Theoretical basis for identification and measurement of air contaminants using an array of sensors having partly overlapping selectivities

Abstract

The objective of this paper is to provide a theoretical basis for the selection and effective use of an array of chemical sensors for a particular application. The array is to be used in conjunction with a microprocessor in a small portable device capable of detecting, identifying and quantifying any of a large number N of hazardous compounds, either singly or in mixtures of up to A such compounds. A compact array of S different sensors is used, each of which can operate in M differently selective modes so as to yield P=MS parameters, or data channels. The minimum number of parameters required to identify the compounds solely on the basis of the presence or absence of significant signals in the various channels is determined by the inequality

For example, P ⩾ 18 or P ⩾ 22 for N = 100 and A = 3 or 4, respectively.

A computational approach is proposed to first eliminate all candidate compounds whose known response patterns do not overlap the channels exhibiting the strongest signals. The remaining candidate compounds are then quantified by solving simultaneous linear equations.

A determinant, which is used to solve the simultaneous equations, provides a measure of the selectivity and/or non-redundancy of the set of channels exhibiting the strongest signals. This determinant is also inversely proportional to the experimental error or to the required accuracy of the measurements. By computing the values of this determinant for various mixtures, the selectivities and/or non-redundancies of alternative sets of P parameters with respect to a given set of N hazardous compounds can be evaluated and compared.