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Photoelectric nerve synaptic memristor

A neural synapse and memristor technology, applied in the field of brain-inspired computing devices, can solve the problems of light wave introduction/export methods that need to be further studied, and achieve the effect of accelerated application

Pending Publication Date: 2021-11-09
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In terms of optoelectronic synergy, although optoelectronic synaptic devices have obvious advantages in terms of power consumption and other performance, the way of introducing / exporting light waves still needs further research

Method used

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  • Photoelectric nerve synaptic memristor
  • Photoelectric nerve synaptic memristor
  • Photoelectric nerve synaptic memristor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] In embodiment 1, a kind of optoelectronic synaptic memristor, such as figure 2 As shown, the structure is from top to bottom: a silicon nitride optical waveguide layer (Si 3 N 4 ) 101, oxide isolation layer (SiO 2 ) 102, a transparent top electrode layer (ITO) 201, a two-dimensional material layer composed of molybdenum sulfide and molybdenum oxide (MoS 2 / Mo 2-x o x ) 301, graphene quantum dots modified silicon oxide porous structure layer (GQDs@PSiO x ) 401, and the bottom electrode layer (Si) 501.

[0040] Among them, the width of the optical waveguide layer (non-wedge-shaped output end part) is 5 μm, and the height is 10 μm; the inclination angle of the side of the wedge-shaped output end is 45°, and the contact surface with the top electrode is 10*10 μm 2 ; Top electrode thickness 200nm; MoS 2 / Mo 2-x o x The thickness is 10nm; the thickness of the porous structure is 100nm; the bottom electrode is 300μm.

[0041] The structure is prepared layer by layer...

Embodiment 2

[0054] In embodiment 2, such as figure 2 As shown, the structure from top to bottom is: a silicon optical waveguide layer (Si) 101 including a wedge-shaped output end 103, an oxide isolation layer (SiO 2 ) 102, transparent top electrode layer 201 (FTO), black phosphorus two-dimensional material layer (BP) 301, β-NaYF 4 :Yb 3 +,Tm 3+ / NaYF 4 Quantum dot modified silicon porous structure (β-NaYF 4 :Yb 3 +,Tm 3+ / NaYF 4 @PSi) layer 401, bottom electrode layer (Si) 501.

[0055] Among them, the width of the optical waveguide layer is 2.5 μm, and the height is 5 μm; the side of the wedge-shaped output end is inclined at an angle of 45°, and the contact surface with the top electrode is 5*5 μm 2 ; Top electrode thickness 100nm; BP thickness 3nm; porous structure thickness 150nm; bottom electrode 500μm.

[0056] The structure is prepared layer by layer on the substrate from bottom to top by electrochemical corrosion, ultrasonic dispersion, chemical vapor deposition, transfe...

Embodiment 3

[0062] Such as figure 1 As shown, this embodiment provides a structural schematic diagram of an optoelectronic synapse array. The array structure is as follows: it includes N*M (N≥1, M≥1) photoelectric synaptic memristors, and each photoelectric synaptic memristor includes a wedge-shaped output terminal (Si 3 N 4 ) 103 silicon nitride optical waveguide layer (Si 3 N 4 ) 101, oxide isolation layer (SiO 2 ) 102, grating coupler (Si 3 N 4 ) 104, a transparent top electrode layer (ITO) 201, an external electrode (Au) 202 connecting the top electrode, and a device structure molybdenum sulfide / molybdenum oxide two-dimensional material layer (MoS 2 / Mo 2-x o x) 301, graphene quantum dots modified silicon oxide porous structure layer (GQDs@PSiO x ) 401, and the bottom electrode layer (Si) 501.

[0063] In this embodiment, an optoelectronic synapse array is obtained by integrating an optical waveguide and an optoelectronic memristor structure. Each memristor shares a common ...

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Abstract

The invention discloses a photoelectric nerve synaptic memristor which structurally comprises a bottom electrode layer, a quantum dot modified porous structure layer, a two-dimensional material layer, a transparent top electrode layer and an optical waveguide layer from bottom to top in sequence. The memristor is characterized in that the optical waveguide layer is a ridge-shaped optical waveguide, has a light conduction effect and comprises a wedge-shaped output end, and light can be vertically emitted into the two-dimensional material layer and the quantum dot modified porous structure layer through the wedge-shaped output end of the optical waveguide layer. By integrating the optical waveguide and a photoelectric nerve synapse function structure, the photoelectric control characteristic with high alignment and confinement is obtained, and the photoelectric nerve synaptic device has the advantage of controlling the photoelectric synergistic effect in the photoelectric nerve synapse device. The memristor is simple in operation, high in controllability and excellent in performance, is widely applied to the fields of high-density storage calculation, artificial synapse simulation, artificial intelligence and the like, and is favorable for exploring a novel cranial nerve-like working mechanism.

Description

technical field [0001] The invention relates to a photoelectric neural synaptic memristor, which has the functions of precise control of photoelectric signals, low energy consumption, simulated neural synaptic functions, and accelerated neuromorphic computing, belonging to the technical field of brain-like computing devices. Background technique [0002] With the development of new theories and technologies such as big data, cloud computing, quantum information, and neuromorphic computing, artificial intelligence has become the core driving force leading a new round of technological revolution and industrial transformation, and is considered to be the first to appear in the next ten years. One of the three technological revolutions. Due to the explosive growth of information volume, the "Von Neumann" system that separates traditional computing and storage can no longer meet the development needs of new technologies such as artificial intelligence, the Internet of Things, and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H01L45/00H01L27/24G06N3/067
CPCG06N3/0675H10B63/80H10N70/24H10N70/257G06N3/049G06N3/088H01L29/0673H01L31/035227H01L31/035218
Inventor 黄安平姬宇航高勤王玫肖志松
Owner BEIHANG UNIV
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