启用MEMS化学微传感器阵列用于痕量分析物检测

D. Meier, J. Evju, K. Benkstein, B. Raman, Z. Boger, D. Lahr, S. Semancik
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引用次数: 1

摘要

我们描述了一种电导气体微传感器技术的发展,该技术以优化的方式结合了纳米结构传感膜、MEMS微热板阵列平台和人工神经网络信号处理。单个可寻址的微量元素,包括各种半导体氧化物,被温度调制以产生分析丰富的数据流,允许识别背景混合物中的低浓度目标分析物。这份简短的报告强调:1)最近开发的选择和处理方法,用于在MEMS平台上整合高性能传感材料;2)特殊的操作模式和数据采集方法,以确保良好的信号质量,同时最大限度地提高信息内容;3)信号分析技术,包括预处理程序和先进的识别算法。
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Enabling MEMS Chemical Microsensor Arrays for Trace Analyte Detection
We describe the development of a conductometric gas microsensor technology that combines, in an optimized manner, nanostructured sensing films, MEMS microhotplate array platforms, and artificial neural networks signal processing. Individually addressable microelements, including varied semiconducting oxides, are temperature modulated to produce analytically rich data streams that allow recognition of low concentration target analytes in background mixtures. This brief report emphasizes: 1) recently developed selection and processing methods for incorporation of high performance sensing materials on the MEMS platforms, 2) special operational modes and data acquisition approaches for ensuring good signal quality while maximizing information content, and 3) signal analysis techniques that include preprocessing routines and advanced recognition algorithms.
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