Ma Zhiqiang, Fu Mengyao, Gao Chenyang, Fan Shuyu, Chi Haozhen, Li Wei, Hou Dibo, Cao Yunqi
College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.
College of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210046, China.
J Hazard Mater. 2024 Jul 5;472:134553. doi: 10.1016/j.jhazmat.2024.134553. Epub 2024 May 7.
Microwave resonators combined with polymer absorption layers are widely used in volatile organic compound (VOC) detection based on their variable resonant frequencies. However, the response time is limited due to the polymer's slow volumetric absorption of VOC molecules. By constructing a porous structure in Polydimethylsiloxane (PDMS), resulting in reduced the response time to as short as 71.1%. To mitigate the sensitivity decline caused by the porous PDMS, a trenched-substrate complementary split-ring resonator (CSRR) is proposed for enhancing the interaction between the electromagnetic fields (EMFs) and the porous PDMS with VOCs. The removal of the substrate beneath CSRR's sensing region enhances the effective EMF, increasing frequency and amplitude sensitivities up to 175.5% and 137.8%, respectively. Responses to four common VOCs by the sensor show a maximum sensitivity of 217 Hz/ppm and a minimum limit of detection of 295 ppm. Additionally, resonant parameters and extracted lumped parameters are utilized to establish two decision-tree-based VOC classification models, achieving high accuracies of 98.71% and 99.59%, respectively. And the latter one fully utilizing responses throughout the swept band, proves superior in identifying similar substances. This sensor technology helps promote the sensitive detection and accurate classification of diverse VOCs.
结合聚合物吸收层的微波谐振器因其可变的谐振频率而被广泛应用于挥发性有机化合物（VOC）检测。然而，由于聚合物对VOC分子的体吸收缓慢，响应时间受到限制。通过在聚二甲基硅氧烷（PDMS）中构建多孔结构，可将响应时间缩短至原来的71.1%。为了减轻多孔PDMS导致的灵敏度下降，提出了一种沟槽式衬底互补分裂环谐振器（CSRR），以增强电磁场（EMF）与含有VOC的多孔PDMS之间的相互作用。去除CSRR传感区域下方的衬底可增强有效EMF，频率灵敏度和幅度灵敏度分别提高至原来的175.5%和137.8%。该传感器对四种常见VOC的响应显示，最大灵敏度为217 Hz/ppm，最低检测限为295 ppm。此外，利用谐振参数和提取的集总参数建立了两个基于决策树的VOC分类模型，准确率分别达到98.71%和99.59%。后者充分利用了整个扫描频段的响应，在识别相似物质方面表现更优。这种传感器技术有助于推动对各种VOC的灵敏检测和准确分类。
