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首页> 外文期刊>Sensors and Actuators >Highly discriminative and sensitive detection of volatile organic compounds for monitoring indoor air quality using pure and Au-loaded 2D In_2O_3 inverse opal thin films
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Highly discriminative and sensitive detection of volatile organic compounds for monitoring indoor air quality using pure and Au-loaded 2D In_2O_3 inverse opal thin films

机译:使用纯金和Au负载的二维In_2O_3反蛋白石薄膜对挥发性有机化合物进行高判别和灵敏检测,以监测室内空气质量

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摘要

The lack of gas selectivity in oxide semiconductor chemiresistors has long been an obstacle to realizing discriminative detection of indoor volatile organic compounds (VOCs) with different health impacts. A simple and reliable algorithm to discriminate between critically harmful aromatic VOCs (benzene, xylene, and toluene) and less harmful ethanol is suggested by the simple combination of sensor signals from pure In2O3and Au-loaded In2O32D inverse opal (IO) thin films prepared by heat-treating the precursor-dipped self-assembled polystyrene templates and Au deposition. The Au-loaded In2O3IO sensor showed unprecedentedly high responses to 5 ppm ethanol (resistance ratio = 1640.2) and comparably high responses to 5 ppm benzene,p-xylene, and toluene (resistance ratio range of 674.5–1012.9). Such high gas responses were attributed to the periodically porous and thus highly gas-accessible structures, while the clear discrimination between aromatic VOCs and ethanol was achieved by tuning gas selectivity through systematic control of the size, morphology, and loading concentration of Au nano-catalysts. The results of this study can be used for reliable and precise monitoring of indoor air pollutants.
机译:长期以来,氧化物半导体化学电阻器中气体选择性的缺乏一直是实现对具有不同健康影响的室内挥发性有机化合物(VOC)进行判别检测的障碍。通过将纯In2O3和载有Au的In2O32D反蛋白石(IO)薄膜(通过加热制备)的传感器信号进行简单组合,提出了一种区分可靠的芳香族VOC(苯,二甲苯和甲苯)和危害较小的乙醇的简单可靠算法处理浸渍前体的自组装聚苯乙烯模板和金沉积。载有Au的In2O3IO传感器对5 ethanolppm的乙醇表现出前所未有的高响应(电阻比= 1640.2),对5 ppm的苯,对二甲苯和甲苯也表现出较高的响应(电阻比范围为674.5-1012.9)。如此高的气体响应归因于周期性的多孔性,因此具有高度的气体可及性;而通过系统地控制金纳米催化剂的大小,形态和负载浓度来调节气体的选择性,则可以清晰地区分芳香族VOC和乙醇。 。这项研究的结果可用于可靠和精确地监测室内空气污染物。

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