Effect of oxygen flow rate on long-term and short-term Schottky barrier modulations in Pd/IGZO/SiO2/p+-Si memristors. (January 2023)

• Record Type: Journal Article
• Authors: Lee, Hee Jun; Kim, Donguk; Choi, Woo Sik; Kim, Changwook; Choi, Sung-Jin; Bae, Jong-Ho; Kim, Dong Myong; Kim, Sungjun; Kim, Dae Hwan
• Is Part Of: Materials science in semiconductor processing. Volume 153(2023)
• Publication Date: 2023-01
• Subjects: Neuromorphic system -- Synaptic device -- Memristor -- Indium gallium zinc oxide -- Neuromorphic simulation; Semiconductors -- Periodicals; Integrated circuits -- Materials -- Periodicals; Semiconducteurs -- Périodiques; Circuits intégrés -- Matériaux -- Périodiques; Electronic journals; 621.38152
• DOI: 10.1016/j.mssp.2022.107183
• Languages: English
• ISSNs: 1369-8001

Abstract

Abstract: In this work, we investigate the long- and short-term Schottky barrier modulations in a Pd/IGZO/SiO2 /p + -Si memristor under oxygen flow rate (OFR) control. The thickness of the SiO2 layer verified using transmission electron microscopy (TEM) was found to affect resistive-switching characteristics such as the on/off ratio. A high barrier was observed corresponding to a high OFR in the thermionic emission model. In addition, we present an energy band diagram considering traps and oxygen vacancies for oxygen-rich (O-rich) and oxygen-poor (O-poor) devices. Moreover, physical parameters such as a change in barrier height, activation energy, and potentiation/depression were experimentally extracted through various pulse schemes. Experimental results reveal that an O-rich device has high accuracy with a neural network on the MNIST dataset. In this study, we optimized the resistive-switching characteristics by varying OFR as an experimental factor. Further, we provide guidelines for designing hardware-based neuromorphic systems by separating short- and long-term components.