Application of machine learning for high-performance multicrystalline materials

Noritaka Usami, Kentaro Kutsukake, Takuto Kojima, Hiroaki Kudo, Tetsuya Matsumoto, Tatsuya Yokoi, Yasuo Shimizu, Yutaka Ohno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We report on our recent attempt to pioneer “multicrystalline informatics” through collaboration of experiments, theory, computation, and machine learning to establish universal guidelines how we can obtain high-performance multicrystalline materials. We employ silicon as a model material, and develop various useful machine learning models. One example is a neural network to predict distribution of crystal orientations in a large-area sample from multiple optical images. Transfer learning of pre-trained image classifier could predict spatial distribution of probability of dislocations generation from photoluminescence images. Extracted regions with high probability of dislocations generation could be characterized by multiscale experiments as well as computation using artificial-neural-network interatomic potential to disclose the physics behind. The obtained knowledge could be useful for process development of high-performance multicrystalline materials.

Original languageEnglish
Title of host publication239th ECS Meeting with the 18th International Meeting on Chemical Sensors, IMCS 2021 - High Purity and High Mobility Semiconductors 16
EditorsE. Simoen, O. Kononchuk, O. Nakatsuka, C. Claeys
PublisherIOP Publishing Ltd.
Pages11-16
Number of pages6
Edition4
ISBN (Electronic)9781607685395
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event239th ECS Meeting with the 18th International Meeting on Chemical Sensors, IMCS 2021 - Chicago, United States
Duration: 2021 May 302021 Jun 3

Publication series

NameECS Transactions
Number4
Volume102
ISSN (Print)1938-6737
ISSN (Electronic)1938-5862

Conference

Conference239th ECS Meeting with the 18th International Meeting on Chemical Sensors, IMCS 2021
Country/TerritoryUnited States
CityChicago
Period21/5/3021/6/3

ASJC Scopus subject areas

  • Engineering(all)

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