Influence of graphene nanoplates and titanium diboride particulate on wear and interfacial bonding properties of sintered aluminium alloy composites

材料科学 复合材料 石墨烯 压痕硬度 纳米复合材料 合金 复合数 二硼化钛 扫描电子显微镜 铝合金 场发射显微术 陶瓷 微观结构 纳米技术 物理 衍射 光学
作者
J. Lokesh Kumar,P. Gurusamy,N. Gayathri,V. Muthuraman
出处
期刊:Diamond and Related Materials [Elsevier BV]
卷期号:144: 111035-111035
标识
DOI:10.1016/j.diamond.2024.111035
摘要

Graphene has been considered an appropriate reinforcing filler for aluminium/titanium metal matrix composites due to its outstanding strength and stiffness and its exceptional thermal and electrical properties. The variable concentrations of graphene nanoplates (GNPs) was considered in this research, such as 2 %, 4 %, 6 % and 8 %, for determining wear properties and interface bonding aluminium alloy composites. The graphene-reinforced Al 7075/10 % TiB2 hybrid nanocomposite samples were produced using ball milling and pressure-less vacuum sintering process. The wear loss was investigated for all the variable graphene concentration samples with respect to wear load and sliding distance by pin-on-disk method and optimum concentatrion of GNPs was obtained by design of experimental (DOE) analysis. Further, Field Emission Scanning Electron Microscopy (FESEM), Elemental mapping, Energy Dispersive X-ray (EDX), and microhardness tests were utilized to analyze the graphene-reinforced Al 7075/10 % TiB2 hybrid nanocomposites, It was concluded that the wear resistance and microhardness of Al/10 % TiB2/4 % GNPs increased by 71.3 % and 17.6 %, respectively, compared with non-hybrid aluminium alloy materials. Moreover, a Transmission Electron Microscope (TEM) has been used to investigate the interfacial strength of aluminium alloy composites. The wear loss characteristics was also optimized using and central composite design (CCD) of response surface methodology (RSM).

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
cdercder应助Twilight采纳,获得10
刚刚
哈哈哈完成签到,获得积分10
刚刚
野猪完成签到,获得积分10
刚刚
活泼的蘑菇完成签到 ,获得积分10
刚刚
刚刚
静心完成签到,获得积分10
1秒前
李健的小迷弟应助SEVEN采纳,获得10
1秒前
快乐小狗完成签到,获得积分10
1秒前
1秒前
1秒前
iIl1oO0完成签到,获得积分10
2秒前
entgegen完成签到,获得积分10
3秒前
洪文完成签到,获得积分10
3秒前
lliy完成签到,获得积分10
4秒前
YYYYSO完成签到,获得积分10
4秒前
4秒前
丫丫完成签到,获得积分10
5秒前
5秒前
吃饭打肯德基完成签到 ,获得积分10
5秒前
5秒前
池鱼完成签到,获得积分10
6秒前
ExtroGod完成签到,获得积分10
6秒前
毗昙发布了新的文献求助10
7秒前
min20210429发布了新的文献求助10
7秒前
7秒前
7秒前
不以完成签到,获得积分10
8秒前
Yurrrrt完成签到,获得积分0
8秒前
00K完成签到,获得积分10
9秒前
娃哈哈完成签到,获得积分10
9秒前
慕青应助李现真滴帅采纳,获得10
10秒前
一个薯片完成签到,获得积分10
10秒前
10秒前
10秒前
oldeight完成签到,获得积分20
10秒前
10秒前
神勇问安完成签到,获得积分10
10秒前
朵朵完成签到 ,获得积分10
10秒前
WILL完成签到,获得积分10
11秒前
心灵美的幼蓉完成签到,获得积分10
11秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
政治传播过程中的外交与说服——以中苏友好协会为例的历史考察 566
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7579814
求助须知:如何正确求助?哪些是违规求助? 9159288
关于积分的说明 19594255
捐赠科研通 7162441
什么是DOI,文献DOI怎么找? 3265750
关于科研通互助平台的介绍 2430774
邀请新用户注册赠送积分活动 2256569