36 citations · 57 across the 9 of their papers we have counts for
9 papers
Generative reconstruction of 2D and 3D polycrystalline microstructures using symmetrized hyperspherical harmonics
Ali R. Safi, Paul Seibert, Santiago Benito +3
Establishing structure-property linkages in polycrystalline materials requires representative two- (2D) and three- (3D) dimensional microstructural inputs for full-field simulation…
An Efficient Bayesian Framework for Inverse Problems via Optimization and Inversion: Surrogate Modeling, Parameter Inference, and Uncertainty Quantification
Mihaela Chiappetta, Massimo Carraturo, Alexander Raßloff +2
The present paper proposes a Bayesian framework for inverse problems that seamlessly integrates optimization and inversion to enable rapid surrogate modeling, accurate parameter in…
Inverse design of spinodoid structures using Bayesian optimization
Alexander Raßloff, Paul Seibert, Karl A. Kalina +1
Tailoring materials to achieve a desired behavior in specific applications is of significant scientific and industrial interest as design of materials is a key driver to innovation…
Reconstructing microstructures from statistical descriptors using neural cellular automata
Paul Seibert, Alexander Raßloff, Yichi Zhang +4
The problem of generating microstructures of complex materials in silico has been approached from various directions including simulation, Markov, deep learning and descriptor-base…
DA-VEGAN: Differentiably Augmenting VAE-GAN for microstructure reconstruction from extremely small data sets
Yichi Zhang, Paul Seibert, Alexandra Otto +3
Microstructure reconstruction is an important and emerging field of research and an essential foundation to improving inverse computational materials engineering (ICME). Much of th…
Two-stage 2D-to-3D reconstruction of realistic microstructures: Implementation and numerical validation by effective properties
Paul Seibert, Alexander Raßloff, Karl Kalina +4
Realistic microscale domains are an essential step towards making modern multiscale simulations more applicable to computational materials engineering. For this purpose, 3D compute…
Microstructure Characterization and Reconstruction in Python: MCRpy
Paul Seibert, Alexander Raßloff, Karl Kalina +2
Microstructure characterization and reconstruction (MCR) is an important prerequisite for empowering and accelerating integrated computational materials engineering. Much progress…
Descriptor-based reconstruction of three-dimensional microstructures through gradient-based optimization
Paul Seibert, Alexander Raßloff, Marreddy Ambati +1
Microstructure reconstruction is an important cornerstone to the inverse materials design concept. In this work, a general algorithm is developed to reconstruct a three-dimensional…
Reconstructing random heterogeneous media through differentiable optimization
Paul Seibert, Marreddy Ambati, Alexander Raßloff +1
Microstructure reconstruction is a key enabler of process-structure-property linkages, a central topic in materials engineering. Revisiting classical optimization-based reconstruct…