The 82nd JSAP Autumn Meeting 2021

Presentation information

Oral presentation

12 Organic Molecules and Bioelectronics » 12.2 Characterization and Materials Physics

[11a-N323-1~9] 12.2 Characterization and Materials Physics

Sat. Sep 11, 2021 9:00 AM - 11:30 AM N323 (Oral)

Satoshi Kera(IMS), Hirofumi Tanaka(Kyushu Inst. of Tech.)

11:15 AM - 11:30 AM

[11a-N323-9] Fatigue life prediction of cyclic bending in polymer films by machine learning

Masayuki Kishino1, Ryo Taguchi1, Norihisa Akamatsu1, Atsushi Shishido1 (1.Lab. for Chem. & Life Sci., Tokyo Tech)

Keywords:fatigue life, machine learning, bending

Polymer films are used for a substrate of flexible electronic devices. Such substrates are required to be durable against cyclic bending. Therefore, predicting fatigue life of bending polymer films enables us to design an appropriate polymer substrate. However, a huge number of experiments are required to predict the fatigue life by a conventional method. In this study, we predicted the fatigue life of bending polymer films by machine learning.