Publications by authors named "Vincent P Schnee"

Semiconductor quantum dots (QDs) are bright fluorophores that have significant utility for imaging and sensing applications. Core QDs are often employed in chemosensing via redox processes that modulates their fluorescence in the presence of an analyte. However, such particles lack robust surface passivation and generally contain a sizable portion of nonfluorescent QDs, which is detrimental to the detection limit.

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The incorporation of organic polymeric materials into chemical sensors and electro-optic devices has the potential to greatly advance these fields. A major challenge to their incorporation is the fabrication of thin films due to their intolerance of thermal deposition methods and solvent compatibility challenges. Here, a method for contact printing of quantum dot (QD) and organic polymer (OP) composites for the production of thin-film chemical sensors is described.

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Sensors are the key element to enable smart electronics and will play an important role in the emerging big data era. In this work, we reported an experimental study and a data-analytical characterization method to enhance the precision of discriminating chemically and structurally similar gases. Graphene sensors were fabricated by conventional photolithography and measured with feature analysis against different chemicals.

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A cross-reactive array of semiselective chemiresistive sensors made of polymer-graphene nanoplatelet (GNP) composite coated electrodes was examined for detection and discrimination of chemical warfare agents (CWA). The arrays employ a set of chemically diverse polymers to generate a unique response signature for multiple CWA simulants and background interferents. The developed sensors' signal remains consistent after repeated exposures to multiple analytes for up to 5 days with a similar signal magnitude across different replicate sensors with the same polymer-GNP coating.

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A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis.

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A cross-reactive chemical sensing array was made from CdSe Quantum Dots (QDs) and five different organic polymers by inkjet printing to create segmented fluorescent composite regions on quartz substrates. The sensor array was challenged with exposures from two sets of analytes, including one set of 14 different functionalized benzenes and one set of 14 compounds related to security concerns, including the explosives trinitrotoluene (TNT) and ammonium nitrate. The array was broadly responsive to analytes with different chemical functionalities due to the multiple sensing mechanisms that altered the QDs' fluorescence.

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A fluorescent polymer sensor array (FPSA) was made from commercially available fluorescent polymers coated onto glass beads and was tested to assess the ability of the array to discriminate between different analytes in aqueous solution. The array was challenged with exposures to 17 different analytes, including the explosives trinitrotoluene (TNT), tetryl, and RDX, various explosive-related compounds (ERCs), and nonexplosive electron-withdrawing compounds (EWCs). The array exhibited a natural selectivity toward EWCs, while the non-electron-withdrawing explosive 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) produced no response.

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Changes in MEKC chemical selectivity that are induced by changes in the headgroup structure of cationic surfactants are examined. Separations of acidic, basic, and hydrophobic solutes are examined. The acidic analytes are comprised of methoxyphenols, which are of interest due to their prevalence in wood smoke.

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MEKC and the linear solvation energy relationship (LSER) model have been applied to two series of cationic surfactants. The synthetic flexibility of the quaternary ammonium group is exploited to generate the two series, one consisting of linear substitutions and the other incorporating the ammonium into ring structures of varying size. The effects of the head group structure on the CMC, aggregation number, and electrophoretic properties of the surfactants were determined.

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A phosphonium surfactant is introduced as a pseudostationary phase for MEKC and its performance and selectivity are compared to that of an analogous ammonium surfactant. The linear solvation energy relationship model has been applied to the two cationic surfactants, allowing the contributions of five chemical factors to the interactions between solutes and the micelles to be evaluated. Differences in the pseudophases cohesivity and acid/base interactions were observed.

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MEKC and linear solvation free energy relationships (LSFERs) have been used to characterize the solute distribution between water and self-assemblies formed from ionic liquid type mono-chain cationic surfactants containing a cyclic pyrrolidinium head group. Several features of the solvation environment afforded by these micellar solutions were found to be quite different from that of CTAB, a structurally analogous cationic surfactant with a conventional, acyclic quaternary ammonium head group. None of the LSFER coefficients were found to vary in any systematic way with increasing alkyl chain length for these unique surfactants.

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