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先进的化学气相沉积法合成了负载氧化锇的氧化钨纳米线作为气体传感器阵列：通过主成分分析和人工神经网络增强检测能力。

AACVD synthesized tungsten oxide-NWs loaded with osmium oxide as a gas sensor array: enhancing detection with PCA and ANNs.

作者信息

Santos-Betancourt Alejandro, Navarrete Èric, Cossement Damien, Bittencourt Carla, Llobet Eduard

机构信息

Universitat Rovira i Virgili, Microsystems Nanotechnologies for Chemical Analysis (MINOS), Departament d'Enginyeria Electronica Països Catalans, 26 43007 Tarragona Catalunya Spain.

IU-RESCAT, Research Institute in Sustainability, Climatic Change and Energy Transition, Universitat Rovira i Virgili Joanot Martorell 15 43480 Vilaseca Spain

出版信息

RSC Adv. 2024 Nov 1;14(47):34985-34995. doi: 10.1039/d4ra05346j. eCollection 2024 Oct 29.

DOI:10.1039/d4ra05346j
PMID:39493545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11529781/
Abstract

This paper presents the fabrication of sensors based on tungsten trioxide nanowires decorated with osmium oxide nanoparticles using the aerosol-assisted chemical vapor deposition (AACVD) technique. This methodology allows the obtention of different osmium oxide decoration loadings on the tungsten oxide nanowires. The morphological and chemical characteristics; and the structural properties of the sensing layers of the sensors were studied using different techniques such as FESEM, HR-TEM, and ToF-SIMS. The gas sensing properties were analyzed for pure tungsten trioxide sensors and tungsten trioxide loaded with osmium exposed to nitrogen dioxide, hydrogen, and ethanol, thus assessing the impact of the loading on the sensor response. A sensor array comprising pure and osmium-loaded tungsten oxide devices coupled to multivariate pattern recognition techniques is shown to perform well in gas identification and quantification tasks, offering promising implications in the field of gas sensing technology.

摘要

本文介绍了采用气溶胶辅助化学气相沉积（AACVD）技术制备基于氧化锇纳米颗粒修饰的三氧化钨纳米线的传感器。该方法能够在氧化钨纳米线上获得不同的氧化锇修饰负载量。使用场发射扫描电子显微镜（FESEM）、高分辨率透射电子显微镜（HR-TEM）和飞行时间二次离子质谱（ToF-SIMS）等不同技术研究了传感器传感层的形态和化学特性以及结构性质。对纯三氧化钨传感器和负载氧化锇的三氧化钨传感器在暴露于二氧化氮、氢气和乙醇时的气敏特性进行了分析，从而评估负载对传感器响应的影响。结果表明，由纯的和负载氧化锇的氧化钨器件组成的传感器阵列与多元模式识别技术相结合，在气体识别和定量任务中表现良好，在气敏技术领域具有广阔的应用前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/98ef53d165fc/d4ra05346j-f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/d7dce9dbfb7b/d4ra05346j-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/cef18d249682/d4ra05346j-f5.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/db7a4a1d6c89/d4ra05346j-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/5a0328773b02/d4ra05346j-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/403fbbec7a59/d4ra05346j-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/98ef53d165fc/d4ra05346j-f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/d7dce9dbfb7b/d4ra05346j-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/8d3c92dee30e/d4ra05346j-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/5fb57b567118/d4ra05346j-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/8f1c2890c00b/d4ra05346j-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/cef18d249682/d4ra05346j-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/cbae27f1c85e/d4ra05346j-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/db7a4a1d6c89/d4ra05346j-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/5a0328773b02/d4ra05346j-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/403fbbec7a59/d4ra05346j-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/485a/11529781/98ef53d165fc/d4ra05346j-f10.jpg

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