Literature DB >> 33466648

Memristive Switching Characteristics in Biomaterial Chitosan-Based Solid Polymer Electrolyte for Artificial Synapse.

Shin-Yi Min1, Won-Ju Cho1.   

Abstract

This study evaluated the memristive switching characteristics of a biomaterial solid polymer electrolyte (SPE) chitosan-based memristor and confirmed its artificial synaptic behavior with analog switching. Despite the potential advantages of organic memristors for high-end electronics, the unstable multilevel states and poor reliability of organic devices must be overcome. The fabricated Ti/SPE-chitosan/Pt-structured memristor has stable bipolar resistive switching (BRS) behavior due to a cation-based electrochemical reaction between a polymeric electrolyte and metal ions and exhibits excellent endurance in 5 × 102 DC cycles. In addition, we achieved multilevel per cell (MLC) BRS I-V characteristics by adjusting the set compliance current (Icc) for analog switching. The multilevel states demonstrated uniform resistance distributions and nonvolatile retention characteristics over 104 s. These stable MLC properties are explained by the laterally intensified conductive filaments in SPE-chitosan, based on the linear relationship between operating voltage margin (ΔVswitching) and Icc. In addition, the multilevel resistance dependence on Icc suggests the capability of continuous analog resistance switching. Chitosan-based SPE artificial synapses ensure the emulation of short- and long-term plasticity of biological synapses, including excitatory postsynaptic current, inhibitory postsynaptic current, paired-pulse facilitation, and paired-pulse depression. Furthermore, the gradual conductance modulations upon repeated stimulation by 104 electric pulses were evaluated in high stability.

Entities:  

Keywords:  chitosan; electronic synapses; multilevel state; organic memristor; solid polymer electrolyte

Year:  2021        PMID: 33466648     DOI: 10.3390/ijms22020773

Source DB:  PubMed          Journal:  Int J Mol Sci        ISSN: 1422-0067            Impact factor:   5.923


  2 in total

1.  An Artificial Synapse Based on CsPbI3 Thin Film.

Authors:  Jia-Ying Chen; Xin-Gui Tang; Qiu-Xiang Liu; Yan-Ping Jiang; Wen-Min Zhong; Fang Luo
Journal:  Micromachines (Basel)       Date:  2022-02-10       Impact factor: 2.891

2.  Emulating Artificial Synaptic Plasticity Characteristics from SiO2-Based Conductive Bridge Memories with Pt Nanoparticles.

Authors:  Panagiotis Bousoulas; Charalampos Papakonstantinopoulos; Stavros Kitsios; Konstantinos Moustakas; Georgios Ch Sirakoulis; Dimitris Tsoukalas
Journal:  Micromachines (Basel)       Date:  2021-03-15       Impact factor: 2.891

  2 in total

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