2022 Fiscal Year Final Research Report
Understanding the three-dimensional multiscale porous microstructures by applying deep neural networks
| Project/Area Number |
21K14090
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 19020:Thermal engineering-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
SCIAZKO Anna 東京大学, 生産技術研究所, 特任助教 (30898945)
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| Project Period (FY) |
2021-04-01 – 2023-03-31
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| Keywords | solid oxide fuel cell / machine learning / 3D microstructure / FIB-SEM / GAN network / semantic segmentation / super-resolution / artificial structure |
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| Outline of Final Research Achievements |
An automated microstructure analysis framework using machine learning was developed. The framework was built to improve three-dimensional (3D) microscopy analysis by super resolution and semantic segmentation algorithms. The developed framework can contribute in shortening actual measurement time up to 8 times and data post-processing time by two orders of magnitude. Furthermore, a novel method with generative network was proposed to create an artificial 3D microstructure model from a single two-dimensional image. Additionally, the generative network trained with microstructure datasets, can fabricate realistic microstructure models with predefined properties and gradients. The automated segmentation framework was used to characterize gadolinium doped ceria ceria-based solid oxide fuel (SOFC) anodes with the controlled properties (porosity, material composition, and particle size) and it enables to reconstruct SOFC anode with carbon deposition.
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| Free Research Field |
Energy engineering
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| Academic Significance and Societal Importance of the Research Achievements |
The porous media found interest in many fields of engineering. Particularly, the porous electrode microstructure determines the performances of fuel cells and batteries. This study proposed comprehensive framework for analyzing porous media microstructures based on machine learning methods.
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