Simulation of neutron dark-field data for grating-based interferometers

Area of Science:

• Materials Science
• Neutron Scattering Physics
• Computational Science

Background:

• Hierarchical structures and heterogeneous materials are crucial in fields like additive manufacturing, alternative energy, biology, and polymer science.
• Understanding the structure-function relationship is key to developing advanced materials, but broad length-scale characterization often requires multiple techniques.
• Neutron far-field interferometry offers multi-scale characterization by integrating neutron imaging and small-angle neutron scattering (SANS) through dark-field imaging.

Purpose of the Study:

• To develop a computational tool for analyzing neutron dark-field interferometry data.
• To bridge the gap in analytical models for dark-field imaging by leveraging the relationship with SANS via Hankel transforms.
• To facilitate the use of neutron far-field interferometry for microstructure characterization.

Main Methods:

• Development of a Python-based library named 'correlogram-tools'.
• Utilized existing small-angle neutron scattering (SANS) models within the library.
• Implemented a numerical Hankel transform for simulating dark-field interferometry data.

Main Results:

• The 'correlogram-tools' library can simulate dark-field interferometry data using SANS models and Hankel transforms.
• Demonstrated the software's utility in identifying suitable sample sets for interferometry experiments.
• Showcased the ability to analyze interferometry data and generate simulated images for training advanced analysis models.

Conclusions:

• The 'correlogram-tools' library provides a valuable resource for researchers in materials science and related fields.
• This software enhances the application of neutron far-field interferometry for detailed microstructure analysis.
• Facilitates multi-scale characterization of hierarchical and heterogeneous materials.