Mass spectrometry molecular fingerprinting of mineral and synthetic lubricant oils

化学 质谱法 润滑油 傅里叶变换离子回旋共振 分析化学(期刊) 质谱 电喷雾电离 色谱法 偏最小二乘回归 掺假者 红外光谱学 有机化学 数学 统计
作者
Caroline Pais de Carvalho,Adriano Reis José da Silva,Rosineide C. Lima,Marcos N. Eberlin
出处
期刊:Journal of Mass Spectrometry [Wiley]
卷期号:58 (4) 被引量:2
标识
DOI:10.1002/jms.4906
摘要

The molecular composition of lubricating oils has a strong impact on how automotive engines function, but the techniques used to monitor the quality parameters of these oils only inspect their gross physical-chemical properties such as viscosity, color, and bulk spectroscopy profiles; hence, bad-quality, adulterated, or counterfeit oils are hard to detect. Herein, we investigated the ability of direct infusion electrospray ionization mass spectrometry (ESI-MS) to provide simple, rapid but characteristic fingerprint profiles for such oils of the mineral and synthetic types. After a simple aqueous extraction, ESI-MS analyses, particularly in the positive ion mode, did indeed show characteristic molecular markers with unique profiles, which were confirmed and more clearly visualized by partial least squares-discriminant analysis (PLS-DA). Nuclear magnetic resonance and Fourier transform infrared-attenuated total reflection spectroscopy were also tested for the bulk samples but showed nearly identical spectra, thus failing to reveal their distinct molecular composition and to differentiate the oil samples. To simulate adulteration, mixtures of mineral and synthetic oils were also analyzed by ESI(+)-MS, and additions as low as 1% of mineral oil to synthetic oil could be detected. The technique therefore offers a simple and fast but powerful tool to monitor the molecular composition of lubricant oils, particularly vias their more polar constituents.

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
刚刚
刚刚
Owen应助HHZ采纳,获得10
刚刚
1秒前
2秒前
2秒前
隐形曼青应助LC采纳,获得10
3秒前
无极微光应助垃圾筐采纳,获得20
3秒前
秋梨膏完成签到 ,获得积分10
4秒前
4秒前
haifang发布了新的文献求助10
4秒前
4秒前
4秒前
5秒前
在水一方应助HHZ采纳,获得10
5秒前
5秒前
郭郭郭发布了新的文献求助10
6秒前
学术菜鸡123完成签到,获得积分10
6秒前
陈明健完成签到,获得积分10
6秒前
举人烧烤发布了新的文献求助10
6秒前
8秒前
8秒前
8秒前
9秒前
Bill发布了新的文献求助10
9秒前
dd发布了新的文献求助10
9秒前
852应助QAQ采纳,获得10
10秒前
lhm完成签到,获得积分10
10秒前
桐桐应助举人烧烤采纳,获得10
10秒前
田様应助HHZ采纳,获得10
11秒前
11秒前
量子星尘发布了新的文献求助10
11秒前
Yang发布了新的文献求助20
12秒前
14秒前
14秒前
14秒前
15秒前
外星人完成签到,获得积分10
15秒前
深情安青应助HHZ采纳,获得10
15秒前
顺心纸鹤发布了新的文献求助10
15秒前
高分求助中
(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
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exploring Nostalgia 500
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
Advanced Memory Technology: Functional Materials and Devices 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5666454
求助须知:如何正确求助?哪些是违规求助? 4882107
关于积分的说明 15117498
捐赠科研通 4825502
什么是DOI,文献DOI怎么找? 2583441
邀请新用户注册赠送积分活动 1537599
关于科研通互助平台的介绍 1495756