Experimental Investigation on the Wear Performance of Nano-Additives on Degraded Gear Lubricant

润滑油 材料科学 水溶液 傅里叶变换红外光谱 纳米- 降级(电信) 氧化物 石墨烯 盐酸 化学工程 复合材料 冶金 化学 纳米技术 有机化学 计算机科学 电信 工程类
作者
Harish Hirani,Dharmender Jangra,Kishan Nath Sidh
出处
期刊:Lubricants [Multidisciplinary Digital Publishing Institute]
卷期号:11 (2): 51-51 被引量:9
标识
DOI:10.3390/lubricants11020051
摘要

This study investigates the degradation of a commercially available gear lubricant and the potential of nano-additives to mitigate such degradation. Initially, we performed an experimental study on the chemical degradation of commercially available API GL-4 EP90 gear lubricant by mixing the different concentrations of aqueous hydrochloric acid (aqueous HCl) varying from 0.0005% v/v up to 0.0025% v/v, while maintaining overall water content in the oil below the prescribed limits. The degradation was monitored using the pH value, total acid number (TAN) value, and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) analysis. The experiments were performed on a developed gear test rig using conventional gear oil as well as chemically aged gear oil, and the corresponding results of pH value and wear debris were recorded. Based on the results, an empirical regression model between the concentration of aqueous HCl and lubricant aging time has been established. Under chemically aged lubricant, severe wear of gear was observed, which motivated us to explore suitable nano-additive to minimize the gear wear. Initially, three nano-additives—graphite, graphene, and “graphene oxide functionalized with silicon oxide (GO@SiO2)”—were chosen. A series of tests were conducted using the design of experiments method (L8 and L16 orthogonal array) to investigate the effect of nano-additives and to find the optimum additive for wear performance. Finally, experiments were conducted on gear setup using the degraded lubricant optimized with nano-additive. Overall results indicate a very significant contribution of nano-additives in decreasing gear wear.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
ysh完成签到,获得积分10
刚刚
Luna完成签到,获得积分10
2秒前
4秒前
小二郎应助Caddie采纳,获得10
4秒前
Rondab应助飞云采纳,获得10
4秒前
4秒前
JIMMMY完成签到,获得积分10
5秒前
5秒前
7秒前
zhuling完成签到,获得积分10
7秒前
Sky完成签到,获得积分10
9秒前
Master_Ye发布了新的文献求助10
9秒前
漂泊发布了新的文献求助10
10秒前
Scinature发布了新的文献求助10
11秒前
mashichuang发布了新的文献求助10
11秒前
13秒前
ding应助吴丹采纳,获得20
15秒前
英姑应助欣喜沛芹采纳,获得10
15秒前
萱1988完成签到,获得积分10
15秒前
ikun完成签到,获得积分10
16秒前
pollen06完成签到,获得积分10
16秒前
天天快乐应助mashichuang采纳,获得10
17秒前
Atan完成签到,获得积分10
18秒前
Jasper应助平常的凝蕊采纳,获得30
18秒前
CHEE完成签到 ,获得积分10
18秒前
18秒前
SciGPT应助汪汪别吃了采纳,获得10
18秒前
wy完成签到,获得积分10
19秒前
Caddie发布了新的文献求助10
19秒前
文艺小馒头完成签到,获得积分10
20秒前
Wang发布了新的文献求助10
22秒前
Rondab应助飞云采纳,获得10
28秒前
慕青应助么大人采纳,获得10
28秒前
29秒前
31秒前
燕子发布了新的文献求助30
31秒前
32秒前
yi完成签到,获得积分10
33秒前
34秒前
害羞的囧完成签到 ,获得积分10
34秒前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
Problems of point-blast theory 400
Indomethacinのヒトにおける経皮吸収 400
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 390
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3997679
求助须知:如何正确求助?哪些是违规求助? 3537190
关于积分的说明 11270985
捐赠科研通 3276344
什么是DOI,文献DOI怎么找? 1806900
邀请新用户注册赠送积分活动 883582
科研通“疑难数据库(出版商)”最低求助积分说明 809975