Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for predicting wettability between defect-introduced graphene and metal

A prediction method, graphene technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effect of reducing blindness, saving time and cost

Active Publication Date: 2017-11-10
NANCHANG HANGKONG UNIVERSITY
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is no specific method for predicting or evaluating the change of graphene wettability due to introduced defects. This application is to establish a fast and effective method for evaluating and predicting the wettability of graphene after introducing defects.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for predicting wettability between defect-introduced graphene and metal
  • Method for predicting wettability between defect-introduced graphene and metal
  • Method for predicting wettability between defect-introduced graphene and metal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] First, determine the defect types that need to be established in the graphene model according to the defect types that can be introduced in the experiment. 13 Then, the structure optimization of the above five structures was carried out to obtain the most stable structure; secondly, the above four graphene models were combined with the Al 13 Cluster combination and structural optimization were performed to obtain 4 sets of data, and the bond energy and structural parameters between the optimized graphene and metal clusters were calculated; finally, the change law of bond energy was determined, and the influence of bond energy change on wettability was determined as The level of wettability between graphene and metals with different defects is introduced for effective prediction and analysis.

[0033] Determine four structural models of defect-free graphene, vacancy-defect graphene, doped Ni-atom-defect graphene, and adsorbed Ni-atom-defect graphene, such as figure 2 ,...

Embodiment 2

[0038]First, determine the type of defect that needs to be established in the graphene model according to the type of defect that can be introduced in the experiment. 13 Then, the structure optimization of the above five structures was carried out to obtain the most stable structure; secondly, the above four graphene models were combined with the Cu 13 Cluster combination and structural optimization were performed to obtain 4 sets of data, and the bond energy and structural parameters between the optimized graphene and metal clusters were calculated; finally, the change law of bond energy was determined, and the influence of bond energy change on wettability was determined as The level of wettability between graphene and metals with different defects is introduced for effective prediction and analysis.

[0039] Determine four structural models of defect-free graphene, vacancy-defect graphene, doped Ni-atom-defect graphene, and adsorbed Ni-atom-defect graphene, such as figure...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for predicting wettability between defect-introduced graphene and metal. The method comprises the following step: based on a density functional theory of first principles, calculating the change of adsorption energy, bond energy and structures between graphene that is introduced with different types of defects and a metal cluster to predict the wettability between graphene and the metal cluster, wherein the defects introduced to graphene mainly include point defects, doped Ni defects and adsorption Ni defects. By separately calculating the change of the adsorption energy, the bond energy and the structure of graphene after being adsorbed with metal Cu13 clusters or Al13 clusters, the result shows that the introduction of graphene defects can improve the wettability between graphene and the metal, and particularly, the wettability between graphene doped with Ni atoms and the metal can be significantly improved. According to the method disclosed by the invention, the wettability between objects introduced with different defects and the metal can also be effectively predicted and analyzed according to the difference of the introduced defects or the difference of the objects introduced with the defects.

Description

technical field [0001] The invention relates to a method for predicting wettability between graphene with defects introduced and metal, and specifically belongs to the technical field of metal matrix composite materials. Background technique [0002] With the development of the automotive and aerospace fields, especially in the space field, the specific strength, specific modulus, corrosion resistance, electrical and thermal conductivity and other properties of metal matrix composites are required in harsh environments such as ionizing radiation. Traditional ceramics Fiber and granular reinforcements have been unable to meet the material requirements. In recent years, graphene has been considered as the most ideal metal matrix composite reinforcement because of its excellent mechanical and physical properties. [0003] Because the C atom of graphene itself is difficult to form a stable chemical bond with the metal, it is difficult for the graphene added in the metal-based g...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 李多生李锦锦周贤良洪跃邹伟
Owner NANCHANG HANGKONG UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com