Applicability of nanoscale ceramic particles as tribological lubricant additives

Á. Tóth, Á. Szabó
{"title":"Applicability of nanoscale ceramic particles as tribological lubricant additives","authors":"Á. Tóth, Á. Szabó","doi":"10.1109/CogMob55547.2022.10117843","DOIUrl":null,"url":null,"abstract":"Lubricants play a critical role in the energy losses of an engine. Several engineering solutions are existing to reduce the frictional and wear losses caused by the lubricant such as ultra-low-viscosity lubricants. With the spread of low-viscosity engine oils like 0W-20 and below, the importance of tribological lubricant additives is increasing. To ensure the necessary protection of the rubbing surfaces against friction and wear, new lubricant additive materials should be researched and investigated. Next to the tribological performance of the additives, their impact on the price is a strong influencing factor. No financial information of the investigated additive materials is available in the current scientific articles and so no rentable decision can be defined which additive worth to invest as an engine oil additive in the future mass production engine oils. This article presents the tribological potential of selected nanoscale ceramic particles (zirconia, cupric oxide and yttria) as lubricant additives and compares them according to their financial impact. According to the results it can be stated that not always the additive with the best tribological properties will be the one be used in mass production manufactured lubricants.","PeriodicalId":430975,"journal":{"name":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 1st International Conference on Cognitive Mobility (CogMob)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CogMob55547.2022.10117843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Lubricants play a critical role in the energy losses of an engine. Several engineering solutions are existing to reduce the frictional and wear losses caused by the lubricant such as ultra-low-viscosity lubricants. With the spread of low-viscosity engine oils like 0W-20 and below, the importance of tribological lubricant additives is increasing. To ensure the necessary protection of the rubbing surfaces against friction and wear, new lubricant additive materials should be researched and investigated. Next to the tribological performance of the additives, their impact on the price is a strong influencing factor. No financial information of the investigated additive materials is available in the current scientific articles and so no rentable decision can be defined which additive worth to invest as an engine oil additive in the future mass production engine oils. This article presents the tribological potential of selected nanoscale ceramic particles (zirconia, cupric oxide and yttria) as lubricant additives and compares them according to their financial impact. According to the results it can be stated that not always the additive with the best tribological properties will be the one be used in mass production manufactured lubricants.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
纳米陶瓷颗粒作为摩擦学润滑剂添加剂的适用性
润滑油在发动机的能量损失中起着至关重要的作用。目前已有几种工程解决方案可以减少润滑剂(如超低粘度润滑剂)造成的摩擦和磨损损失。随着低粘度发动机油(如0W-20及以下)的普及,摩擦学润滑油添加剂的重要性日益增加。为了保证摩擦表面免受摩擦和磨损的必要保护,必须研究和研究新的润滑添加剂材料。除了添加剂的摩擦学性能外,它们对价格的影响也是一个强有力的影响因素。在目前的科学文章中,没有关于所研究的添加剂材料的财务信息,因此无法确定哪种添加剂值得在未来量产的发动机油中作为添加剂进行投资。本文介绍了选定的纳米级陶瓷颗粒(氧化锆、氧化铜和氧化钇)作为润滑剂添加剂的摩擦学潜力,并根据它们的经济影响对它们进行了比较。结果表明,并非所有具有最佳摩擦学性能的添加剂都能用于大批量生产的润滑油。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Transformation domain requirements specification into computation tree logic language Closer-to-reality artificial ageing of engine oils with implemented nitration Downloading modern vehicles data for Forensics examination - A case study Two state dual loop EGR engine model Temperature Prediction of Automotive Battery Systems under Realistic Driving Conditions using Artificial Neural Networks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1