QUANTITATIVE STUDY OF THE RESOLVING POWER OF ARRAYS OF CARBON BLACK-POLYMER COMPOSITES IN VARIOUS VAPOR-SENSING TASKS

A statistical metric, based on the magnitude and standard deviations a long linear projections of clustered away response data, was utilized to facilitate an evaluation of the performance of detector arrays in v arious vapor classification tasks. This approach allowed quantificatio n of the ability of a 14-element array of carbon black-insulating poly mer composite chemiresistors to distinguish between members of a set o f 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 q uestions such as the optimal number of detectors required for a specif ic task, whether improved performance is obtained by increasing the nu mber of detectors in a detector array, and how to assess statistically the diversity of a collection of detectors in order 40 understand mor e fully which properties are underrepresented in a particular set of a rray elements. In addition, the resolving power of arrays of carbon bl ack-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.