A Dynamical Compact Model of Diffusive and Drift Memristors for Neuromorphic Computing (Adv. Electron. Mater. 8/2022). (23rd August 2022)

• Record Type: Journal Article
• Authors: Zhuo, Ye; Midya, Rivu; Song, Wenhao; Wang, Zhongrui; Asapu, Shiva; Rao, Mingyi; Lin, Peng; Jiang, Hao; Xia, Qiangfei; Williams, R. Stanley; Yang, J. Joshua
• Is Part Of: Advanced Electronic Materials. Volume 8:Number 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-23
• Subjects: Materials -- Electric properties -- Periodicals; Materials science -- Periodicals; Magnetic materials -- Periodicals; Electronic apparatus and appliances -- Periodicals; 537
• DOI: 10.1002/aelm.202270040
• Languages: English
• ISSNs: 2199-160X

Abstract

Abstract : Neuromorphic Computing Different from memory applications where only the static ending states are used, neuromorphic computing with memristors utilizes their dynamical switching process itself, which calls for a comprehensive dynamical memristor model. Such a model shown here can reproduce the long‐term memory of drift memristors and the short‐term plasticity of diffusive memristors. It captures quasi‐static and dynamic characteristics of these devices, demonstrating a good agreement with the experimental data. More details can be found in article number 2100696 by J. Joshua Yang and co‐workers.