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Related Concept Videos

Scanning Electron Microscopy01:07

Scanning Electron Microscopy

A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
Accelerated...
Preparation of Samples for Electron Microscopy01:20

Preparation of Samples for Electron Microscopy

To be visualized by an electron microscope, either transmission or scanning, biological samples need to be fixed (stabilized) so the electron beam does not destroy them and dried thoroughly (desiccated/dehydrated) so the vacuum does not affect them. Fixation needs to be done as quickly as possible because the sample properties will start changing as soon as it is removed from its natural environment. For example, in a tissue sample, the oxygen levels begin decreasing, causing an altered...

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Related Experiment Video

Updated: Jul 9, 2026

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SEM Image Processing Assisted by Deep Learning to Quantify Mesoporous γ-Alumina Spatial Heterogeneity and Its

Aleksandra Głowska1,2, Elsa Jolimaitre2, Adam Hammoumi2

  • 1Centre for Nature Inspired Engineering and Department of Chemical Engineering, University College London, London WC1E 7JE, United Kingdom.

The Journal of Physical Chemistry. C, Nanomaterials and Interfaces
|May 29, 2024
PubMed
Summary

Characterizing porous catalyst supports like gamma-alumina (γ-Al2O3) is key for better catalyst design. Spatial heterogeneity in porosity has a minor impact on tortuosity unless inclusion content is high and porosity differences are significant.

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Area of Science:

  • Materials Science
  • Chemical Engineering
  • Catalysis

Background:

  • Porous heterogeneous catalyst supports significantly influence mass transfer kinetics.
  • Understanding structure-transport relationships is crucial for designing advanced catalysts with improved performance and durability.

Purpose of the Study:

  • To quantify the spatial heterogeneity of gamma-alumina (γ-Al2O3) using advanced imaging and analysis.
  • To develop a model for γ-Al2O3 organization and predict tortuosity based on porosity variations.
  • To assess the impact of spatial porosity heterogeneity on effective tortuosity.

Main Methods:

  • Combined N2 adsorption/desorption and mercury porosimetry with advanced SEM imaging.
  • Utilized deep learning semantic segmentation and calibrated gray-level analysis for SEM image processing.
  • Applied effective medium theory (EMT)-based models for tortuosity factor prediction.

Main Results:

  • Quantified inclusion volume fraction and interphase porosity difference in γ-Al2O3.
  • Found negligible impact of spatial porosity heterogeneity on tortuosity for studied aluminas.
  • Determined that heterogeneity becomes significant at ≥30% inclusion content and >20% interphase porosity difference.

Conclusions:

  • Developed a machine-learning-supported methodology for porous material characterization.
  • The proposed platform offers a general approach for analyzing spatial heterogeneity in porous materials.
  • Highlights the conditions under which porosity heterogeneity significantly affects catalyst support performance.