Response and Discrimination Performance of Arrays of Organothiol-Capped Au Nanoparticle Chemiresistive Vapor Sensors

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

Response versus Chain Length of Alkanethiol-Capped Au Nanoparticle Chemiresistive Chemical Vapor Sensors

Au nanoparticles capped with a homologous series of straight chain alkanethiols (containing 4−11 carbons in length) have been investigated as chemiresistive organic vapor sensors. The series of alkanethiols was used to elucidate the mechanisms of vapor detection by such capped nanoparticle chemiresistive films and to highlight the molecular design principles that govern enhanced detection. The thiolated Au nanoparticle chemiresistors demonstrated rapid and reversible responses to a set of test vapors (n-hexane, n-heptane, n-octane, iso-octane, cyclohexane, toluene, ethyl acetate, methanol, ethanol, isopropanol, and 1-butanol) that possessed a variety of analyte physicochemical properties. The resistance sensitivity to nonpolar and aprotic polar vapors systematically increased as the chain length of the capping reagent increased. Decreases in the nanoparticle film resistances, which produced negative values of the differential resistance response, were observed upon exposure of the sensor films to alcohol vapors. The response signals became more negative with higher alcohol vapor concentrations, producing negative values of the sensor sensitivity. Sorption data measured on Au nanoparticle chemiresistor films using a quartz crystal microbalance allowed for the measurement of the partition coefficients of test vapors in the Au nanoparticle films. This measurement assumed that analyte sorption only occurred at the organic interface and not the surface of the Au core. Such an assumption produced partition coefficient values that were independent of the length of the ligand. Furthermore, the value of the partition coefficient was used to obtain the particle-to-particle interfacial effective dielectric constant of films upon exposure to analyte vapors. The values of the dielectric constant upon exposure to alcohol vapors suggested that the observed resistance response changes observed were not significantly influenced by this dielectric change, but rather were primarily influenced by morphological changes and by changes in the interparticle spacing

Extraction of spatiotemporal response information from sorption-based cross-reactive sensor arrays for the identification and quantification of analyte mixtures

Linear sensor arrays made from small molecule/carbon black composite chemiresistors placed in a low headspace volume chamber, with vapor delivered at low flow rates, allowed for the extraction of chemical information that significantly increased the ability of the sensor arrays to identify vapor mixture components and to quantify their concentrations. Each sensor sorbed vapors from the gas stream to various degrees. Similar to gas chromatography, species having high vapor pressures were separated from species having low vapor pressures. Instead of producing typical sensor responses representative of thermodynamic equilibrium between each sensor and an unchanging vapor phase, sensor responses varied depending on the position of the sensor in the chamber and the time from the beginning of the analyte exposure. This spatiotemporal (ST) array response provided information that was a function of time as well as of the position of the sensor in the chamber. The responses to pure analytes and to multi-component analyte mixtures comprised of hexane, decane, ethyl acetate, chlorobenzene, ethanol, and/or butanol, were recorded along each of the sensor arrays. Use of a non-negative least squares (NNLS) method for analysis of the ST data enabled the correct identification and quantification of the composition of 2-, 3-, 4- and 5-component mixtures from arrays using only 4 chemically different sorbent films and sensor training on pure vapors only. In contrast, when traditional time- and position-independent sensor response information was used, significant errors in mixture identification were observed. The ability to correctly identify and quantify constituent components of vapor mixtures through the use of such ST information significantly expands the capabilities of such broadly cross-reactive arrays of sensors

Use of Spatiotemporal Response Information from Sorption-Based Sensor Arrays to Identify and Quantify the Composition of Analyte Mixtures

Linear sensor arrays made from small molecule/carbon black composite chemiresistors placed in a low-headspace volume chamber, with vapor delivered at low flow rates, allowed for the extraction of new chemical information that significantly increased the ability of the sensor arrays to identify vapor mixture components and to quantify their concentrations. Each sensor sorbed vapors from the gas stream and, thereby, as in gas chromatography, separated species having high vapor pressures from species having low vapor pressures. Instead of producing only equilibrium-based sensor responses that were representative of the thermodynamic equilibrium partitioning of analyte between each sensor and the initial vapor phase, the sensor responses varied depending on the position of the sensor in the chamber and the time since the beginning of the analyte exposure. The concomitant spatiotemporal (ST) sensor array response therefore provided information that was a function of time, as well as of the position of the sensor in the chamber. The responses to pure analytes and to multicomponent analyte mixtures comprised of hexane, decane, ethyl acetate, chlorobenzene, ethanol, and/or butanol were recorded along each of the sensor arrays. Use of a non-negative least-squares (NNLS) method for analysis of the ST data enabled the correct identification and quantification of the composition of two-, three-, four-, and five-component mixtures from arrays using only four chemically different sorbent films. In contrast, when traditional time- and position-independent sensor response information was used, these same mixtures could not be identified or quantified robustly. The work has also demonstrated that, for ST data, NNLS yielded significantly better results than analyses using extended disjoint principal components modeling. The ability to correctly identify and quantify constituent components of vapor mixtures through the use of such ST information significantly expands the capabilities of such broadly cross-reactive arrays of sensors

Chemiresistors for Array-Based Vapor Sensing Using Composites of Carbon Black with Low Volatility Organic Molecules

Chemically sensitive resistors have been fabricated from composites of carbon black and low volatility, nonpolymeric, organic molecules such as propyl gallate, lauric acid, and dioctyl phthalate. Sorption of organic vapors into the nonconductive phase of such composites produced rapid and reversible changes in the relative differential resistance response of the sensing films. Arrays of these sensors, in which each sensing film was comprised of carbon black and a chemically distinct nonpolymeric organic molecule or blend of organic molecules, produced characteristic response patterns upon exposure to a series of different organic test vapors. The use of nonpolymeric sorption phases allowed fabrication of sensors having a high density of randomly oriented functional groups and provided excellent discrimination between analytes. By comparison to carbon black−polymer composite vapor sensors and sensor arrays, such sensors provided comparable detection limits as well as enhanced clustering and enhanced resolution ability between test analytes