Pith. sign in

REVIEW 1 cited by

Fast reconstruction of microstructures with ellipsoidal inclusions using analytical descriptors

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2306.08316 v1 pith:A4N2NY5E submitted 2023-06-14 cond-mat.mtrl-sci

classification cond-mat.mtrl-sci
keywords reconstructionmicrostructuredescriptorscomputationalanalyticaldescriptor-basedellipsoidalfast
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Microstructure reconstruction is an important and emerging aspect of computational materials engineering and multiscale modeling and simulation. Despite extensive research and fast progress in the field, the application of descriptor-based reconstruction remains limited by computational resources. Common methods for increasing the computational feasibility of descriptor-based microstructure reconstruction lie in approximating the microstructure by simple geometrical shapes and by utilizing differentiable descriptors to enable gradient-based optimization. The present work combines these two ideas for structures composed of non-overlapping ellipsoidal inclusions such as magnetorheological elastomers. This requires to express the descriptors as a function of the microstructure parametrization. Deriving these relations leads to analytical solutions that further speed up the reconstruction procedure. Based on these descriptors, microstructure reconstruction is formulated as a multi-stage optimization procedure. The developed algorithm is validated by means of different numerical experiments and advantages and limitations are discussed in detail.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. PolyMicros: Bootstrapping a Foundation Model for Polycrystalline Material Structure

    cs.LG 2025-05 conditional novelty 7.0 of 10

    PolyMicros bootstraps a generative foundation model for polycrystalline microstructures from five experimental volumes and applies it zero-shot to microscopy super-resolution and 2D-to-3D dimensionality expansion.

Pith tools