材料科学
聚苯乙烯
聚合物
丙酮
挥发性有机化合物
甲醇
异丙醇
甲苯
辛烷值
分子印迹聚合物
化学工程
纳米颗粒
选择性
有机化学
纳米技术
化学
复合材料
催化作用
工程类
作者
Bishakha Ray,Saurabh Parmar,Varsha Vijayan,Satyendra Vishwakarma,Suwarna Datar
出处
期刊:Nanotechnology
[IOP Publishing]
日期:2022-01-18
卷期号:33 (20): 205505-205505
被引量:6
标识
DOI:10.1088/1361-6528/ac4c5e
摘要
Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV-vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class.
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