Limits of Recognition for Binary and Ternary Vapor Mixtures Determined with Multitransducer Arrays

Abstract

The discrimination of simple vapor mixtures from their components with polymer-coated multitransducer (MT) arrays as a function of the absolute and relative concentrations of those components is explored. The data set consists of calibrated responses to 11 organic vapors from arrays of 5 or 8 microsensors culled from a group of 5 cantilever, 5 capacitor, and 5 calorimeter transducers coated with 1 of 5 different sorptive-polymer films. Monte Carlo methods are applied to simulate error-enhanced composite responses to all possible binary and ternary mixtures of the 11 vapors, and principal component regression models are established for estimating expected rates of recognition as a function of mixture composition. The limit of recognition (LOR), defined as the maximum recognizable mixture composition range, is used as the metric of performance. With the optimal 8-sensor MT array, 19 binary and 3 ternary mixtures could be identified (i.e., discriminated from their components) with <5% error. The binary-mixture LORs are shown to decrease with increases in the baseline noise levels and random sensitivity variations of the sensors, as well as the similarity of the vapors. Importantly, most of the binary LOR contours are significantly asymmetric with respect to composition, and none of the mixtures could be recognized with <5% error at component relative concentration ratios exceeding 20:1. Discrimination of ternary mixtures from their components and binary subcomponent mixtures is possible only if the relative concentration ratio between any two of the components is <5:1. In comparing binary LORs for the best five-sensor single-transducer (ST) array to those of the best five-sensor MT array, the latter were larger in nearly all cases. The implications of these results are considered in the context of using such arrays as detectors in microanalytical systems with upstream chromatographic modules.

Sensor Array Design for Complex Sensing Tasks

“…For example, Grate and colleagues (18,19,(48)(49)(50)(51) have reported extensively on the use of SAW and other sorption-based sensor arrays in detection of chemical vapors. Zellers and colleagues (52)(53)(54)(55) have reported microfabricated arrays of chemiresistor and hybrid arrays applied to binary and ternary chemical mixtures. Suslick and colleagues (56)(57)(58)(59)(60) have reported colorimetric sensor arrays applied to many complex chemical sensing problems.…”

CMOS Monolithic Nanoparticle-Coated Chemiresistor Array for Micro-Scale Gas Chromatography

“…Although individual volatile organic compounds (VOC) often can be differentiated from each other 1530-437X/$31.00 © 2012 IEEE on the basis of the response patterns from a stand-alone array, an upstream chromatographic separation stage is necessary to determine the components of mixtures of VOCs [20]. By presenting the array with time-resolved peaks corresponding to individual vapors, the problem of identifying and quantifying the components of a complex VOC mixture is reduce to a series of easier problems of determining smaller subsets of that mixture [21].…”

Electron-Beam Patterned Monolayer-Protected Gold Nanoparticle Interface Layers on a Chemiresistor Vapor Sensor Array

“…Error-enhanced response patterns for individual vapors or their binary mixtures (synthesized assuming additivity of responses) are then compared to stored library patterns using EDPCR to determine if the vapor or vapor mixture has been correctly recognized. Details of this methodology can be found elsewhere [37], [38].…”