Literature DB >> 34279076

Flexible Artificial Synapses with a Biocompatible Maltose-Ascorbic Acid Electrolyte Gate for Neuromorphic Computing.

Wei Qin1, Byung Ha Kang1, Hyun Jae Kim1.   

Abstract

As constructing hardware technology is widely regarded as an important step toward realizing brain-like computers and artificial intelligence systems, the development of artificial synaptic electronics that can simulate biological synaptic functions is an emerging research field. Among the various types of artificial synapses, synaptic transistors using an electrolyte as the gate electrode have been implemented as the high capacitance of the electrolyte increases the driving current and lowers operating voltages. Here, transistors using maltose-ascorbic acid as the proton-conducting electrolyte are proposed. A novel electrolyte composed of maltose and ascorbic acid, both of which are biocompatible, enables the migration of protons. This allows the channel conductance of the transistors to be modulated with the gate input pulse voltage, and fundamental synaptic functions including excitatory postsynaptic current, paired-pulse facilitation, long-term potentiation, and long-term depression can be successfully emulated. Furthermore, the maltose-ascorbic acid electrolyte (MAE)-gated synaptic transistors exhibit high mechanical endurance, with near-linear conductivity modulation and repeatability after 1000 bending cycles under a curvature radius of 5 mm. Benefitting from its excellent biodegradability and biocompatibility, the proposed MAE has potential applications in environmentally friendly, economical, and high-performance neuromorphic electronics, which can be further applied to dermal electronics and implantable electronics in the future.

Entities:  

Keywords:  artificial synapse; ascorbic acid; indium tin oxide; maltose; synaptic transistor

Year:  2021        PMID: 34279076     DOI: 10.1021/acsami.1c07073

Source DB:  PubMed          Journal:  ACS Appl Mater Interfaces        ISSN: 1944-8244            Impact factor:   9.229


  1 in total

1.  Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing.

Authors:  Dmitry Kireev; Samuel Liu; Harrison Jin; T Patrick Xiao; Christopher H Bennett; Deji Akinwande; Jean Anne C Incorvia
Journal:  Nat Commun       Date:  2022-07-28       Impact factor: 17.694

  1 in total

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