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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

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

Yaoyuan Wang, Ziyang Zhang, Mingkun Xu

ACS Applied Materials & Interfaces

|May 24, 2019

Summary

Electronic memristors mimicking synaptic ion dynamics enable neuromorphic computing. These Ag/Ag:Ta2O5/Pt devices emulate calcium (Ca2+) ion behavior for short- and long-term plasticity (STP and LTP) in artificial synapses.

Keywords:

dynamics interface memristor neuromorphic computing synaptic plasticity

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Area of Science:

Materials Science
Neuroscience
Computer Engineering

Background:

Biological synapses utilize calcium (Ca2+) ion dynamics for short-term plasticity (STP) and long-term plasticity (LTP).
Neuromorphic computing aims to replicate brain functions using electronic devices, requiring emulation of synaptic behaviors.
Existing synaptic devices often mimic qualitative behaviors, but few replicate the physical dynamics of Ca2+ ions in STP and LTP.

Purpose of the Study:

To develop electronic memristors that emulate the physical behavior of Ca2+ ion dynamics in biological synapses.
To investigate the potential of these devices for realizing advanced neuromorphic computing functionalities.
To demonstrate STP, LTP, and their transition in a novel memristor architecture.

Main Methods:

Fabrication of Ag/Ag:Ta2O5/Pt self-doping memristors utilizing conductive filaments from double sources.
Characterization of device behavior under voltage sweeps and pulse stimuli.
Nanoparticle dynamic simulations to correlate Ag atom movement with Ca2+ ion dynamics.
Implementation and simulation of a perceptron network with an STP to LTP transition layer.

Main Results:

The developed memristors exhibited unique double-switching behavior.
Devices successfully emulated essential synaptic plasticity behaviors: STP, LTP, STP to LTP transition, and spike-rate-dependent plasticity.
Experimental and simulation results confirmed that Ag atoms mimic Ca2+ dynamics in synaptic terminals.
A perceptron network utilizing these memristors efficiently performed noisy figure recognition tasks.

Conclusions:

Ag/Ag:Ta2O5/Pt self-doping memristors effectively emulate biological synaptic Ca2+ ion dynamics.
These devices show significant promise for creating hardware components in neuromorphic systems.
The demonstrated capabilities pave the way for more sophisticated brain-inspired computing architectures.