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 the proposed model lie in its universality …
models for the first time. The novelty and strength of the proposed model lie in its universality …
Conditional diffusion-based microstructure reconstruction
Microstructure reconstruction, a major component of inverse computational materials
engineering, is currently advancing at an unprecedented rate. While various training-based …
engineering, is currently advancing at an unprecedented rate. While various training-based …
Two-stage 2D-to-3D reconstruction of realistic microstructures: Implementation and numerical validation by effective properties
Realistic microscale domains are an essential step towards making modern multiscale
simulations more applicable to computational materials engineering. For this purpose, 3D …
simulations more applicable to computational materials engineering. For this purpose, 3D …
[HTML][HTML] DA-VEGAN: Differentiably Augmenting VAE-GAN for microstructure reconstruction from extremely small data sets
Microstructure reconstruction is an important and emerging field of research and an
essential foundation to improving inverse computational materials engineering (ICME) …
essential foundation to improving inverse computational materials engineering (ICME) …
Reconstructing microstructures from statistical descriptors using neural cellular automata
The problem of generating microstructures of complex materials in silico has been
approached from various directions including simulation, Markov, deep learning and …
approached from various directions including simulation, Markov, deep learning and …
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling
Acquiring reliable microstructure datasets is a pivotal step toward the systematic design of
materials with the aid of integrated computational materials engineering (ICME) approaches …
materials with the aid of integrated computational materials engineering (ICME) approaches …
Experimental validation of reconstructed microstructure via deep learning in discontinuous fiber platelet composite
A novel approach for microstructure reconstruction using artificial intelligence (MR-AI) was
proposed to nondestructively measure the through-thickness average stochastic fiber …
proposed to nondestructively measure the through-thickness average stochastic fiber …
Fast reconstruction of microstructures with ellipsoidal inclusions using analytical descriptors
Microstructure reconstruction is an important and emerging aspect of computational
materials engineering and multiscale modeling and simulation. Despite extensive research …
materials engineering and multiscale modeling and simulation. Despite extensive research …
Inverse design of dual-phase steel microstructures using generative machine learning model and Bayesian optimization
N Kusampudi, M Diehl - International Journal of Plasticity, 2023 - Elsevier
The design of optimal microstructures requires first, the identification of microstructural
features that influence the material's properties and, then, a search for a combination of …
features that influence the material's properties and, then, a search for a combination of …
Denoising diffusion probabilistic models for generative alloy design
Inverse material design is an extremely challenging optimization task made difficult by, in
part, the highly nonlinear relationship linking performance with composition. Quantitative …
part, the highly nonlinear relationship linking performance with composition. Quantitative …