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Updated: Sep 8, 2025

Determination of Total Lipid and Lipid Classes in Marine Samples
Published on: December 11, 2021
Screening and classification of hydrogenated vegetable oils using a combination of SFC-FID, SFC-MS and GCxGC-MS
Laval R Nicolas1, Jim Barker2, Jody Clark3
1School of Chemistry and Chemical Engineering, University of Southampton, SO17 1BJ, UK. J.M.Herniman@soton.ac.uk.
Abstract:
This study employs a combination of orthogonal chromatographic and detection techniques to screen and characterise hydrogenated vegetable oils (HVOs), addressing the question of whether HVOs share the same composition. The data revealed that the HVOs are different, and the variations are primarily influenced by the initial feedstocks and production processes. Significant variations in linear and branched hydrocarbon distribution, particularly in the C14-C18 range were observed and the detection of polar components, such as free fatty acids, fatty acid methyl esters, and mono-, di-, and tri-acylglycerides in some samples, suggested potential concerns related to fuel storage, delivery, and performance. Each analytical technique contributed unique insights: GCxGC-MS provided extended chromatographic resolution and detailed identification of saturates and aromatics, including the critical iso-alkane to n-alkane ratio, which is essential for predicting cold flow properties. Additionally, a streamlined data visualisation method was introduced to facilitate the assessment of fuel profile. SFC-FID enabled quantitative group-based separations of polars, saturates, and aromatics with minimal sample preparation and SFC-ESI-MS selectively separated and detected individual polar compounds. The combined approach highlights the importance of using multiple techniques to obtain a chemical profile of the individual HVOs. Given the observed compositional differences, this study suggests that "HVO" is an overly broad term that does not accurately reflect the chemical diversity of these fuels. A refined classification system distinguishing HVO subclasses is suggested that better represents these variations.
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