Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures

• Published in: Frontiers in materials Vol. 8
• Main Authors: Prifling, Benedikt, Röding, Magnus, Townsend, Philip, Neumann, Matthias, Schmidt, Volker
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 23.12.2021
• Subjects: 3-phase; algorithm; deep learning; diffusion; diffusivity; electrodes; fluid permeability; lattice boltzmann method; mass transport; Matematik; Materials Science; Mathematical sciences; microstructures; neural-networks; nonlinear minimization subject; permeability; porous materials; simulation; structure-property relationship; tortuosity; virtual materials testing
• ISSN: 2296-8016; 2296-8016
• DOI: 10.3389/fmats.2021.786502

Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast data...