QCM virtual multisensor array for fuel discrimination and detection of gasoline adulteration
© 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)
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