Multi-scale modelling for adhesive wear in tribo-pairs of nano-hydroxyapatite reinforced UHMWPE bio-composite and Co-Cr alloy

材料科学 复合材料 胶粘剂 复合数 轮廓仪 扫描电子显微镜 表面粗糙度 磨损系数 有限元法 摩擦学 结构工程 图层(电子) 工程类
作者
Nishant Verma,Himanshu Pathak,Sunny Zafar
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications [SAGE]
卷期号:: 146442072110516-146442072110516
标识
DOI:10.1177/14644207211051625
摘要

The ultra-high molecular weight polyethylene (UHMWPE) is a popular biomaterial. Pre-clinical evaluation of UHMWPE in terms of wear resistance is extremely important to avoid the effect of implant loosening after implantation. This work proposed an efficient and accurate computational modelling approach to predict elasto-plastic properties at meso-scale, and further integrated at macro-scale to predict adhesive wear in dry tribo-pairs condition. The representative volume element (RVE) based finite element technique was used to predict elastoplastic behaviour of nano-hydroxyapatite (nHA) reinforced UHMWPE composite. The predicted values were validated experimentally and applied as a material property of pin during a numerical investigation of adhesive wear by a macro-scale modelling approach. The CoCr alloy was taken as the counter disc material. The integration of Archard's wear model and user-subroutine was done for numerical prediction of wear. The numerically obtained wear rate and friction coefficient results were validated experimentally by a pin on the disc wear setup under dry conditions. The fabrication of the specimen for validation was done by microwave-assisted compression moulding (MACM). The microstructural investigation of worn surfaces was done by scanning electron microscopy (SEM) to understand the mechanism of adhesive wear. The surface mapping of worn surfaces was done using an optical profilometer to observe the surface roughness after adhesive wear. Biocompatibility of the composite material was confirmed by In-vitro direct contact cytotoxicity test
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
1秒前
星辰大海应助Yenom采纳,获得10
1秒前
jjy完成签到,获得积分10
2秒前
科研通AI5应助雾蓝采纳,获得10
2秒前
大地完成签到,获得积分10
2秒前
大门神完成签到,获得积分10
2秒前
2秒前
苦逼工科仔完成签到,获得积分10
3秒前
gaos发布了新的文献求助10
3秒前
3秒前
4秒前
4秒前
4秒前
从容飞凤完成签到,获得积分10
5秒前
药疯了发布了新的文献求助30
5秒前
今天做实验了吗完成签到 ,获得积分10
6秒前
晚意意意意意完成签到 ,获得积分10
6秒前
Jenny应助xiuxiu_27采纳,获得10
7秒前
7秒前
麻辣爆锅完成签到,获得积分10
7秒前
7秒前
qq小兵发布了新的文献求助10
7秒前
Owen应助littlewhite采纳,获得30
8秒前
3137874883完成签到,获得积分20
8秒前
1111完成签到,获得积分10
8秒前
本杰明发布了新的文献求助10
9秒前
润润轩轩发布了新的文献求助10
9秒前
9秒前
共享精神应助烧烤采纳,获得10
10秒前
酒酿是也完成签到 ,获得积分10
10秒前
H71000A完成签到 ,获得积分10
10秒前
文章多多完成签到 ,获得积分10
10秒前
10秒前
bwbw发布了新的文献求助10
11秒前
华仔应助Lvj采纳,获得10
11秒前
我是老大应助灵巧的坤采纳,获得10
11秒前
12秒前
wwwwyyyy完成签到,获得积分10
12秒前
hbb完成签到,获得积分10
12秒前
故意的傲玉应助韭菜采纳,获得10
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759