Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 µM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (=3%) on the detection of either analyte. Nonimprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics. © 2009 American Chemical Society.

Whole-Vehicle modelling of exhaust energy recovery on a diesel-electric hybrid bus

Hybrid vehicles can use energy storage systems to disconnect the engine from the driving wheels of the vehicle. This enables the engine to be run closer to its optimum operating condition, but fuel energy is still wasted through the exhaust system as heat. The use of a turbogenerator on the exhaust line addresses this problem by capturing some of the otherwise wasted heat and converting it into useful electrical energy.

This paper outlines the work undertaken to model the engine of a diesel-electric hybrid bus, coupled with a hybrid powertrain model which analysed the performance of a hybrid vehicle over a drive-cycle. The distribution of the turbogenerator power was analysed along with the effect on the fuel consumption of the bus. This showed that including the turbogenerator produced a 2.4% reduction in fuel consumption over a typical drive-cycle.

The hybrid bus generator was then optimised to improve the performance of the combined vehicle/engine package and the turbogenerator was then shown to offer a 3.0% reduction in fuel consumption. The financial benefits of using the turbogenerator were also considered in terms of fuel savings for operators. For an average bus, a turbogenerator could reduce fuel costs by around £1200 per year.

Hybrid Polyoxovanadates: Anion-Influenced Formation of Nanoscopic Cages and Supramolecular Assemblies of Asymmetric Clusters

Organoarsonate-functionalized polyoxovanadates form upon the reduction of vanadates(V) in aqueous systems, whereby the underlying condensation reactions are influenced by the nature of the employed acid. In the presence of Cl− ions that derive from hydrochloric acid, a tetradecanuclear cage [VIV14O16(OH)8(O3AsC6H4-4-NH2)10]4– is obtained. When nitric acid is used, a condensed, decanuclear complex [V10O18(O3AsC6H4-4-NH2)7(DMF)2]5– forms. The latter organizes into a hexagonal packing arrangement in the solid state.

Self-assembly of hybrid organic–inorganic polyoxovanadates: functionalised mixed-valent clusters and molecular cages’

Herein we report the intra- and inter-molecular assembly of a {V5O9} subunit. This mixed-valent structural motif can be stabilised as [V5O9(L1–3)4]5−/9− (1–3) by a range of organoarsonate ligands (L1–L3) whose secondary functionalities influence its packing arrangement within the crystal structures. Variation of the reaction conditions results in the dodecanuclear cage structure [V12O14(OH)4(L1)10]4− (4) where two modified convex building units are linked via two dimeric {O4VIV(OH)2VIVO4} moieties. Bi-functional phosphonate ligands, L4–L6 allow the intramolecular connectivity of the {V5O9} subunit to give hybrid capsules [V10O18(L4–6)4]10− (5–7). The dimensions of the electrophilic cavities of the capsular entities are determined by the incorporated ligand type. Mass spectrometry experiments confirm the stability of the complexes in solution. We investigate and model the temperature-dependent magnetic properties of representative complexes 1, 4, 6 and 7 and provide preliminary cell-viability studies of three different cancer cell lines with respect to Na8H2[6]·36H2O and Na8H2[7]·2DMF·29H2O.

Hybrid Organic–Inorganic Polyoxometalates: Functionalization of VIV/ VV Nanosized Clusters to Produce Molecular Capsules

Functionalization of polyoxovanadate clusters using phosphonate and arsonate ligands results in molecular capsules (see structure; green V, purple P, red O, black C). Through the use of extended homologous ligands, these hybrid organic-inorganic capsules can be successively elongated into tubular molecules.

Homologous size-extension of hybrid vanadate capsules – solid state structures, solution stability and surface deposition

The dimensions and cavity sizes of the molecular capsules with the general formula [V₁₀O₁₈L₄]¹⁰⁻ can be controlled modularly through the nature of the bifunctional, rigid organophosphonate ligands L¹ and L² (L¹ = bis(4-phosphonatophenyl)ethyne and L² = bis(4-phosphonatophenyl)butadiyne); the solution stability of the molecular entities as demonstrated by ESI-MS studies permits their assembly on the Au(111) surface on a sub-monolayer scale giving rise to a 2D supramolecular structure that is comparable to the packing arrangements of the capsules in the crystal structures.

The Engine of Thought Is a Hybrid: Roles of Associative and Structured Knowledge in Reasoning

Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful.