A kind of electret-based synaptic transistor and its preparation method

An electret and transistor technology, which is applied in the field of electret-based synaptic transistors and their preparation, can solve problems such as the lack of synaptic transistors, and achieve the effects of high switching ratio and improved accuracy
CN111180582BActive Publication Date: 2021-12-21FUZHOU UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
FUZHOU UNIV
Publication Date
2021-12-21

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Abstract

The invention relates to an electret-based synaptic transistor and a preparation method thereof, wherein the transistor is composed of a base with an insulating layer, an electret dielectric layer, an organic semiconductor layer and a top electrode from bottom to top; The above-mentioned electret dielectric layer forms an interface capture layer between the insulating layer and the semiconductor, which is used to capture electrons and holes, form an additional electric field, and play an additional gate control role on the semiconductor layer. The transistor has a high switching ratio, a large range of conductance control, and a good linear relationship between the increase in conductance and the number of regulated pulses. It is suitable for neuromorphic computing and can effectively improve the accuracy of pattern recognition. Touch provides an application prospect.
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Description

technical field

[0001] The invention relates to the field of electronic materials and devices, in particular to an electret-based synaptic transistor and a preparation method thereof. Background technique

[0002] Traditional computing is limited by the von Neumann bottleneck due to the independence of storage and processing. Neuromorphic computing can perform multiple tasks at the same time by simulating the human brain nervous system, such as learning, storing and transmitting information, and it has the characteristics of high efficiency and low efficiency. Neuromorphic computing inspired by the nervous system of the human brain will overcome the problem of independent information processing and storage. Artificial synapse devices, as the basic unit of neuromorphic computing systems, can perform signal processing with low power consumption. A variety of synaptic devices exist today, such as resistive random access memory (RRAM), phase change memory (PCM), memristor, and...

Claims

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