Local quantification of mesoporous silica microspheres using multiscale electron tomography and lattice Boltzmann simulations
Journal article, 2020
The multiscale pore structure of mesoporous silica microspheres plays an important role for tuning mass transfer kinetics in technological applications such as liquid chromatography. While local analysis of a pore network in such materials has been previously achieved, multiscale quantification of microspheres down to the nanometer scale pore level is still lacking. Here we demonstrate for the first time, by combining low convergence angle scanning transmission electron microscopy tomography (LC-STEM tomography) with image analysis and lattice Boltzmann simulations, that the multiscale pore network of commercial mesoporous silica microspheres can be quantified. This includes comparing the local tortuosity and intraparticle diffusion coefficients between different regions within the same microsphere. The results, spanning more than two orders of magnitude between nanostructures and entire object, are in good agreement with bulk characterization techniques such as nitrogen gas physisorption and add valuable local information for tuning mass transfer behavior (in liquid chromatography or catalysis) on the single microsphere level.
Scanning transmission electron microscopy
Quantitative electron tomography
Intraparticle diffusivity
Lattice Boltzmann simulations
Mesoporous silica
Author
Andreas J. Fijneman
Eindhoven University of Technology
Nouryon Pulp and Performance Chemicals AB
Maurits Goudzwaard
Eindhoven University of Technology
Arthur D.A. Keizer
Eindhoven University of Technology
Paul H.H. Bomans
Eindhoven University of Technology
Tobias Gebäck
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
M. Palmlof
Nouryon Pulp and Performance Chemicals AB
Michael Persson
Nouryon Pulp and Performance Chemicals AB
Joakim Högblom
Nouryon Pulp and Performance Chemicals AB
Gijsbertus de With
Eindhoven University of Technology
Heiner Friedrich
Eindhoven University of Technology
Microporous and Mesoporous Materials
1387-1811 (ISSN)
Vol. 302 110243Subject Categories
Other Computer and Information Science
Computer Vision and Robotics (Autonomous Systems)
Medical Image Processing
DOI
10.1016/j.micromeso.2020.110243