The response and discrimination performance of an array that consisted of 20 different organothiol-capped Au nanoparticle chemiresistive vapor sensors was evaluated during exposure to 13 different organic vapors. The passivating organothiol ligand library consisted of collections of straight-chain alkanethiols, branched alkanethiols, and aromatic thiols. A fourth collection of sensors was formed from composites of 2-phenylethanethiol-capped Au nanoparticles and nonpolymeric aromatic materials that were coembedded in a sensor film. The organic vapors consisted of six hydrocarbons (n-hexane, n-heptane, n-octane, isooctane, cyclohexane, and toluene), three polar aprotic vapors (chloroform, tetrahydrofuran, and ethyl acetate), and four alcohols (methanol, ethanol, isopropanol, and 1-butanol). Trends in the resistance response of the sensors were consistent with expected trends in sorption due to the properties of the test vapor and the molecular structure of the passivating ligands in the sensor films. Classification algorithms including principal components analysis and Fisher’s linear discriminant were used to evaluate the discrimination performance of an array of such sensors. Each collection of sensors produced accurate classification of most vapors, with misclassification occurring primarily for vapors that had mutually similar polarity. The classification performance for an array that contained all of the sensor collections produced nearly perfect discrimination for all vapors studied. The dependence of the array size (i.e., the number of sensors) and the array chemical diversity on the discrimination performance indicated that, for an array of 20 sensors, an array size of 13 sensors or more produced the maximum discrimination performance
