am9b04901_si_001.pdf (1.45 MB)
Self-Doping Memristors with Equivalently Synaptic Ion Dynamics for Neuromorphic Computing
journal contribution
posted on 2019-05-23, 00:00 authored by Yaoyuan Wang, Ziyang Zhang, Mingkun Xu, Yifei Yang, Mingyuan Ma, Huanglong Li, Jing Pei, Luping ShiThe
accumulation and extrusion of Ca2+ ions in the pre- and
post-synaptic terminals play crucial roles in initiating short- and
long-term plasticity (STP and LTP) in biological synapses, respectively.
Mimicking these synaptic behaviors by electronic devices represents
a vital step toward realization of neuromorphic computing. However,
the majority of reported synaptic devices usually focus on the emulation
of qualitatively synaptic behaviors; devices that can truly emulate
the physical behavior of the synaptic Ca2+ ion dynamics
in STP and LTP are rarely reported. In this work, Ag/Ag:Ta2O5/Pt self-doping memristors were developed to equivalently
emulate the Ca2+ ion dynamics of biological synapses. With
conductive filaments from double sources, these memristors produced
unique double-switching behavior under voltage sweeps and demonstrated
several essential synaptic behaviors under pulse stimuli, including
STP, LTP, STP to LTP transition, and spike-rate-dependent plasticity.
Experimental results and nanoparticle dynamic simulations both showed
that Ag atoms from double sources could mimic Ca2+ dynamics
in the pre- and post-synaptic terminals under stimuli. A perceptron
network with an STP to LTP transition layer based on the self-doping
memristors was also introduced and evaluated; simulations showed that
this network could solve noisy figure recognition tasks efficiently.
All of these results indicate that the self-doping memristors are
promising components for future hardware creation of neuromorphic
systems and emulate the characteristics of the brain.