Optimal coating selection for the analysis of organic vapor mixtures with polymer-coated surface acoustic wave sensor arrays.
Optimal coating selection for the analysis of organic vapor mixtures with polymer-coated surface acoustic wave sensor arrays.
复制标题
使用聚合物涂层表面声波传感器阵列分析有机蒸气混合物的最佳涂层选择。
DOI：
10.1021/ac00102a012
复制
发表时间：
1995
影响因子：
7.4
通讯作者：
Patrash,SJ
中科院分区：
文献类型：
--
作者：
Zellers,ET;Batterman,SA;Han,M;Patrash,SJ
描述了一种用于确定包括在用于分析有机蒸气的表面声波（SAW）传感器阵列中的聚合物传感器涂层的最佳组的方法。该方法结合了扩展的不相交主成分回归（EDPCR）模式识别分析与Monte Carlo模拟的传感器响应的各种可能的涂层选择排名，并估计传感器阵列的能力，以确定任何一组蒸汽分析物。一个数据库组成的校准响应的10个聚合物涂层SAW传感器，以每六个有机溶剂vaporsfrom三个化学类的产生来证明该方法。在检测的浓度范围内，对单个蒸汽的响应呈线性，涂层在几个月的运行中保持稳定。对二元混合物的响应是单个组分响应的加和函数，即使对于能够形成强氢键的蒸气也是如此。EDPCR-Monte Carlo方法用于选择四个传感器阵列，该阵列在识别六种蒸气时提供最小的误差，无论是单独存在还是二元混合物。实验验证了预测的蒸汽识别率（87%），在大多数情况下，蒸汽浓度估计在10%的实验值。大多数的错误发生在识别时，一个单独的蒸汽不能区分从一个混合物的相同的蒸汽与一个低得多的浓度的第二个组件的最佳涂层组的选择几个三元蒸汽混合物也检查。结果表明，聚合物涂层的SAW传感器阵列的能力，用于分析的溶剂蒸气mixtures和EDPCR-Monte Carlo方法的优势，用于预测和优化performance.A越来越多的报道出现在最近几年使用的聚合物涂层的表面声波（SAW）传感器和传感器阵列的有机蒸气在低浓度下的直接测量。1-6当被配置为反馈振荡器电路中的频率控制元件时，
A method for determining the optimal set of polymer sensor coatings to include in a surface acoustic wave (SAW) sensor array for the analysis of organic vapors is described. The method combines an extended disjoint principal components regression (EDPCR) pattern rec-ognition analysis with Monte Carlo simulations of sensor responses to rank the various possible coating selections and to estimate the ability of the sensor array to identify any set of vapor analytes. A data base consisting of the calibrated responses of 10 polymer-coated SAW sensors to each of six organic solvent vaporsfrom three chemical classes was generated to demonstrate the method. Re-sponses to the individual vapors were linear over the concentration ranges examined, and coatings were stable over several months of operation. Responses to binary mixtures were additive functions of the individual com-ponent responses, even for vapors capable of strong hydrogen bonding. The EDPCR-Monte Carlo method was used to select the four-sensor array that provided the least error in identifying the six vapors, whether present individually or in binary mixtures. The predicted rate of vapor identification (87%) was experimentally verified, and the vapor concentrations were estimated within 10% of experimental values in most cases. The majority of errors in identification occurred when an individual vapor could not be differentiated from a mixture of the same vapor with a much lower concentration of a second component The selection of optimal coating sets for several ternary vapor mixtures is also examined. Results demonstrate the capabilities of polymer-coated SAW sensor arrays for analyzing of solvent vapor mixtures and the advantages of the EDPCR-Monte Carlo method for predicting and optimizing performance.An increasing number of reports have appeared in recent years on the use of polymer-coated surface acoustic wave (SAW) sensors and sensor arrays for direct measurement of organic vapors at low concentrations. 1-6 When configured as the frequency-control-ling element in a feedback oscillator circuit, the response of the