Automatic electron hologram acquisition of catalyst nanoparticles using particle detection with image processing and machine learning

IR (HANDLE) Open Access
  • Ichihashi, Fumiaki
    Research & Development Group, Hitachi, Ltd
  • Koyama, Akira
    Department of Applied Quantum Physics and Nuclear Engineering, Kyushu University
  • Akashi, Tetsuya
    Research & Development Group, Hitachi, Ltd
  • Miyauchi, Shoko
    Graduate School of Information Science and Electronical Engineering, Kyushu University
  • Morooka, Ken'ichi
    Graduate School of Natural Science and Technology, Okayama University
  • Hojo, Hajime
    Department of Advanced Materials Science and Engineering, Faculty of Engineering Sciences, Kyushu University
  • Einaga, Hisahiro
    Department of Advanced Materials Science and Engineering, Faculty of Engineering Sciences, Kyushu University
  • Takahashi, Yoshio
    Research & Development Group, Hitachi, Ltd
  • Tanigaki, Toshiaki
    Research & Development Group, Hitachi, Ltd
  • Shinada, Hiroyuki
    Research & Development Group, Hitachi, Ltd
  • Murakami, Yasukazu
    Department of Applied Quantum Physics and Nuclear Engineering, Kyushu University The Ultramicroscopy Research Center, Kyushu University

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Description

To enable better statistical analysis of catalyst nanoparticles by high-resolution electron holography, we improved the particle detection accuracy of our previously developed automated hologram acquisition system by using an image classifier trained with machine learning. The detection accuracy of 83% was achieved with the small training data of just 232 images showing nanoparticles by utilizing transfer learning based on VGG16 to train the image classifier. Although the construction of training data generally requires much effort, the time needed to select the training data candidates was significantly shortened by utilizing a pattern matching technique. Experimental results showed that the high-resolution hologram acquisition efficiency was improved by factors of about 100 and 6 compared to a scan method and a pattern-matching-only method, respectively.

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Details 詳細情報について

  • CRID
    1050586411175747968
  • ISSN
    10773118
    00036951
  • HANDLE
    2324/7161519
  • Text Lang
    en
  • Article Type
    journal article
  • Data Source
    • IRDB

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