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一种在温度循环操作中使用MOS传感器对宽浓度范围内还原气体进行简便定量和识别的技术。

Facile Quantification and Identification Techniques for Reducing Gases over a Wide Concentration Range Using a MOS Sensor in Temperature-Cycled Operation.

作者信息

Schultealbert Caroline, Baur Tobias, Schütze Andreas, Sauerwald Tilman

机构信息

Lab for Measurement Technology, Saarland University, 66123 Saarbrücken, Germany.

出版信息

Sensors (Basel). 2018 Mar 1;18(3):744. doi: 10.3390/s18030744.

Abstract

Dedicated methods for quantification and identification of reducing gases based on model-based temperature-cycled operation (TCO) using a single commercial MOS gas sensor are presented. During high temperature phases the sensor surface is highly oxidized, yielding a significant sensitivity increase after switching to lower temperatures (differential surface reduction, DSR). For low concentrations, the slope of the logarithmic conductance during this low-temperature phase is evaluated and can directly be used for quantification. For higher concentrations, the time constant for reaching a stable conductance during the same low-temperature phase is evaluated. Both signals represent the reaction rate of the reducing gas on the strongly oxidized surface at this low temperature and provide a linear calibration curve, which is exceptional for MOS sensors. By determining these reaction rates on different low-temperature plateaus and applying pattern recognition, the resulting footprint can be used for identification of different gases. All methods are tested over a wide concentration range from 10 ppb to 100 ppm (4 orders of magnitude) for four different reducing gases (CO, H₂, ammonia and benzene) using randomized gas exposures.

摘要

本文介绍了基于模型的温度循环操作(TCO),使用单个商用MOS气体传感器对还原气体进行定量和识别的专用方法。在高温阶段,传感器表面被高度氧化,切换到较低温度后灵敏度显著提高(差分表面还原,DSR)。对于低浓度,评估该低温阶段对数电导的斜率,并可直接用于定量。对于较高浓度,评估在相同低温阶段达到稳定电导的时间常数。这两个信号都代表了还原气体在该低温下强氧化表面上的反应速率,并提供了一条线性校准曲线,这对于MOS传感器来说是很特别的。通过在不同的低温平台上确定这些反应速率并应用模式识别,得到的特征图谱可用于识别不同的气体。所有方法均使用随机气体暴露,在10 ppb至100 ppm(4个数量级)的宽浓度范围内对四种不同的还原气体(CO、H₂、氨和苯)进行了测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6177/5876710/1a3bed32c257/sensors-18-00744-g001.jpg

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