基于气相色谱的声表面波传感器系统对有毒环境气体/蒸汽的潜在检测和识别的特性研究

Q3 Materials Science
A. Ashibaparveen, V. Senthilkumar, Venkatesan Thirumal, P. Gowdhaman, Haresh M. Pandya
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引用次数: 0

摘要

本文介绍了一种定制设计的基于gc的SAW电子鼻传感器系统的特性,以研究该传感器系统检测和识别低中毒性和高毒性蒸汽的传感能力。半自动多蒸汽发生器产生化合物蒸气,然后将其暴露在传感系统中,以检查其在不同浓度下的性能。GC-SAW传感器的时域和频率响应注意到对不同化合物的重复循环,如二甲苯,1,2二溴乙烷,硫酸二甲酯,磷酸三乙酯,硝基苯,三氯化磷被测试。生成的数据使用主成分分析(PCA)技术进行检查,以检测单个化合物的独特响应。并报道了实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterization Studies of a GC based SAW Sensor System for Potential Detection and Identification of Toxic Environmental Gases/Vapors
The characterization of a custom-designed GC-based SAW e-Nose sensor system is presented here to study the sensing ability of the sensor system to detect and identify low medium and high toxic vapors. A semi-automated multi-vapor generator generates vapors of chemical compounds that are then exposed to the sensing system to examine its performance under various concentrations. Time-domain verses frequency response of GC-SAW Sensor is noted for repeated cycles against different chemical compounds like xylene, 1,2 dibromoethane, dimethyl sulfate, triethyl phosphate, nitrobenzene, phosphorous trichloride being tested. The generated data is examined using a principle component analysis (PCA) technique to detect a unique response for an individual chemical compound. Experimental results are reported.
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来源期刊
Journal of Water and Environmental Nanotechnology
Journal of Water and Environmental Nanotechnology Materials Science-Materials Science (miscellaneous)
CiteScore
2.40
自引率
0.00%
发文量
0
审稿时长
8 weeks
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