Predicting low temperature lubricant rheology using nuclear magnetic resonance spectroscopy and mass spectrometry

B. K. Sharma; A. J. Stipanovic

doi:10.1023/b:tril.0000009709.83578.f5

Predicting low temperature lubricant rheology using nuclear magnetic resonance spectroscopy and mass spectrometry

B. K. Sharma, A. J. Stipanovic

Research output: Contribution to journal › Article › peer-review

Abstract

The effect or hydrocarbon base-oil composition on the low temperature rheology of lubricants was evaluated in this study. Average structural parameters (ASPs) were derived using ¹³C nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). These ASPs were then used to develop statistical and neural network models capable of predicting the low temperature properties (LTPs) of base-oil. Isoparaffinic structures were found to be most important in defining low temperature rheology. 04 Plenum Publishing Corporation.

Original language	English (US)
Pages (from-to)	11-19
Number of pages	9
Journal	Tribology Letters
Volume	16
Issue number	1-2
DOIs	https://doi.org/10.1023/b:tril.0000009709.83578.f5
State	Published - Feb 2004
Externally published	Yes

Keywords

Low temperature rheology
Lubricants
Mineral base oils
NMR

ASJC Scopus subject areas

Mechanics of Materials
Mechanical Engineering
Surfaces and Interfaces
Surfaces, Coatings and Films

Online availability

10.1023/b:tril.0000009709.83578.f5

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AB - The effect or hydrocarbon base-oil composition on the low temperature rheology of lubricants was evaluated in this study. Average structural parameters (ASPs) were derived using 13C nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). These ASPs were then used to develop statistical and neural network models capable of predicting the low temperature properties (LTPs) of base-oil. Isoparaffinic structures were found to be most important in defining low temperature rheology. 04 Plenum Publishing Corporation.

KW - Low temperature rheology

KW - Lubricants

KW - Mineral base oils

KW - NMR

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Predicting low temperature lubricant rheology using nuclear magnetic resonance spectroscopy and mass spectrometry

Abstract

Keywords

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