Electrically-generated memristor based on inkjet printed silver nanoparticles. Issue 8 (20th June 2019)

• Record Type: Journal Article
• Authors: Yoon, Kyung Jean; Han, Jin-Woo; Moon, Dong-Il; Seol, Myeong Lok; Meyyappan, M.; Kim, Han Joon; Hwang, Cheol Seong
• Is Part Of: Nanoscale advances. Volume 1:Issue 8(2019)
• Page Start: 2990
• Page End: 2998
• Publication Date: 2019-06-20
• Subjects: 620.5
• DOI: 10.1039/c9na00329k
• Languages: English
• ISSNs: 2516-0230

Abstract

Abstract : Wide range of memristor behavior is investigated based on electrically-induced oxide electrolyte from inkjet-printed silver. Abstract : A method to electrically induce memristor performance from inkjet-printed silver (Ag) nanoparticles is presented, which is effective on a specifically designed hourglass-shaped Ag metal device. Joule heating-induced oxidation in the bottleneck region, when applying a high current to the device, results in a metal-electrolyte-metal structure produced from just a single metal ink for the memristor operation. This electrically induced memristor shows a nonuniform dispersion of the Ag nanoparticles within the oxide electrolyte layer, depending on the bias polarity adopted during the initial metal rupture process. A versatile and useful range of controllable memristor behaviors, from volatile threshold switching to nonvolatile unipolar as well as bipolar resistive switching, are observed based on the reversible rejuvenation and rupture of the Ag nanofilaments according to the Ag cation migration within the oxide electrolyte. The interplay between the electric field induced redox reaction and thermal diffusion of the Ag nanoparticles constitutes the primary reason for the different switching behaviors, further supported by thermo-field simulation results. The bipolar switching memristor demonstrates reliable endurance even under harsh DC switching conditions with low power consumption compared with its unipolar switching operation. The observed range of controllable switching behavior can be exploited for future low power flexible memory, as a selector in crossbar memory architecture, synaptic learning, and others.