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High ionic conductivity Li0.33La0.557TiO3nanofiber/polymer composite solid electrolyte for flexible transparent InZnO synaptic transistors.

Wenhui FuJun LiLinkang LiDongliang JiangWenqing ZhuJianhua Zhang
Published in: Nanotechnology (2021)
With the rapid development of wearable artificial intelligence devices, there is an increasing demand for flexible oxide neuromorphic transistors with the solid electrolytes. To achieve high-performance flexible synaptic transistors, the solid electrolytes should exhibit good mechanical bending characteristics and high ion conductivity. However, the polymer-based electrolytes with good mechanical bending characteristics show poor ion conductivity (10-6-10-7S cm-1), which limits the performance of flexible synaptic transistors. Thus, it is urgent to improve the ion conductivity of the polymer-based electrolytes. In the work, a new strategy of electrospun Li0.33La0.557TiO3nanofibers-enhanced ion transport pathway is proposed to simultaneously improve the mechanical bending and ion conductivity of polyethylene oxide/polyvinylpyrrolidone-based solid electrolytes. The flexible InZnO synaptic transistors with Li0.33La0.557TiO3nanofibers-based solid electrolytes successfully simulated excitatory post-synaptic current, paired-pulse-facilitation, dynamic time filter, nonlinear summation, two-terminal input dynamic integration and logic function. This work is a useful attempt to develop high-performance synaptic transistors.
Keyphrases
  • solid state
  • ion batteries
  • artificial intelligence
  • ionic liquid
  • prefrontal cortex
  • machine learning
  • big data
  • quantum dots
  • deep learning
  • blood pressure
  • visible light