利用体声波谐振器虚拟传感器阵列研究挥发性有机化合物与超分子在动态振荡时的吸附相互作用。

IF 7.3 1区 工程技术 Q1 INSTRUMENTS & INSTRUMENTATION
Microsystems & Nanoengineering Pub Date : 2024-07-17 eCollection Date: 2024-01-01 DOI:10.1038/s41378-024-00729-x
Zilun Wang, Zeyu Zhao, Suhan Jin, Feilong Bian, Ye Chang, Xuexin Duan, Xiangdong Men, Rui You
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引用次数: 0

摘要

超分子被认为是挥发性有机化合物(VOCs)传感应用的理想材料。正确理解主客体相互作用中发生的吸附过程对于提高基于超分子的传感阵列的模式识别能力至关重要。在此,我们报告了一种研究动态主-客体识别过程的新方法,即采用能够产生多种振荡幅度并同时记录对挥发性有机化合物的多种响应的体声波(BAW)谐振器。在四个 BAW 传感器上改性了 β-环糊精(β-CD)的自组装单层(SAM),以展示振荡幅度和 SAM 长度方面的气表相互作用。根据该方法,通过对单个传感器在不同振幅下的多个响应进行模式识别,可以实现虚拟传感器阵列(VSA)型电子鼻(e-nose)。VOCs 分析分别采用主成分分析法(PCA)进行单个 VOC 识别和线性判别分析法(LDA)进行 VOCs 混合物分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Investigation of sorptive interactions between volatile organic compounds and supramolecules at dynamic oscillation using bulk acoustic wave resonator virtual sensor arrays.

Investigation of sorptive interactions between volatile organic compounds and supramolecules at dynamic oscillation using bulk acoustic wave resonator virtual sensor arrays.

Supramolecules are considered as promising materials for volatile organic compounds (VOCs) sensing applications. The proper understanding of the sorption process taking place in host-guest interactions is critical in improving the pattern recognition of supramolecules-based sensing arrays. Here, we report a novel approach to investigate the dynamic host-guest recognition process by employing a bulk acoustic wave (BAW) resonator capable of producing multiple oscillation amplitudes and simultaneously recording multiple responses to VOCs. Self-assembled monolayers (SAMs) of β-cyclodextrin (β-CD) were modified on four BAW sensors to demonstrate the gas-surface interactions regarding oscillation amplitude and SAM length. Based on the method, a virtual sensor array (VSA) type electronic nose (e-nose) can be realized by pattern recognition of multiple responses at different oscillation amplitudes of a single sensor. VOCs analysis was realized respectively by using principal component analysis (PCA) for individual VOC identification and linear discriminant analysis (LDA) for VOCs mixtures classification.

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来源期刊
Microsystems & Nanoengineering
Microsystems & Nanoengineering Materials Science-Materials Science (miscellaneous)
CiteScore
12.00
自引率
3.80%
发文量
123
审稿时长
20 weeks
期刊介绍: Microsystems & Nanoengineering is a comprehensive online journal that focuses on the field of Micro and Nano Electro Mechanical Systems (MEMS and NEMS). It provides a platform for researchers to share their original research findings and review articles in this area. The journal covers a wide range of topics, from fundamental research to practical applications. Published by Springer Nature, in collaboration with the Aerospace Information Research Institute, Chinese Academy of Sciences, and with the support of the State Key Laboratory of Transducer Technology, it is an esteemed publication in the field. As an open access journal, it offers free access to its content, allowing readers from around the world to benefit from the latest developments in MEMS and NEMS.
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