Rational Design of QCM-D Virtual Sensor Arrays Based on Film Thickness, Viscoelasticity, and Harmonics for Vapor Discrimination
Rational Design of QCM-D Virtual Sensor Arrays Based on Film Thickness, Viscoelasticity, and Harmonics for Vapor Discrimination
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DOI：
10.1021/ac5046824
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发表时间：
2015-05-19
影响因子：
7.4
通讯作者：
Warner, Isiah M.
中科院分区：
文献类型：
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作者：
Speller, Nicholas C.;Siraj, Noureen;Warner, Isiah M.
在这里，我们展示了一种替代策略，通过使用单个传感器来创建基于QCM的传感器阵列，以提供每个分析物的多个响应。模拟虚拟传感器阵列（VSA）的传感器通过将离子液体薄膜（1-辛基-3-甲基咪唑溴盐（[OMIm][Br]）或1-辛基-3-甲基咪唑硫氰酸盐（[OMIm][SCN]））沉积到QCM-D换能器的表面上来开发。传感器暴露于18种不同的有机蒸气（醇，烃，氯代烃，腈）属于相同或不同的同源系列。在多个谐波下测量所得频移（Δ f），并使用主成分分析（PCA）和判别分析（DA）进行评估，这表明分析物可以极高的准确度进行分类。在几乎所有的情况下，同一类的成员，即，组内歧视，识别的准确性是100%，确定使用二次判别分析（QDA）。令人印象深刻的是，一些VSA允许以接近100%的准确度对所有18种测试分析物进行分类。这些结果强调了利用较少利用的影响信号转导的特性的重要性。总体而言，这些结果表明虚拟传感器阵列策略在利用QCM检测和区分汽相分析物方面具有出色的潜力。据我们所知，这是第一次报告QCM VSAs，以及实验传感器阵列，主要是基于粘弹性，膜厚，谐波。
Herein, we demonstrate an alternative strategy for creating QCM-based sensor arrays by use of a single sensor to provide multiple responses per analyte. The sensor, which simulates a virtual sensor array (VSA), was developed by depositing a thin film of ionic liquid, either 1-octyl-3-methylimidazolium bromide ([OMIm][Br]) or 1-octyl-3-methylimidazolium thiocyanate ([OMIm][SCN]), onto the surface of a QCM-D transducer. The sensor was exposed to 18 different organic vapors (alcohols, hydrocarbons, chlorohydrocarbons, nitriles) belonging to the same or different homologous series. The resulting frequency shifts (Delta f) were measured at multiple harmonics and evaluated using principal component analysis (PCA) and discriminant analysis (DA) which revealed that analytes can be classified with extremely high accuracy. In almost all cases, the accuracy for identification of a member of the same class, that is, intraclass discrimination, was 100% as determined by use of quadratic discriminant analysis (QDA). Impressively, some VSAs allowed classification of all 18 analytes tested with nearly 100% accuracy. Such results underscore the importance of utilizing lesser exploited properties that influence signal transduction. Overall, these results demonstrate excellent potential of the virtual sensor array strategy for detection and discrimination of vapor phase analytes utilizing the QCM. To the best of our knowledge, this is the first report on QCM VSAs, as well as an experimental sensor array, that is based primarily on viscoelasticity, film thickness, and harmonics.