2023年第70回応用物理学会春季学術講演会

講演情報

シンポジウム(口頭講演)

シンポジウム » 誘電体研究における機械学習

[16a-A404-1~7] 誘電体研究における機械学習

2023年3月16日(木) 09:00 〜 12:30 A404 (6号館)

齋藤 真澄(キオクシア)、平永 良臣(東北大)

10:00 〜 10:30

[16a-A404-3] Machine learning for discovery of meaningful chemical and physical contributors to piezoresponse force microscopy

Nazanin Bassiri-Gharb1 (1.Georgia Tech)

キーワード:machine learning, piezoresponse force microscopy, PFM

This talk provides an overview of machine learning methods applied to characterization of ferroelectric materials through piezoresponse force microscopy (PFM), and particularly the resonant PFM approaches. I will specifically discuss data curation to apply physical and chemical constraints to machine learning, as well as a method to mask or enhance different contributions to the signal.