Session Details

[25p-61C-1~13]23.1 Joint Session N "Informatics"

Mon. Mar 25, 2024 1:00 PM - 4:30 PM JST
Mon. Mar 25, 2024 4:00 AM - 7:30 AM UTC
61C (Building No. 6)
Toyohiro Chikyo(NIMS), Masato Kotsugi(Tokyo Univ. of Sci.)

[25p-61C-1]Development of machine learning potentials for mixed Ge-Ni system

〇Machika Naito1, Yusuke Nishimura1, Takanobu Watanabe1 (1.Waseda Univ.)

[25p-61C-2]Investigation of effective datasets to train neural network interatomic potential for SiO2/Si interfaces

〇Kentaro Hirai1, Kotaro Takematsu1, Takanobu Watanabe1 (1.Waseda Univ.)

[25p-61C-3]Physics-informed data-driven discovery of high thermal conductive polymer crystals

〇(D)Rohit Sanjay Dahule1, Kenji Oqmhula1, Ryo Maezono1, Kenta Hongo1 (1.JAIST)

[25p-61C-4]The mechanism of occurrence of breakthrough scientific research based on Structural Hall Theory

〇Keisuke Shinagawa

[25p-61C-5]Detection of the horizontal propagation vector in EEG signals

〇Taisei Nakayama1, Riku Takamura1, Hirohito Sawahata1 (1.Kosen, Ibaraki Col)

[25p-61C-6]Somatosensory EEG based brain-machine interface for substituting finger motion

〇Shota Tonochi1, Hirohito Sawahata1 (1.Kosen, Ibaraki Col.)

[25p-61C-7]Coherence influx is indispensable for quantum reservoir computing

〇Shumpei Kobayashi1, Hoan Tran3, Kohei Nakajima2,3,1 (1.CI, Univ. Tokyo, 2.MI, Univ. Tokyo, 3.AI, Univ. Tokyo)

[25p-61C-8]Multi-valued inverse problem analysis: An example for analysis of defect distribution and electron transport in amorphous oxide semiconductor transistors

〇Masatoshi Kimura1, Kuan-Ju Zhou2, Keisuke Ide1, Takayoshi Katase1, Hidenori Hiramatsu1, Hideo Hosono1, Ting-Chang Chang2, Toshio Kamiya1 (1.Tokyo Tech, 2.NSYSU)

[25p-61C-9]Machine Learning for Accelerated Diffusion of Impurity in Silicon

〇(M2)Daiki Shimoda1, Kentaro Kutsukake2,3, Toru Ujihara1,3 (1.Grad. School of Eng. Nagoya Univ., 2.AIP RIKEN, 3.IMaSS Nagoya Univ.)

[25p-61C-10]Residual Stress Distribution in Unitary Interconnect Metals for Beyond 2nm Logic Nodes: A Molecular Dynamics Study Based on Neural Network Potential

〇Shuichiro Hashimoto1, Takanobu Watanabe1,2 (1.Wasda Univ. SEES, 2.Waseda Univ. FSE)

[25p-61C-11]Exploration of Materials Design Guideline via Fusion of Machine Learning and Domain Knowledge for Anion Exchange Membrane Polymer

〇YinKan Phua1, Tsuyohiko Fujigaya1,2,3, Koichiro Kato1,2,4 (1.Grad. Sch. of Eng., Kyushu Univ., 2.CMS, Kyushu Univ., 3.WPI-I2CNER, Kyushu Univ., 4.RIIT, Kyushu Univ.)

[25p-61C-12]Polymer exploration for electrical equipment using self-supervised deep learning model

〇Chihiro Tateyama1, Gen Komiya1, Hiroyasu Tarui1 (1.Toshiba Infrastructure Systems & Solutions Corp.)

[25p-61C-13]PE Biodegradability Prediction using PoLyInfo RDF Database Integration

〇Masashi Ishii1, Koichi Sakamoto1, Natsuko Ishikawa2 (1.NIMS, 2.NITE)