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Keynote Lecture

Understanding hindered diffusion in porous networks combining electron tomography and pore-scale simulations

Thursday (27.09.2018)
14:45 - 15:15 S1/01 - A04
Part of:

Disordered hierarchical porous media play a crucial role as fixed bed supports for a wide range of applications from separation techniques such as HPLC to heterogeneous catalysis. To understand and ultimately optimize their performance, the relationship between morphology and transport properties has to be established. The key is a statistically meaningful, quantitative description of the pore structure linked to pore-scale simulations to determine the flow and diffusion properties using realistic models for the macro and mesopores [1].

In this presentation, we focus on the diffusion properties of silica monoliths determined by their mesopore morphology. An isomorphic series of monoliths with varying average pore diameter (12 to 26 nm) is the basis for our quantitative analysis. Electron tomographic reconstruction followed by advanced image processing is used to reconstruct a statistically relevant volume of the different monoliths, which is segmented to form realistic experimental models of the pore structure. Hindered diffusion, explicitly taking into account the solute vs. pore size ratio, is simulated for all models to derive a quantitative expression of the hindrance factor, which describes the degree to which diffusion through a material is hindered compared to the diffusion in the bulk liquid depending on the size ratio. The result is a master curve describing hindered diffusion without specific surface interactions for all materials with comparable morphology, which potentially encompasses all sol-gel processed mesoporous silicas.

Details on the image acquisition, reconstructed microstructure morphology and the diffusion simulation will be presented and the crucial role of the combination of experiment and modelling discussed.


1. Reich, S.-J. et al. Hindrance Factor Expression for Diffusion in Random Mesoporous Adsorbents Obtained from Pore-Scale Simulations in Physical Reconstructions. Ind. Eng. Chem. Res. online (2018). doi:10.1021/acs.iecr.7b04840


Dr. Christian Kübel
Karlsruhe Institute of Technology (KIT)
Additional Authors:
  • Stefan-Johannes Reich
    Philipps-Universität Marburg
  • Artur Svidrytski
    Philipps-Universität Marburg
  • Dzmitry Hlushkou
    Philipps-Universität Marburg
  • Dr. Daniela Stoeckel
    Philipps-Universität Marburg
  • Dr. Alexandra Höltzel
    Philipps-Universität Marburg
  • Prof. Ulrich Tallarek
    Philipps-Universität Marburg