Self-Doping Memristors with Equivalently Synaptic Ion Dynamics for Neuromorphic Computing

Abstract

The 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.

Hybrid oxide brain-inspired neuromorphic devices for hardware implementation of artificial intelligence

“…memristor performance [145]. Besides, Ag-doped Ta 2 O 5 [146], Ag-doped HfO x [147], Ag-doped MgO x [147], Ag-doped SiO x N y [147], Cu-Al-codoped SiO 2 and Cu-Ga-codoped SiO 2 [148] have been employed to fabricate memristive devices based on metal ion migration.…”

Magnetic Elements for Neuromorphic Computing

“…In addition, this "analog" behavior makes the memristor suitable for neuromorphic computing applications. A large number of publications describes the possible use of memristors as artificial synapses [66][67][68][69][70] or even neurons [71][72][73].…”

Cupper doping effect on the electrical characteristics of TiO2 based Memristor

“…Under the negative and positive pulse trains, memristor is revealed respectively high and low resistance switching, which can completely match with stimulus and blockage spike of the bio synapse [27]. Also, self-doping memristors introduced to emulate the ion dynamics (Ca 2+ ) of biological synapses in Ag/Ag: Ta2O5/Pt structure [28]. Another work is a penetrate Ag into oxide of Pt/SiOxNy:Ag/Pt device.…”

“…In neuromorphic engineering, CMOS based artificial synapses circuits have high power consumption due to multipart structure needs. The most attractive candidate among these structures are two terminal memristor which is exactly identical synapses [28]. Low power consumption and also three-dimensional scalability of memristors have advantages over conventional CMOS technology [30][31].…”