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

机译:QCM虚拟多传感器阵列,用于燃料识别和汽油掺假检测

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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 (VMSA) 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. (C) 2017 Elsevier Ltd. All rights reserved.
机译:在此,提出了一种用于区分石油基燃料的简单的石英晶体微天平(QCM)方法。在这方面,采用了石英晶体微天平(QCM)虚拟多传感器阵列(VMSA)来区分不同的石油基燃料,并以高精度检测汽油掺假。首先,使用基于离子液体的V-MSA来区分四种燃料类型(石油醚,汽油,煤油和柴油)。随后,该系统用于成功地区分三种汽油等级,以此作为汽油掺假研究的前身。最后,该系统用于检测和确定几种不同v / v比(1%,10%,20%和40%)的汽油掺杂物的性质。每项研究均达到了极高的准确性(100%),这充分说明了这种方法的潜力。该报告代表了用于检测汽油掺假的QCM传感器阵列的第一个示例。 (C)2017 Elsevier Ltd.保留所有权利。

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