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Memristive network based on movable conductive nanoparticles and self-organizing evolution operation application

A nanoparticle, dynamic conduction technology, applied in electrical components and other directions, can solve the problems of huge time and space overhead, and achieve the effect of simple and reliable preparation process, good repeatability, and reduced device size

Pending Publication Date: 2021-11-19
PEKING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, limited by the size of traditional CMOS devices close to the physical limit and the separation of storage and calculation in traditional computing architectures, it is difficult for current computers to meet future needs in terms of speed, power consumption, and area when processing data, especially when solving some classic complex computing problems. often requires a huge amount of time and space

Method used

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  • Memristive network based on movable conductive nanoparticles and self-organizing evolution operation application
  • Memristive network based on movable conductive nanoparticles and self-organizing evolution operation application
  • Memristive network based on movable conductive nanoparticles and self-organizing evolution operation application

Examples

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Effect test

Embodiment 1

[0038] Here, specific materials and processes are selected to illustrate the preparation process of the memristive network based on movable conductive nanoparticles, such as Figure 5 shown. Among them, the substrate material is a silicon substrate that has been thermally oxidized, the conductive electrode is a combination of active metal and inert metal Ti / Au, the dielectric layer is made of PEO material and obtained by spin coating, and the movable conductive nanoparticles are made of active metal silver. particles. Here is a specific process to illustrate the main preparation process of the silver nanoparticle memristive network:

[0039] In the first step, metallic Ti / Au electrodes are grown. The thermally oxidized silicon substrate is used as the substrate to spin-coat PMMA electron beam glue. After defining the metal electrode area through electron beam exposure and development and fixing processes, Ti and Au metal materials are grown sequentially by electron beam evap...

Embodiment 2

[0044] Here is an example to show the result of using the memristive network based on movable conductive nanoparticles of the present invention to solve the shortest path problem. When using the memristive network based on movable conductive nanoparticles to solve the shortest path problem, some conductive islands can be designed and arranged between the conductive electrodes based on the basic structure according to the specific problem, so as to realize the description and solution of different graph structures . Among them, the conductive island can be compared with figure 1 The conductive electrodes shown in the first step are prepared together by patterning techniques (such as: photolithography, electron beam exposure, etc.). Here, the silver nanoparticle memristive network prepared by the method described in Example 1 is taken as an example for illustration, and the corresponding scanning electron microscopy results are as follows Figure 7 shown. Figure 7 (a) is the...

Embodiment 3

[0046] Here, a 3×3 scale maze is taken as an example to illustrate how to use a five-terminal movable conductive nanoparticle memristive network to represent a grid decision. The structure of the 3×3 maze is as follows Figure 8 As shown in (a), for the convenience of description, each grid is numbered with numbers 1-9 here. The connectivity of the maze is indicated by color, with white representing connectivity and black representing disconnection. The connectivity of the maze determines the optional direction of each grid decision. For example, for grid No. 5 in the maze, it is connected to grid No. 2 and grid No. 8, and there is a "wall" to block grid No. 4 and grid No. 6, so it cannot be connected. You can move up (No. 2 grid) or down (No. 8 grid), but not left (No. 4 grid) and right (No. 6 grid). Since there are only four possibilities for the decision-making of each grid in the maze: up, down, left, and right, it can be represented by a five-terminal movable conductiv...

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Abstract

The invention discloses a memristor network based on movable conductive nanoparticles and a self-organizing evolution operation application. The memristive network comprises a substrate, a plurality of conductive electrodes, a dielectric layer and movable conductive nanoparticles; the conductive electrodes are located on the substrate and serve as signal input and output ends of the memristive network; the dielectric layer is filled between the conductive electrodes; the movable conductive nanoparticles are dispersed on the surface and / or inside the dielectric layer, and the movable conductive nanoparticles can migrate in the dielectric layer under the action of an electric field, so that the emergence behavior of the self-evolution network can be highly mapped, and advantages in solving some classic complex operation problems which are difficult to solve by a traditional computer are achieved. The invention further provides application of the memristor network based on the movable conductive nanoparticles in solving classical optimization problems, including solving of the shortest path problem and the maze problem, and the time complexity and the space complexity of operation can be greatly reduced.

Description

technical field [0001] The invention belongs to the field of new computing technologies, and in particular relates to a memristive network structure based on movable conductive nanoparticles and an application of self-organizing evolution computing. Background technique [0002] At present, in the context of the big data era, the wave of artificial intelligence, Internet of Things, and blockchain is sweeping the world. The explosive growth of data volume puts forward higher requirements on computer performance. However, limited by the size of traditional CMOS devices close to the physical limit and the separation of storage and calculation in traditional computing architectures, it is difficult for current computers to meet future needs in terms of speed, power consumption, and area when processing data, especially when solving some classic complex computing problems. It often takes a huge time and space overhead. In fact, the operation of various networks in the real worl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H01L45/00
CPCH10N70/20H10N70/801H10N70/881H10N70/021H10N70/011
Inventor 杨玉超徐丽莹朱嘉迪黄如
Owner PEKING UNIV
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