Vapor recognition with small arrays of polymer-coated microsensors. A comprehensive analysis
Vapor recognition with small arrays of polymer-coated microsensors. A comprehensive analysis
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DOI：
10.1021/ac9902401
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发表时间：
1999-09-01
影响因子：
7.4
通讯作者：
Zellers, ET
中科院分区：
文献类型：
--
作者：
Park, J;Groves, WA;Zellers, ET
给出了作为蒸汽传感器阵列中传感器数量的函数的蒸汽识别的综合分析。从6个聚合物涂层表面声波(SAW)传感器收集的16个有机蒸汽的响应被用于结合模式识别分析的蒙特卡罗模拟，以推导蒸汽识别率作为阵列中传感器数量(小于或等于6)、所使用的聚合物传感器涂层以及被分析蒸汽的数量和浓度的函数的统计估计，结果表明，只有两个传感器可以识别阵列中具有5倍LOD的16种可能性中的单个蒸汽。在较低浓度下，至少需要三个传感器，但由3-6个传感器组成的阵列可提供类似的结果。分析还表明，个别蒸汽的识别更多地取决于蒸汽响应模式的相似性，而不是所考虑的可能蒸汽的总数。还分析了特定的2-、3-、4-、5-和B-蒸汽子集的蒸汽混合物，其中同时考虑了每个子集内的所有可能的蒸汽组合。使用与子集中的蒸汽相同数量的传感器，对最多四个蒸汽的混合物可以获得良好的识别率。通常观察到的混合物识别率较低：包括结构上相同的蒸气。显然，由于所考虑的大量蒸汽组合(即分别为31个和63个)，所检查的5个和6个蒸汽亚集无法获得可接受的识别率。重要的是，增加阵列中传感器的数量并没有显著提高任何混合物分析的性能，这表明对于SAW传感器和其他响应依赖于气相聚合物平衡分配的传感器来说，大阵列对于准确的气体识别和定量是非常必要的。
A comprehensive analysis of vapor recognition as a function of the number of sensors in a vapor-sensor array is presented. Responses to 16 organic vapors collected from Six polymer-coated surface acoustic wave (SAW) sensors were used in Monte Carlo simulations coupled with pattern recognition analyses to derive statistical estimates of vapor recognition rates as a function of the number of sensors in the array (less than or equal to 6), the polymer sensor coatings employed, and the number and concentration of vapors being analyzed, Results indicate that as few as two sensors can recognize individual vapors from a set of 16 possibilities with 5 x LOD for the array. At lower concentrations, a minimum of three sensors is required, but arrays of 3-6 sensors provide comparable results. Analyses also revealed that individual-vapor recognition hinges more on the similarity of the vapor response patterns than on the total number of possible vapors considered. Vapor mixtures were also analyzed for specific 2-, 3-, 4-, 5-, and B-vapor subsets where all possible combinations of vapors within each subset were considered simultaneously. Excellent recognition rates were obtainable for mixtures of up to four vapors using the same number of sensors as vapors in the subset. Lower recognition rates were generally observed for mixtures: that included structurally homologous vapors. Acceptable recognition rates could not be obtained for the 5- and 6-vapor subsets examined, due, apparently, to the large number of vapor combinations considered (i.e., 31 and 63, respectively). importantly, increasing the number of sensors tin the array did not improve performance significantly for any of the mixture analyses, suggesting that for SAW sensors and other sensors whose responses rely on-equilibrium vapor-polymer partitioning, large arrays are hot necessary for accurate vapor recognition and quantification.