Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Bidirectional Electric-induced Conductance based on GeTe/Sb2Te3 Interfacial Phase Change Memory for Neuro-inspired Computing

Version 1 : Received: 24 September 2021 / Approved: 27 September 2021 / Online: 27 September 2021 (11:32:46 CEST)

A peer-reviewed article of this Preprint also exists.

Kang, S.-Y.; Jin, S.-M.; Lee, J.-Y.; Woo, D.-S.; Shim, T.-H.; Nam, I.-H.; Park, J.-G.; Sutou, Y.; Song, Y.-H. Bidirectional Electric-Induced Conductance Based on GeTe/Sb2Te3 Interfacial Phase Change Memory for Neuro-Inspired Computing. Electronics 2021, 10, 2692. Kang, S.-Y.; Jin, S.-M.; Lee, J.-Y.; Woo, D.-S.; Shim, T.-H.; Nam, I.-H.; Park, J.-G.; Sutou, Y.; Song, Y.-H. Bidirectional Electric-Induced Conductance Based on GeTe/Sb2Te3 Interfacial Phase Change Memory for Neuro-Inspired Computing. Electronics 2021, 10, 2692.

Journal reference: Electronics 2021, 10, 2692
DOI: 10.3390/electronics10212692

Abstract

Corresponding to the principles of biological synapses, an essential prerequisite for hardware neural networks using electronics devices is continuous regulation of conductance. We implemented artificial synaptic characteristics in a (GeTe/Sb2Te3)16 iPCM with a superlattice structure under optimized identical pulse trains. Based on atomically controlling the Ge switch in the phase transition that appears in the GeTe/Sb2Te3 superlattice structure, multiple conductance states were implemented by applying the appropriate electrical pulses. Furthermore, we found that the bidirectional switching behavior of a (GeTe/Sb2Te3)16 iPCM can achieve a desired resistance level using the pulse width. Therefore, we also fabricated a Ge2Sb2Te5 PCM and designed a pulse scheme based on the phase transition mechanism to compare to the (GeTe/Sb2Te3)16 iPCM. We designed an identical pulse scheme that implements linear and symmetrical LTP and LTD based on the iPCM mechanism. As a result, the (GeTe/Sb2Te3)16 iPCM showed relatively excellent synaptic characteristics by implementing gradual conductance modulation, a nonlinearity value of 0.32, and LTP/LTD 40 conductance states using identical pulses trains. Our results demonstrate the general applicability of the artificial synaptic device for potential use in neuro-inspired computing and next generation non-volatile memory.

Keywords

interfacial phase change memory; phase change memory; artificial synaptic device; superlattice; neuromorphic devices

Subject

ENGINEERING, Electrical & Electronic Engineering

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