Terylene/boron nitride/polypyrrole composite conductive fiber and fiber-based nerve synapse transistor device

A composite conductive and synaptic technology, applied in the field of transistors, can solve the problems of poor synaptic plasticity of fiber-based transistors, inability to realize self-monitoring and signal learning at the same time, and achieve excellent biocompatibility, wearable and implantable , the effect of low energy consumption

Pending Publication Date: 2022-05-13
WUHAN TEXTILE UNIV
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  • Application Information

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Problems solved by technology

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the object of the present invention is to provide a polyester / boron nitride / polypyrrole composite conductive fiber and a fiber-based neurosynaptic transistor device, which solves the problem of poor synaptic plasticity of the fiber-based transistor and the inability to simultaneously realize self- Problems with monitoring and signal learning functions

Method used

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  • Terylene/boron nitride/polypyrrole composite conductive fiber and fiber-based nerve synapse transistor device
  • Terylene/boron nitride/polypyrrole composite conductive fiber and fiber-based nerve synapse transistor device
  • Terylene/boron nitride/polypyrrole composite conductive fiber and fiber-based nerve synapse transistor device

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Embodiment 1

[0043] A polyester / boron nitride / polypyrrole composite conductive fiber is prepared through the following steps:

[0044] 1. Firstly, the original base material polyester (PET) was ultrasonically cleaned with acetone and alcohol for 10 minutes each, and the two-dimensional material boron nitride (BN) solution was sonicated in a cell pulverizer for 2 hours to make it more uniformly dispersed.

[0045] 2. Wind the PET on the coil and soak it in the BN solution. After soaking for 2 hours, take it out and dry it in a fume hood to obtain a PET / BN fiber coil.

[0046] 3. Prepare anthraquinone-2-sulfonate sodium solution (AQS): Weigh 1.5g of solid surfactant anthraquinone-2-sulfonate sodium salt, heat and dissolve in 150mL deionized water at 50°C, and cool at room temperature. Refrigerate for 5-10 minutes and set aside.

[0047] 4. Configure acidic ferric nitrate nonahydrate solution (Fe(NO 3 ) 3 9H 2 O): Weigh the dopant dihydrate 5-sulfosalicylic acid (C 7 h 6 o 6 S·2H 2 O)...

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Abstract

The invention provides a polyester / boron nitride / polypyrrole composite conductive fiber and a fiber-based nerve synapse transistor device. The neural synapse transistor comprises a source electrode, a drain electrode and a grid electrode which are arranged in a mutually crossed manner, and gel electrolyte arranged between cross points, the source electrode, the drain electrode and the grid electrode are made of PET / BN / PPy composite conductive fibers, the composite conductive fibers are obtained by firstly dipping BN on the surface of polyester and then carrying out in-situ polymerization growth on pyrrole on the surface of the composite conductive fibers, and the conductive polymer composite fiber flexible electrode material with a three-dimensional net-shaped and linear structure is obtained. The fiber-based nerve synapse transistor device has the advantages of being soft, breathable, good in biocompatibility and diversified in integration mode. The method mainly has a wide application prospect in the fields of brain-computer interfaces, bionic nerves, wearable and implantable technologies and the like.

Description

technical field [0001] The invention relates to the technical field of transistors, in particular to a polyester / boron nitride / polypyrrole composite conductive fiber and a fiber-based neural synapse transistor device. Background technique [0002] In order to get rid of the bottleneck of the von Neumann architecture, artificial neurosynaptic devices inspired by biological nerves have attracted widespread attention. Researchers first realized a non-volatile memristor in 1994. After decades Over the years of development, memristors have been rapidly developed in artificial neural networks. But its disadvantage is that it cannot realize the artificial neural network function of signal monitoring and self-learning at the same time. The regulation of synaptic plasticity is the key to simulating the biological nervous system. Therefore, in order to simultaneously realize the functions of signal monitoring and self-learning, it is necessary to simulate the synaptic plasticity of a...

Claims

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Application Information

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IPC IPC(8): D06M11/80D06M15/37H01L51/10D06M101/32
CPCD06M11/80D06M15/37D06M2101/32H10K10/82Y02P70/50
Inventor 王栋舒庆卿星吴建美李沐芳
Owner WUHAN TEXTILE UNIV
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