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热电子鼻的传感性能:ZnO与SnO纳米线的比较

Sensing Performance of Thermal Electronic Noses: A Comparison between ZnO and SnO Nanowires.

作者信息

Tonezzer Matteo, Armellini Cristina, Toniutti Laura

机构信息

IMEM-CNR, Sede di Trento-FBK, Via alla Cascata 56/C, 38123 Trento, Italy.

Center Agriculture Food Environment, University of Trento/Fondazione Edmund Mach, Via E. Mach 1, 38010 San Michele all'Adige, Italy.

出版信息

Nanomaterials (Basel). 2021 Oct 20;11(11):2773. doi: 10.3390/nano11112773.

DOI:10.3390/nano11112773
PMID:34835538
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8624967/
Abstract

In recent times, an increasing number of applications in different fields need gas sensors that are miniaturized but also capable of distinguishing different gases and volatiles. Thermal electronic noses are new devices that meet this need, but their performance is still under study. In this work, we compare the performance of two thermal electronic noses based on SnO and ZnO nanowires. Using five different target gases (acetone, ammonia, ethanol, hydrogen and nitrogen dioxide), we investigated the ability of the systems to distinguish individual gases and estimate their concentration. SnO nanowires proved to be more suitable for this purpose with a detection limit of 32 parts per billion, an always correct classification (100%) and a mean absolute error of 7 parts per million.

摘要

近年来,不同领域中越来越多的应用需要小型化但又能够区分不同气体和挥发性物质的气体传感器。热电子鼻是满足这一需求的新型设备,但其性能仍在研究之中。在这项工作中,我们比较了基于SnO和ZnO纳米线的两种热电子鼻的性能。使用五种不同的目标气体(丙酮、氨、乙醇、氢气和二氧化氮),我们研究了系统区分单个气体并估计其浓度的能力。结果表明,SnO纳米线更适合此用途,其检测限为十亿分之32,分类准确率始终为100%,平均绝对误差为百万分之7。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/f150a15a0db2/nanomaterials-11-02773-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/13954453f399/nanomaterials-11-02773-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/4d80ea214179/nanomaterials-11-02773-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/0ff1dd25fbd1/nanomaterials-11-02773-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/fff075d2ce9a/nanomaterials-11-02773-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/77d5012f09f5/nanomaterials-11-02773-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/254076c26fbd/nanomaterials-11-02773-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/f150a15a0db2/nanomaterials-11-02773-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/13954453f399/nanomaterials-11-02773-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/4d80ea214179/nanomaterials-11-02773-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/0ff1dd25fbd1/nanomaterials-11-02773-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/fff075d2ce9a/nanomaterials-11-02773-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/77d5012f09f5/nanomaterials-11-02773-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/254076c26fbd/nanomaterials-11-02773-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd91/8624967/f150a15a0db2/nanomaterials-11-02773-g007.jpg

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2
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J Hazard Mater. 2022 Jan 15;422:126832. doi: 10.1016/j.jhazmat.2021.126832. Epub 2021 Aug 5.
3
Estimates of emission strengths of 43 VOCs in wintertime residential indoor environments, Beijing.
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4
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6
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7
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8
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9
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10
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Nanomaterials (Basel). 2020 Mar 11;10(3):511. doi: 10.3390/nano10030511.