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Cited 3 time in webofscience Cited 4 time in scopus
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Cellulose Nanocrystal Based Bio-Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications

Authors
Hussain, TassawarAbbas, HaiderYoun, ChulminLee, HojinBoynazarov, TurgunKu, BoncheolJeon, Yu-RimHan, HoonheeLee, Jong HyeonChoi, ChanghwanChoi, Taekjib
Issue Date
Feb-2022
Publisher
WILEY
Keywords
cellulose nanocrystals; nanocomposites; bio-memristor; artificial synaptic devices; green-electronics; neuromorphic computing
Citation
ADVANCED MATERIALS TECHNOLOGIES, v.7, no.2, pp 1 - 13
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
ADVANCED MATERIALS TECHNOLOGIES
Volume
7
Number
2
Start Page
1
End Page
13
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/139672
DOI
10.1002/admt.202100744
ISSN
2365-709X
Abstract
Nanocomposites based on biomaterials are promising candidates for emerging green- electronics benefiting from environment-friendly, renewable, biocompatible, and biodegradable resources for sustainable research and development. Especially, the application of biocomposites-based memristor for simulating artificial synapses called bio-memristor has further facilitated the progress of ecologically benign bioelectronics. In this study, the authors present that the environment-friendly nanocomposites films, consisting of Ag nanoparticles and cellulose nanocrystal (CNC)-based bio-memristor with excellent bipolar resistive switching behavior can perform the artificial bio-synaptic emulation with continuous resistance modulation for memory storage and neuromorphic computing applications. The bio-memristor exhibits a large resistive switching (I-ON/OFF as high as approximate to 10(4) and ultralow SET/RESET voltage of approximate to 0.2 V) and reliable switching characteristics through the electrochemical formation/rupture of Ag metallic filaments within the nanocomposite layer. The device presents coexistence of digital and analog switching properties favorable for both nonvolatile digital memory and neuromorphic computing applications. By applying appropriate pulse stimulations to the device, the authors demonstrate biological synaptic functions, including long-term potentiation/depression, spike-rate-dependent plasticity, excitatory post-synaptic current, paired-pulse facilitation, and paired-pulse depression. Thus, this CNC-based bio-memristor as an effective artificial synaptic device is beneficial towards the realization of green-electronics and bio-inspired neuromorphic systems.
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