Tribological and Corrosion Properties of Graphene Nanoplatelets and Titanium Dioxide Nanoparticles Reinforced Aluminium Zinc Magnesium Alloy-Based Nanohybrid Metal Matrix Composites

IF 0.9 4区 材料科学 Q4 METALLURGY & METALLURGICAL ENGINEERING
Rahul Chaurasia, Saroj Kumar Sarangi, Ashish Kumar Srivastava, Ambuj Saxena
{"title":"Tribological and Corrosion Properties of Graphene Nanoplatelets and Titanium Dioxide Nanoparticles Reinforced Aluminium Zinc Magnesium Alloy-Based Nanohybrid Metal Matrix Composites","authors":"Rahul Chaurasia,&nbsp;Saroj Kumar Sarangi,&nbsp;Ashish Kumar Srivastava,&nbsp;Ambuj Saxena","doi":"10.1134/S1067821225600206","DOIUrl":null,"url":null,"abstract":"<p>Present study focuses on the fabrication and evaluation of graphene nanoplatelets and titanium dioxide nano powder-reinforced aluminium-zinc-magnesium alloy-based nanohybrid metal matrix composites using the cost-effective and scalable stir casting technique with the objective to enhance tribological performance and corrosion resistance. The tribological properties were evaluated under 10 and 20 N loads at 300 and 600 rpm conditions. Wear and coefficient of friction shows significant improvement. Minimum wear is reported in 2% graphene nanoplatelets and 3% titanium dioxide samples at 10 N and 300 rpm conditions, whereas coefficient of friction is minimum in the same composition at 20 N 600 rpm conditions having values of 0.0016 mm<sup>3</sup> min<sup>–1</sup> and 0.28 respectively. Scanning electron microscopy images revealed wear mechanisms at 10 and 20 N loads, showcasing reduced wear scars and smoother surfaces in higher reinforced composites. Minimum surface roughness observed is 1.71 µm. Corrosion resistance was also notably enhanced, as confirmed by scanning electron microscopy images analysis of corroded surfaces. The lowest corrosion rate observed is 0.83 mmpy at 2% graphene nanoplatelets and 3% titanium dioxide reinforced sample. Artificial neural networks and multiple linear regression were employed, showing excellent correlation with experimental data for accurate property predictions. The results demonstrate that the incorporation of present reinforcements substantially improves wear resistance, lowers friction coefficient, and mitigates corrosion in saline environments.</p>","PeriodicalId":765,"journal":{"name":"Russian Journal of Non-Ferrous Metals","volume":"66 1","pages":"1 - 16"},"PeriodicalIF":0.9000,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Non-Ferrous Metals","FirstCategoryId":"88","ListUrlMain":"https://link.springer.com/article/10.1134/S1067821225600206","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METALLURGY & METALLURGICAL ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

Present study focuses on the fabrication and evaluation of graphene nanoplatelets and titanium dioxide nano powder-reinforced aluminium-zinc-magnesium alloy-based nanohybrid metal matrix composites using the cost-effective and scalable stir casting technique with the objective to enhance tribological performance and corrosion resistance. The tribological properties were evaluated under 10 and 20 N loads at 300 and 600 rpm conditions. Wear and coefficient of friction shows significant improvement. Minimum wear is reported in 2% graphene nanoplatelets and 3% titanium dioxide samples at 10 N and 300 rpm conditions, whereas coefficient of friction is minimum in the same composition at 20 N 600 rpm conditions having values of 0.0016 mm3 min–1 and 0.28 respectively. Scanning electron microscopy images revealed wear mechanisms at 10 and 20 N loads, showcasing reduced wear scars and smoother surfaces in higher reinforced composites. Minimum surface roughness observed is 1.71 µm. Corrosion resistance was also notably enhanced, as confirmed by scanning electron microscopy images analysis of corroded surfaces. The lowest corrosion rate observed is 0.83 mmpy at 2% graphene nanoplatelets and 3% titanium dioxide reinforced sample. Artificial neural networks and multiple linear regression were employed, showing excellent correlation with experimental data for accurate property predictions. The results demonstrate that the incorporation of present reinforcements substantially improves wear resistance, lowers friction coefficient, and mitigates corrosion in saline environments.

Abstract Image

石墨烯纳米片和二氧化钛纳米颗粒增强铝锌镁合金基纳米杂化金属基复合材料的摩擦学和腐蚀性能
本文主要研究了石墨烯纳米片和二氧化钛纳米粉末增强铝锌镁合金基纳米杂化金属基复合材料的制备和性能评价,旨在提高其摩擦学性能和耐腐蚀性。在10和20 N载荷下,在300和600 rpm的条件下,对其摩擦学性能进行了评估。磨损和摩擦系数有明显改善。据报道,在10 N和300 rpm条件下,2%石墨烯纳米片和3%二氧化钛样品的磨损最小,而在20 N 600 rpm条件下,摩擦系数最小,分别为0.0016 mm3 min-1和0.28。扫描电子显微镜图像显示了10和20 N载荷下的磨损机制,表明高强度复合材料的磨损疤痕减少,表面更光滑。观察到的最小表面粗糙度为1.71µm。腐蚀表面的扫描电镜图像分析证实,耐腐蚀性也显著增强。在2%的石墨烯纳米片和3%的二氧化钛增强样品中,观察到的最低腐蚀速率为0.83 mmpy。采用人工神经网络和多元线性回归,与实验数据具有良好的相关性,可以准确预测性能。结果表明,加入现有增强剂可显著提高耐磨性,降低摩擦系数,并减轻盐环境中的腐蚀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Russian Journal of Non-Ferrous Metals
Russian Journal of Non-Ferrous Metals METALLURGY & METALLURGICAL ENGINEERING-
CiteScore
1.90
自引率
12.50%
发文量
59
审稿时长
3 months
期刊介绍: Russian Journal of Non-Ferrous Metals is a journal the main goal of which is to achieve new knowledge in the following topics: extraction metallurgy, hydro- and pirometallurgy, casting, plastic deformation, metallography and heat treatment, powder metallurgy and composites, self-propagating high-temperature synthesis, surface engineering and advanced protected coatings, environments, and energy capacity in non-ferrous metallurgy.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信