A theoretical model for the effective thermal conductivity of graphene coated metal foams

石墨烯 热导率 材料科学 金属泡沫 石墨烯泡沫 石蜡 复合材料 多孔性 复合数 多孔介质 热传导 导电体 涂层 纳米技术 氧化石墨烯纸
作者
K.C. Chan,Chi Yan Tso,Abid Hussain,Christopher Y.H. Chao
出处
期刊:Applied Thermal Engineering [Elsevier BV]
卷期号:161: 114112-114112 被引量:24
标识
DOI:10.1016/j.applthermaleng.2019.114112
摘要

Thermal management systems (TMS) are an integral part of electronic devices and ongoing developments using porous structures as TMS have revolutionized this field. Porous composites are extensively used for thermal management due to their light weight and high permeability. To maximize the advantages of porous structures, effective thermal conductivity calculations are critical in designing suitable TMS. Recently, we have developed a graphene coated nickel foam – paraffin composite exhibiting an improvement in thermal conductivity that is 23 times greater than pure paraffin. Current theoretical models, however, cannot predict the thermal conductivity of metal foam with the additional thermally conductive coating layer. Herein we report a theoretical model to determine the effective thermal conductivity of graphene coated metal foam saturated with a filling medium. The model is based on the 2D hexagonal structure of graphene coated metal foams. Samples with various combinations of graphene coated metal foams (nickel and copper foams with different porosities) and filling mediums (paraffin waxes and air) were prepared to validate the model. It is found that the effective thermal conductivities calculated by the model are in good agreement with the experimental results, in which the maximum deviation is less than 2%. The derived theoretical model will be helpful in designing passive TMS using porous structure (graphene coated metal foams) for heat dissipation. Parametric analysis on skeleton and graphene area ratios was also conducted. From the analysis, the node of the metal foam should be minimized. By coating the metal foam with graphene, the thermal conductivity can be increased by 4.4 times from 3.69 W/mK to 19.85 W/mK. This shows that the thin graphene coating is very effective in improving the performance of the graphene coated metal foam saturated with filler for thermal management applications.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
佳思思完成签到,获得积分10
3秒前
bji发布了新的文献求助10
3秒前
jin发布了新的文献求助10
4秒前
星辰大海应助xiao99采纳,获得10
6秒前
1wEi完成签到,获得积分10
6秒前
ppp完成签到,获得积分10
7秒前
NexusExplorer应助luen采纳,获得10
9秒前
9秒前
9秒前
10秒前
好家伙完成签到,获得积分10
11秒前
HikarizzZ完成签到,获得积分10
11秒前
12秒前
安江涛完成签到,获得积分10
13秒前
激情的冰绿完成签到 ,获得积分10
13秒前
13秒前
mm完成签到 ,获得积分10
14秒前
14秒前
15秒前
pluto应助柠儿采纳,获得10
15秒前
16秒前
FashionBoy应助虚心烧鹅采纳,获得10
16秒前
上官小怡发布了新的文献求助10
16秒前
17秒前
思源应助谎1028采纳,获得10
17秒前
万能图书馆应助慕若涵冰采纳,获得10
17秒前
土豪的琪完成签到,获得积分10
17秒前
zhou发布了新的文献求助10
17秒前
冷傲之玉完成签到,获得积分20
18秒前
19秒前
Akim应助高大的小鸭子采纳,获得10
19秒前
xiao99发布了新的文献求助10
20秒前
313完成签到 ,获得积分10
20秒前
KasenDen发布了新的文献求助10
21秒前
24秒前
24秒前
ying777发布了新的文献求助30
25秒前
25秒前
高风亮节发布了新的文献求助10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
信任代码:AI 时代的传播重构 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6357856
求助须知:如何正确求助?哪些是违规求助? 8172365
关于积分的说明 17207840
捐赠科研通 5413315
什么是DOI,文献DOI怎么找? 2865033
邀请新用户注册赠送积分活动 1842556
关于科研通互助平台的介绍 1690663