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Published October 1, 1998 | public
Journal Article

Quantitative Study of the Resolving Power of Arrays of Carbon Black−Polymer Composites in Various Vapor-Sensing Tasks

Abstract

A statistical metric, based on the magnitude and standard deviations along linear projections of clustered array response data, was utilized to facilitate an evaluation of the performance of detector arrays in various vapor classification tasks. This approach allowed quantification of the ability of a 14-element array of carbon black−insulating polymer composite chemiresistors to distinguish between members of a set of 19 solvent vapors, some of which vary widely in chemical properties (e.g., methanol and benzene) and others of which are very similar (e.g., n-pentane and n-heptane). The data also facilitated evaluation of questions such as the optimal number of detectors required for a specific task, whether improved performance is obtained by increasing the number of detectors in a detector array, and how to assess statistically the diversity of a collection of detectors in order to understand more fully which properties are underrepresented in a particular set of array elements. In addition, the resolving power of arrays of carbon black−polymer composites was compared to the resolving power of specific collections of bulk conducting organic polymer or tin oxide detector arrays in a common set of vapor classification tasks.

Additional Information

© 1998 American Chemical Society. Received for review October 31, 1997. Accepted July 8, 1998. Publication Date (Web): August 26, 1998. We acknowledge Dr. Dawei Dong and Prof. Rod Goodman of Caltech for helpful suggestions regarding the manuscript. This work was supported by the National Aeronautics and Space Administration, the Army Research Office, and the Defense Advanced Research Projects Agency. B.J.D. acknowledges the Natural Science and Engineering Research Council of Canada for a 1967 Centennial Fellowship.

Additional details

Created:
August 19, 2023
Modified:
October 17, 2023