Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

  • Cheng Wang
  • Qing N. Chan
  • Renlin Zhang
  • Sanghoon Kook
  • Evatt R. Hawkes
  • Guan H. Yeoh
  • Paul R. Medwell
Research Paper


The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.


Thermophoretic sampling Image processing and enhancement Soot morphology Transmission electron microscopy Aerosols Nanoparticles 



The authors wish to acknowledge the financial support of Australia Research Council (ARC) and University of New South Wales (UNSW) Australia. The authors would also like to acknowledge the many detailed and constructive comments by the anonymous reviewers of this paper. Addressing their comments has strengthened this document considerably.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Cheng Wang
    • 1
  • Qing N. Chan
    • 1
  • Renlin Zhang
    • 1
  • Sanghoon Kook
    • 1
  • Evatt R. Hawkes
    • 1
    • 2
  • Guan H. Yeoh
    • 1
  • Paul R. Medwell
    • 3
    • 4
  1. 1.School of Mechanical and Manufacturing EngineeringUNSWSydneyAustralia
  2. 2.School of Photovoltaic and Renewable Energy EngineeringUNSWSydneyAustralia
  3. 3.Centre for Energy TechnologyThe University of AdelaideAdelaideAustralia
  4. 4.School of Mechanical EngineeringThe University of AdelaideAdelaideAustralia

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