Sessions

Symposium » Machine learning on dielectrics study

Symposium (Oral)

[16a-A404-1~7] Machine learning on dielectrics study

Thu. Mar 16, 2023 9:00 AM - 12:30 PM A404 (Building No. 6)

Masumi Saitoh(Kioxia), Yoshiomi Hiranaga(Tohoku Univ.)

△：Presentation by Applicant for JSAP Young Scientists Presentation Award
▲：English Presentation
▼：Both of Above
No Mark：None of Above

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9:00 AM - 9:30 AM

[16a-A404-1] Data driven ferroelectric materials study using first-principles calculations

〇Hiroki Moriwake^1,2 (1.JFCC, 2.Tokyo Inst. Technology)

9:30 AM - 10:00 AM

[16a-A404-2] Research on Ferroelectric and Piezoelectric Materials Using Machine Learning

〇Takuya Hoshina¹ (1.Tokyo Tech.)

10:00 AM - 10:30 AM

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

〇Nazanin Bassiri-Gharb¹ (1.Georgia Tech)

10:45 AM - 11:00 AM

[16a-A404-4] Statistical Evaluation of Correlation Between Grain Boundaries and Ferroelectric Domain Behavior Based on Machine Learning Analysis of Local C-V Maps

〇Yoshiomi Hiranaga¹, Yuki Noguchi¹, Takanori Mimura², Takao Shimizu², Hiroshi Funakubo², Yasuo Cho¹ (1.Tohoku Univ., 2.Tokyo Tech.)

11:00 AM - 11:30 AM

[16a-A404-5] Reservoir computing utilizing nonlinear dynamics of ferroelectric materials

〇Kasidit Toprasertpong¹, Eishin Nako¹, Ryosho Nakane¹, Mitsuru Takenaka¹, Shinichi Takagi¹ (1.Univ. Tokyo)

11:30 AM - 12:00 PM

[16a-A404-6] Physical reservoirs based on molecular dynamics and electrochemical reactions

〇Kentaro Kinoshita¹ (1.Tokyo Univ. Sci.)

12:00 PM - 12:30 PM

[16a-A404-7] Design of Neuromorphic Information Devices Using Protons

〇Takeaki Yajima¹ (1.Kyushu Univ.)

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