Microstructures and mass transport in porous materials

Abstract: Understanding the microstructure of a porous material and how it relates to its mass transport properties (diffusion, fluid flow) is crucial for designing better materials. One example is coating layers on pharmaceutical pellets for controlled release of compounds, another is liquid transport through fibrous media in hygiene products. We combine e.g. image analysis, spatial statistics, stochastic geometry, numerical simulation techniques, and machine learning to characterize materials and to predict and understand their properties. We will discuss a number of cases involving semantic segmentation of 3D image data, deep learning regression for parameter estimation in different experimental techniques, development of realistic virtual materials models, machine learning-based prediction of properties, and the design of materials with desired properties.

Contact Mohammad Ghorbani to receive the Zoom link.