Microstructure reconstruction using diffusion-based generative models

This paper proposes a microstructure reconstruction framework with denoising diffusion models for the first time. The novelty and strength of proposed model lie in its universality generality characterization (MCR) that can be applied to various types composite materials. applicability diffusion-based is validated several microstructures (e.g., polycrystalline alloy, carbonate, ceramics, copolymer, fiber composite, etc.) have different morphological characteristics. Moreover, an implicit probabilistic (which yields non-Markovian processes) formulated accelerate sampling process, thereby controlling computational cost considering practicability reliability.