3D Multiphase Heterogeneous Microstructure Generation Using Conditional Latent Diffusion Models

The development of a microstructure generation framework tailored to user-specific needs is crucial for understanding materials behavior through distinct processing-structure-property relationships. Recent advancements in generative modeling, particularly with Latent Diffusion Models (LDM), have significantly enhanced our ability to create high-quality images that fulfill specific user requirements. In this paper, we present a scalable framework that employs LDM to generate 3D microstructures (128x128x64) with over a million voxels, customized to user-defined statistical and topological features. This framework can also predict manufacturing conditions that produce these microstructures experimentally, solving the reachability issue. Our work focuses on organic photovoltaics (OPV), but the architecture allows for potential extensions into other fields of materials science by adjusting the training dataset.