation, and crystal lattice orientation in 3D geometries is challenging due to complex optimization problems.
Purpose of the Study:
- To develop and present a robust genetic algorithm-based approach for dynamic compression XRD geometry calibration.
- To overcome the nonlinear, nonsmooth, and discontinuous nature of traditional calibration optimization problems.
Main Methods:
- Implementation of a genetic algorithm for solving the geometry calibration problem.
- Detailed image processing and algorithm implementation strategies.
- Development and deployment of open-source software for calibration.
Main Results:
- Demonstrated capability to calibrate detector and crystal parameters in arbitrary 3D scattering geometries.
- Successfully determined crystal orientation without requiring a priori rotation constraints.
- Validated the genetic algorithm's effectiveness in handling complex XRD calibration scenarios.
Conclusions:
- The genetic algorithm approach provides an effective solution for challenging dynamic compression XRD geometry calibrations.
- The developed open-source software facilitates accurate data interpretation in high-pressure materials science.
- This method enhances the reliability of structural analysis in dynamic compression experiments.
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