Acoustic Wave Sensors for In-situ Detection and Characterization of Organic Contaminants in Aqueous Solution
Acoustic Wave Sensors for In-situ Detection and Characterization of Organic Contaminants in Aqueous Solution
批准号:
9876366
负责人:
Fabien Josse
金额:
$23.79万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-02-15 至 2003-08-31
中文摘要
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英文摘要
9876366JosseOverview. To detect organic compounds in contaminated ground and waste water that result in human and environmental health hazards, this research project will investigate and design a rapid, reliable, and high-sensitivity sensor device for reproducible measurements in liquid environments.Problem. Organic contaminants, particularly volatile organic compounds (VOCs), pose significant human and environmental health hazards. More precisely, groundwater and mixed waste water samples often contain such VOCs as trichloroethene, halogenated phenols, vinyl chloride, benzene, toluene, and xylene. Currently, sampling must be collected and transported to laboratories for analysis. As a consequence, analyses are not only delayed, but more importantly, the delays result in compromised scientific data due to degradation and evaporation of the samples. Accordingly, there is need for a rapid and sensitive method to reproducibly detect ground and waste water contaminants, with ease of testing.Goal and Objectives. The goal of this multidisciplinary research proposal is to investigate, characterize, and design polymer-coated chemical sensors for the direct, rapid, in-situ monitoring of organic compounds and other hazardous constituents in water. To meet this goal, three specific objectives will be met. 1. To investigate and design a reliable and high-sensitivity sensor platform utilizing shear horizontal surface acoustic wave (SH-SAW) device for reproducible sensor operation in liquid environments 2. To characterize individual sensors and classify polymer coating-analyte pairs into patterns3. To investigate the implementation of sensor arrays to characterize mixtures of analytes using the weak selectivity of the coatings together with proven pattern recognition methods.***
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