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Trainable Bilingual Synaptic Functions in Bio-enabled Synaptic Transistorsopen access

Authors
Han, Moon JongTsukruk, Vladimir V.
Issue Date
Sep-2023
Publisher
AMER CHEMICAL SOC
Keywords
brain-inspired computing; photonic cellulose nanocrystals; bio-organic field-effect transistors; neuromorphic behaviors; optoelectronic synaptic devices
Citation
ACS NANO, v.17, no.19, pp.18883 - 18892
Journal Title
ACS NANO
Volume
17
Number
19
Start Page
18883
End Page
18892
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/89403
DOI
10.1021/acsnano.3c04113
ISSN
1936-0851
Abstract
The signal transmission of the nervous system is regulated by neurotransmitters. Depending on the type of neurotransmitter released by presynaptic neurons, neuron cells can either be excited or inhibited. Maintaining a balance between excitatory and inhibitory synaptic responses is crucial for the nervous system's versatility, elasticity, and ability to perform parallel computing. On the way to mimic the brain's versatility and plasticity traits, creating a preprogrammed balance between excitatory and inhibitory responses is required. Despite substantial efforts to investigate the balancing of the nervous system, a complex circuit configuration has been suggested to simulate the interaction between excitatory and inhibitory synapses. As a meaningful approach, an optoelectronic synapse for balancing the excitatory and inhibitory responses assisted by light mediation is proposed here by deploying humidity-sensitive chiral nematic phases of known polysaccharide cellulose nanocrystals. The environment-induced pitch tuning changes the polarization of the helicoidal organization, affording different hysteresis effects with the subsequent excitatory and inhibitory nonvolatile behavior in the bio-electrolyte-gated transistors. By applying voltage pulses combined with stimulation of chiral light, the artificial optoelectronic synapse tunes not only synaptic functions but also learning pathways and color recognition. These multifunctional bio-based synaptic field-effect transistors exhibit potential for enhanced parallel neuromorphic computing and robot vision technology.
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