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Meeting

2026 TMS Annual Meeting & Exhibition

Symposium

AI/ML/Data Informatics for Materials Discovery: Bridging Experiment, Theory, and Modeling

Presentation Title

Using 2D Data and Diffusion Model Principles to Generate 3D Microstructures of TRISO Fuel Compacts

Author(s)

Ryan Weber, Tyler Gerczak, Troy Munro, Oliver Johnson

On-Site Speaker (Planned)

Ryan Weber

Abstract Scope

Generative models have shown significant utility in facilitating material modeling, discovery, and property exploration. Specifically, denoising diffusion probabilistic models (DDPMs) have demonstrated the ability to accurately replicate image detail and patterns, which makes them ideally suited for generating complex anisotropic microstructures. Using 2D scans of a tri-structural isotropic (TRISO) fuel compact with a graphite matrix, taken with a two-modulator general ellipsometry microscope (2MGEM), and principles of DDPMs, 3D representative microstructures have been generated. The synthetic 3D microstructure has an accurate spatial distribution of TRISO particles and graphite orientation gradients and is validated against the 2MGEM data using 2-point correlation functions. These representative microstructures can be combined with orientation-dependent properties to facilitate engineering-scale simulations, which enable greater understanding of TRISO fuel performance.

Proceedings Inclusion?

Planned:

Keywords

ICME, Computational Materials Science & Engineering, Modeling and Simulation

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