Oh, Jiwon
Song, Hyewon
Shin, Euncheol
Yang, Heesun
Lim, Jongtae
Hwang, Jin-Ha https://orcid.org/0000-0002-9581-7413
Funding for this research was provided by:
National Research Foundation of Korea (NRF-2016R1D1A1B01015557)
Article Title: Machine Learning–Assisted Thin-Film Transistor Characterization: A Case Study of Amorphous Indium Gallium Zinc Oxide (IGZO) Thin-Film Transistors
Journal Title: ECS Journal of Solid State Science and Technology
Article Type: paper
Copyright Information: © 2022 The Electrochemical Society (“ECS”). Published on behalf of ECS by IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Publication dates
Date Received: 2022-02-16
Date Accepted:
Online publication date: 2022-05-12