Logo image
Tunable Resistive Switching Enabled by Malleable Redox Reaction in the Nano-Vacuum Gap
Journal article   Peer reviewed

Tunable Resistive Switching Enabled by Malleable Redox Reaction in the Nano-Vacuum Gap

Xinglong Ji, Chao Wang, Kian Guan Lim, Chun Chia Tan, Tow Chong Chong and Rong Zhao
ACS applied materials & interfaces, Vol.11(23), pp.20965-20972
12/06/2019
PMID: 31117430

Abstract

Materials Science Materials Science, Multidisciplinary Nanoscience & Nanotechnology Science & Technology Science & Technology - Other Topics Technology
Neuromorphic computing has emerged as a highly promising alternative to conventional computing. The key to constructing a large-scale neural network in hardware for neuromorphic computing is to develop artificial neurons with leaky integrate-and-fire behavior and artificial synapses with synaptic plasticity using nanodevices. So far, these two basic computing elements have been built in separate devices using different materials and technologies, which poses a significant challenge to system design and manufacturing. In this work, we designed a resistive device embedded with an innovative nano-vacuum gap between a bottom electrode and a mixed-ionic-electronic-conductor (MIEC) layer. Through redox reaction on the MIEC surface, metallic filaments dynamically grew within the nano-vacuum gap. The nano-vacuum gap provided an additional control factor for controlling the evolution dynamics of metallic filaments by tuning the electron tunneling efficiency, in analogy to a pseudo-three-terminal device, resulting in tunable switching behavior in various forms from volatile to nonvolatile switching in a single device. Our device demonstrated cross-functions, in particular, tunable neuronal firing and synaptic plasticity on demand, providing seamless integration for building large-scale artificial neural networks for neuromorphic computing.

Metrics

1 Record Views

Details

Logo image