Gold nanoparticle films (Au(NPF)) functionalized with a range of hydrophobic and hydrophilic thiols were assembled in chemiresistor sensor arrays that were used to differentiate between complex mixtures of analytes in the aqueous phase. A chemiresistor array sampled a simple system of linear alcohols (methanol, ethanol, propan-1-ol, and butan-1-ol) dissolved in water over a range of concentrations. Discriminant analysis confirmed that the response patterns of the array could be used to successfully distinguish between the different alcohol solutions at concentrations above 20 mM for all of the alcohols except methanol, which was distinguished at concentrations above 200 mM. Alcohol solutions more dilute than these concentrations had response patterns that were not consistently recognizable and failed cross validation testing. This defined the approximate limit of discrimination for the system, which was close to the limits of detection for the majority of the individual sensors. Another Au(NPF) chemiresistor array was exposed to, and successfully identified crude oil, diesel, and three varieties of gasoline dissolved in artificial seawater at a fixed concentration. This work is a demonstration that the pattern of responses from an array of differently functionalized Au(NPF) sensors can be used to distinguish analytes in the aqueous phase.
Pt–Ru combinatorial libraries of potential fuel cell anode catalysts are formed by sequential sputter deposition through masks onto Si wafers. Scanning electrochemical microscopy (SECM) is employed for characterization of electrocatalytic activity. Aspects of using a scanning electrochemical microscope for characterization of an array of thin film fuel cell electrode materials are discussed. It is shown that in applying SECM to library characterization, careful attention must be paid to thin film annealing, specimen topography and tip degradation in order to realize meaningful results. Results from a Pt–Ru thin film library reveal the most active members near the 50 Pt/50 Ru composition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.