Identification of Base Stock in Engine Oils by Near Infrared and Fluorescence Spectroscopies Coupled with Chemometrics

Autor: Monica Casale, Maryam Hooshyari
Rok vydání: 2021
Předmět:
Zdroj: Surveys in Geophysics. 42:451-465
ISSN: 1573-0956
0169-3298
Popis: Engine oils are produced with a blend of almost 80% (w/w) base oils and 20% (w/w) of different additives. This study investigates, for the first time, the capabilities of NIR (Near Infrared) and EEM (Emission-Extraction Matrix) fluorescence spectroscopies coupled with chemometrics as low-cost, green and non-destructive methods in identifying the type of base stock into engine oil. In order to reach this goal, base stocks of different American Petroleum Institute (API) groups were analysed without any pre-treatment. PCA (Principal component analysis) performed on NIR and unfolded EEM spectra showed that samples form clusters according to their API groups and to chemical composition. PARAFAC (Parallel Factor Analysis) was also applied on 3-way fluorescence data and outcomes were consistent with PCA results. PLS-DA (Partial Least Squares Discriminant Analysis) was able to classify the base stock samples according to the API groups and satisfactory results were achieved: the correct prediction abilities on an external test set using NIR and EEM fluorescence spectroscopies were 87% and 85%, respectively. In addition, the determination of the base oil group at different gasoline engine oil performance levels was used as a method to evaluate the efficiency of the lubricants. Both spectroscopic methods appear to be fast and non-destructive to characterize the base stocks in analysing pure base stocks and engine oils with different performance levels.
Databáze: OpenAIRE
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