Department of Chemistry, Louisiana State University, Baton Rouge, LA 70803, USA.
Department of Chemistry, Indian Institute of Technology Delhi, Delhi 110016, India.
Sensors (Basel). 2020 Jan 22;20(3):615. doi: 10.3390/s20030615.
Herein, we examine two sensing schemes for detection and discrimination of chlorinated volatile organic compounds (VOCs). In this work, phosphonium ionic liquids (ILs) were synthesized and vapor sensing properties examined and compared to phosphonium IL-polymer composites. Pure IL sensors were used to develop a QCM-based multisensory array (MSA), while IL-polymer composites were used to develop an MSA and virtual sensor arrays (VSAs). It was found that by employing the composite MSA, five chlorinated VOCs were accurately discriminated at 95.56%, which was an increase in accuracy as compared to pure ILs MSA (84.45%). Data acquired with two out of three VSAs allowed discrimination of chlorinated VOCs with 100% accuracy. These studies have provided greater insight into the benefits of incorporating polymers in coating materials for enhanced discrimination accuracies of QCM-based sensor arrays. To the best of our knowledge, this is the first report of a QCM-based VSA for discrimination of closely related chlorinated VOCs.
本文研究了两种用于检测和区分氯化挥发性有机化合物（VOC）的传感方案。在这项工作中，合成了鏻离子液体（IL），并对其蒸气传感性能进行了研究和比较，与鏻 IL-聚合物复合材料进行了比较。纯 IL 传感器用于开发基于 QCM 的多传感器阵列（MSA），而 IL-聚合物复合材料用于开发 MSA 和虚拟传感器阵列（VSA）。结果发现，通过采用复合 MSA，可在 95.56%的精度下准确区分五种氯化 VOC，与纯 ILs MSA（84.45%）相比，精度有所提高。使用两个 VSA 中的两个采集的数据可实现对氯化 VOC 的 100%准确区分。这些研究为在基于 QCM 的传感器阵列中增强聚合物在涂层材料中的增强区分精度提供了更深入的认识。据我们所知，这是第一个用于区分密切相关的氯化 VOC 的基于 QCM 的 VSA 的报告。
