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Use and Application of 2D Layered Materials-Based Memristors for Neuromorphic Computing

This work presents a step forward in the use of 2D layered materials (2DLM),
specifically hexagonal boron nitride (h-BN), for the fabrication of memristors.
In this study, we fabricate, characterize, and use h-BN based memristors with
Ag/few-layer h-BN/Ag structure to implement a fully functioning artificial leaky
integrate-and-fire neuron on hardware. The devices showed volatile resistive
switching behavior with no electro-forming process required, with relatively low
VSET and long endurance of beyond 1.5 million cycles. In addition, we present
some of the failure mechanisms in these devices with some statistical analyses to
understand the causes, as well as a statistical study of both cycle-to-cycle and
device-to-device variabilities in 20 devices.
Moreover, we study the use of these devices in implementing a functioning
artificial leaky integrate-and-fire neuron similar to a biological neuron in the brain.
We provide SPICE simulation as well as hardware implementation of the artificial
neuron that are in full agreement, showing that our device could be used for such
application. Additionally, we study the use of these devices as an activation
function for spiking neural networks (SNNs) by providing a SPICE simulation of
a fully trained network, where the artificial spiking neuron is connected to the
output terminal of a crossbar array. The SPICE simulations provide a proof of
concept for using h-BN based memristor for activation function for SNNs.

Identiferoai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/687565
Date01 February 2023
CreatorsAlharbi, Osamah
ContributorsLanza, Mario, Physical Science and Engineering (PSE) Division, Inal, Sahika, Salama, Khaled N.
Source SetsKing Abdullah University of Science and Technology
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Rights2024-02-08, At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis will become available to the public after the expiration of the embargo on 2024-02-08.

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