Machine Learning–Assisted Thin-Film Transistor Characterization: A Case Study of Amorphous Indium Gallium Zinc Oxide (IGZO) Thin-Film Transistors

• Published in: ECS journal of solid state science and technology Vol. 11; no. 5; pp. 55004 - 55013
• Main Authors: Oh, Jiwon, Song, Hyewon, Shin, Euncheol, Yang, Heesun, Lim, Jongtae, Hwang, Jin-Ha
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.05.2022
• Subjects: IGZO TFT; K-Means Clustering; Machine Learning; Neural Networks; TFT Parameters

Machine learning was applied to classify the device characteristics of indium gallium zinc oxide (IGZO) thin-film transistors (TFTs). A K-means approach was employed for initial clustering of IGZO transfer curves into three of four grades (high, medium-high, medium, and low) of TFT performance accor...