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Class Specific Discrimination of Volatile Organic Compounds Using a Quartz Crystal Microbalance Based Multisensor Array

机译:使用基于石英晶体微天平的多传感器阵列对挥发性有机化合物进行类别区分

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摘要

The use of quartz crystal microbalance (QCM) sensor arrays for analyses of volatile organic compounds (VOC) has attracted significant interest in recent years. In this regard, a >group of >uniformed >materials >based on >organic >salts (GUMBOS) has proven to be promising recognition elements in QCM based sensor arrays due to diverse properties afforded by this class of tunable materials. Herein, we examine the application of four novel phthalocyanine based GUMBOS as recognition elements for VOC sensing using a QCM based multisensor array (MSA). These synthesized GUMBOS are composed of copper (II) phthalocyaninetetrasulfonate (CuPcS4) anions coupled with ammonium or phosphonium cations respectively (tetrabutylammonium (TBA), tetrabutylphosphonium (P4444), 3-(dodecyldimethyl-ammonio)propanesulfonate (DDMA), and tributyl-n-octylphosphonium (P4448)). These materials were characterized using ESI-MS and FTIR, while thermal properties were investigated using TGA. Vapor sensing properties of these GUMBOS towards a set of common VOCs at three sample flow rate ratios were examined. Upon exposure to VOCs, each sensor generated analyte specific response patterns that were recorded and analyzed using principal component and discriminant analyses. Use of this MSA allowed discrimination of analytes into different functional group classes (alcohols, chlorohydrocarbons, aromatic hydrocarbons, and hydrocarbons) with 98.6% accuracy. Evaluation of these results provides further insight into the use of phthalocyanine GUMBOS as recognition elements for QCM-based MSAs for VOC discrimination.
机译:近年来,使用石英晶体微天平(QCM)传感器阵列分析挥发性有机化合物(VOC)引起了人们的极大兴趣。在这方面,> u 的> g 组合是> o m 品类> b 事实证明,>有机> s 替代品(GUMBOS)在此类基于QCM的传感器阵列中是很有前途的识别元素,因为此类可调材料提供了多种特性。在这里,我们研究了基于QCM的多传感器阵列(MSA)四种新颖的基于酞菁的GUMBOS作为VOC传感的识别元件的应用。这些合成的GUMBOS由分别与铵或copper阳离子(四丁基铵(TBA),四丁基phosph(P4444),3-(十二烷基二甲基-铵)丙烷磺酸盐(DDMA)和三丁基正丁基磺酸盐)耦合的酞菁铜(II)酞菁铜(CuPcS4)阴离子组成。辛基phosph(P4448))。使用ESI-MS和FTIR对这些材料进行了表征,同时使用TGA研究了其热性能。检查了这些GUMBOS在三种样品流速比下对一组常见VOC的蒸气感测特性。暴露于VOC后,每个传感器都会生成特定于分析物的响应模式,并使用主成分和判别分析进行记录和分析。使用此MSA可以将分析物区分为不同的官能团类别(醇,氯代烃,芳族烃和烃),准确度为98.6%。对这些结果的评估为使用酞菁GUMBOS作为基于QCM的VOC鉴别MSA的识别元素提供了进一步的见解。

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