Reservoir computing and advanced synaptic plasticity of sputter-deposited ZnO memristors with controllable threshold and nonvolatile switching behavior

Muhammad Ismail, Euncho Seo, Maria Rasheed, Yongjin Park, Chandreswar Mahata, Sungjun Kim

Research output: Contribution to journalArticlepeer-review

Abstract

This study presents an ITO/ZnO/ITO/Si memristor fabricated via reactive sputtering for use in advanced analog synaptic plasticity and reservoir computing (RC) systems. The proposed device exhibited stable threshold and nonvolatile switching characteristics by effectively controlling the current compliance (ICC) limit. Multilevel data storage was achieved through controlled multistate switching via reset-stop voltage and ICC. X-ray diffraction analysis confirmed the formation of a polycrystalline ZnO film with a 12:8 oxygen-to-argon ratio, which facilitated the generation of oxygen-vacancy conductive filaments. The memristor effectively replicated key synaptic characteristics such as long-term potentiation, long-term depression, spike-amplitude/width-dependent plasticity, spike-rate-dependent plasticity, and the transition from short-term to long-term memory. The RC system processed binary 4-bit codes and recognized different digits, achieving 98.84% accuracy in handwritten digit recognition using a convolutional neural network simulation, highlighting its potential for efficient image processing applications.

Original languageEnglish
Article number224701
JournalJournal of Chemical Physics
Volume161
Issue number22
DOIs
StatePublished - 14 Dec 2024

Fingerprint

Dive into the research topics of 'Reservoir computing and advanced synaptic plasticity of sputter-deposited ZnO memristors with controllable threshold and nonvolatile switching behavior'. Together they form a unique fingerprint.

Cite this