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Microsphere array based vapor sensing: New capabilities and applications.

机译:基于微球阵列的蒸气感测:新功能和应用。

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摘要

The work presented in this thesis details new capabilities and applications of a fluorescence-based microsphere array vapor sensing system developed in the Walt Laboratory over a period of several years. The system is designed on the principles of mammalian olfaction in that several cross-reactive and non-specific sensors are integrated into a high density array format. The system responds to an analyte vapor in a cross-reactive manner generating a multi-dimensional signal that can be used to train a pattern recognition program to identify subsequent exposures of the array to learned vapors.;Several ways in which the classification accuracy of this system can be improved are explored. New sensors based on porphyrin compounds were developed and their vapor sensing properties were characterized. This new class of sensors was systematically evaluated within the context of existing sensor types to determine their effectiveness in expanding the range of chemical compounds that can be reliably detected and classified. A second route to improving the classification accuracy of the system involves implementing a biomimetic data processing scheme. This method emulates the biological process of active sampling, or 'sniffing', and has been shown to reduce the number of errors in classification when the system is challenged with a broad range of chemical species. Finally, the ability to monitor the entire fluorescence spectrum from many individual sensors offers the opportunity to optimize the discrete wavelengths at which a response is observed. A method to collect this spectrum in a highly parallel fashion with excellent temporal resolution has been developed and is shown to improve the classification accuracy when information from multiple wavelengths is incorporated into a response matrix.;An exploration into new applications of this system is presented. Specifically, a preliminary investigation into using this device during the early stages of a fire investigation is described. The results of this investigation show that the system is capable of correctly detecting and classifying three types of ignitable liquids when presented in a realistic sample matrix. The design and construction of a portable device is also described and the results of field experiments are presented. The results of these studies demonstrate the basic functionality of the portable device and establish its usefulness in the detection of petroleum distillates in the ambient environment.
机译:本文提出的工作详细介绍了Walt实验室开发的基于荧光的微球阵列蒸气传感系统的新功能和应用,该系统历时数年。该系统是根据哺乳动物嗅觉原理设计的,其中几个交叉反应性和非特异性传感器集成为高密度阵列格式。该系统以交叉反应的方式响应分析物蒸气,生成多维信号,可用于训练模式识别程序,以识别阵列随后对学习到的蒸气的暴露。探索可以改进的系统。开发了基于卟啉化合物的新型传感器,并对其蒸气感测特性进行了表征。在现有传感器类型的背景下,系统地评估了这类新型传感器,以确定它们在扩展可以可靠检测和分类的化学化合物范围方面的有效性。提高系统分类准确度的第二种途径涉及实现仿生数据处理方案。这种方法模拟了主动采样或“嗅探”的生物学过程,并且当系统受到多种化学物质的挑战时,这种方法已显示出减少分类错误的数量。最后,能够监视来自许多单个传感器的整个荧光光谱的能力提供了优化观察到响应的离散波长的机会。已经开发了一种以高度并行的方式,具有优异的时间分辨率来收集该光谱的方法,并且该方法被证明可以在将来自多个波长的信息合并到响应矩阵中时提高分类精度。提出了对该系统的新应用的探索。具体而言,描述了在火灾调查的早期阶段使用该设备的初步调查。这项调查的结果表明,当系统以真实的样品矩阵形式呈现时,该系统能够正确地检测和分类三种可燃液体。还描述了便携式设备的设计和构造,并给出了现场实验的结果。这些研究的结果证明了便携式设备的基本功能,并确立了其在检测周围环境中的石油馏分中的有用性。

著录项

  • 作者

    Aernecke, Matthew J.;

  • 作者单位

    Tufts University.;

  • 授予单位 Tufts University.;
  • 学科 Chemistry Analytical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 200 p.
  • 总页数 200
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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