Application of Signal Processing & Dynamic Modeling Techniques to Modern Microsensors

摘要-McAb- CTS-9616085 目前，大多数化工厂的操作没有真实的时间组成测量的好处。 原因包括成本、可靠性和组成传感器的鲁棒性。 硅基微传感器有望对化学过程的操作产生重大影响。 每个微传感器占据大约400平方微米的表面积，因此在单个小芯片上放置数百个传感器是可行的。 二氧化锡（SnO 2）气体微传感器正在国家标准与技术研究所（NIST）开发，PI正在与该研究所合作。 这些传感器具有几个独特的特征，包括它们的小尺寸，直径约200微米，它们由传统的互补金属氧化物半导体（CMOS）铸造厂制造，并且能够使它们的工作温度以循环模式快速变化，以优化它们对特定气体种类的灵敏度。 在这些传感器可用于解决过程问题之前，仍有许多问题有待解决。 这些问题中的一些包括漂移和噪声效应，对某些化学品缺乏敏感性，以及材料问题。 SnO 2微传感器是非特异性的，它们可以对许多化学物质做出响应。 该研究项目涉及对SnO 2微传感器的进一步研究。 在使用微传感器的广泛问题需要进一步研究：（1）人们可以使用传感器来确定是否存在化学物种，这是一个分类问题;和（2）人们可以使用传感器来确定哪些化学物质存在以及它们的具体浓度，这是一个定量分析问题。 PI研究的短期目标是将信号处理和动态建模技术应用于这些微传感器，以促进其在分类问题中的应用。 微传感器的许多应用涉及分类，例如危险泄漏、气味和火灾检测。 计划的信号处理和建模方法有可能扩展到定量分析问题-因此，研究的长期目标是帮助推进微传感器阵列的使用，以解决定量分析问题。

ABSTRACT - McAvoy - CTS-9616085 At present most chemical plants are operated without the benefit of real time composition measurements. The reasons include cost, reliability, and robustness of composition sensors. Silicon based microsensors, hold promise for having a major impact on the operation of chemical processes. Each microsensor occupies approximately 400 square microns of surface area, so it is feasible to place several hundred sensors on a single, small chip. Tin dioxide (SnO2) gas microsensors are being developed at the National Institute of Standards and Technology (NIST), with whom the PI's are collaborating. These sensors have several unique features including their small size, approximately 200 micrometers in diameter, their fabrication by a conventional complementary metal oxide semiconductor (CMOS) foundry, and the ability to have their operating temperature changed rapidly, in a cyclic pattern, to optimize their sensitivity to a particular gas species. There are a number of problems that remain to be solved before these sensors can be used to solve process problems. Some of these problems include drift and noise effects, lack of sensitivity to some chemicals, and material problems. The SnO2 microsensors are nonspecific and they can respond to a number of chemical species. The research project involves further investigations of SnO2 microsensors. In using microsensors to broad problems need further study: (1) One can use the sensors to determine whether or not a chemical species is present, which is a problem in classification; and (2) one can use the sensors to determine which chemicals are present as well as their specific concentrations, which is a problem in quantitative analysis. The short range goal of the PI's research is to apply signal processing and dynamic modeling techniques to these microsensors to advance their use in the classification problem. Many applications of microsensors involve classification, e.g. hazardous leak, odor, and fire detection . The signal processing and modeling methods planned have the potential to be expanded to the quantitative analysis problem---thus, the long range goal of the research is to help advance the use of microsensor arrays for solving the quantitative analysis problem.