Title
QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration
Document Type
Article
Publication Date
1-1-2017
Abstract
© 2017 Elsevier Ltd Herein, a simplistic quartz crystal microbalance (QCM) approach for discrimination of petroleum based fuels is presented. In this regard, a quartz crystal microbalance (QCM) virtual multisensor array (V-MSA) was employed to discriminate between different petroleum based fuels and to detect gasoline adulteration with high accuracy. First, an ionic liquid based V-MSA was used to discriminate between four fuel types (petroleum ether, gasoline, kerosene, and diesel). Subsequently, the system was used to successfully discriminate between three gasoline grades as a precursor for studies of gasoline adulteration. Finally, the system was used to detect and determine the nature of several gasoline adulterants at different v/v ratios (1%, 10%, 20% and 40%). Excellent accuracy (100%) was achieved for each study extolling the potential of this approach. This report represents the first example of a QCM sensor array utilized for detection of gasoline adulteration.
Publication Source (Journal or Book title)
Fuel
First Page
38
Last Page
46
Recommended Citation
Speller, N., Siraj, N., Vaughan, S., Speller, L., & Warner, I. (2017). QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration. Fuel, 199, 38-46. https://doi.org/10.1016/j.fuel.2017.02.066
