Deep learning-enabled prediction of 2D material breakdown

• Main Authors: Huan, Yan Qi, Liu, Yincheng, Goh, Kuan Eng Johnson, Wong, Swee Liang, Lau, Chit Siong
• Other Authors: PHYSICS
• Format: Article
• Language: English
• Published: IOP PUBLISHING LTD 2021
• Subjects: Science & Technology; Technology; Physical Sciences; Nanoscience & Nanotechnology; Materials Science, Multidisciplinary; Physics, Applied; Science & Technology - Other Topics; Materials Science; Physics; machine learning; convolutional neural network; long short-term memory; electric breakdown; transition metal dichalcogenides; molybdenum disulfide; field-effect transistor; FIELD-EFFECT TRANSISTORS; MONOLAYER MOS2; ELECTRICAL BREAKDOWN; INTEGRATED-CIRCUITS; GRAPHENE
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/202309
• Institution: National University of Singapore

10.1088/1361-6528/abd655