Surface-modified Nafion (R) membrane by casting proton-conducting polyelectrolyte complexes for direct methanol fuel cells

Surface-modified Nafion (R) membrane was prepared by casting proton-conducting polyelectrolyte complexes on the surface of Nafion (R). The casting layer is homogeneous and its thickness is about 900 nm. The proton conductivity of modified Nafion (R) is slightly lower than that of plain Nafion (R); however, its methanol permeability is 41% lower than that of plain Nafion (R). The single cells with modified Nafion (R) exhibit higher open circuit voltage (OCV = 0.73 V) and maximal power density (P-max = 58 mW cm(-2)) than the single cells with plain Nafion (R) (OCV = 0.67 V, P x = 49 mW cm-2). It is a simple, efficient, cost-effective approach to modifying Nafion (R) by casting proton-conducting materials on the surface of Nafion (R).

Effects of casting solvents on the formation of inverted phase in block copolymer thin films

Previously, an inverted phase (the minority blocks comprising the continuum phase) was found in solution-cast block copolymer thin films. In this study, the effect of casting solvents on the formation of inverted phase has been studied. Two block copolymers, poly(styrene-b-butadiene) (SB) (M-w = 73 930 Da) and poly(styrene-b-butadiene-b-styrene) (SBS) (M-w = 140 000 Da), with comparable block lengths and equal polystyrene (PS) weight fraction (similar to30 wt %) were used. The copolymer thin films were cast from different solvents, toluene, benzene, cyclohexane, and binary mixtures of benzene and cyclohexane. Toluene and benzene are good solvents for both PS and PB, but have a preferential affinity for PS, while cyclohexane is a good solvent for PB but a Theta solvent for PS (T-Theta = 34.5 degreesC). The differential solvent affinity for PS and PB was estimated in terms of a difference between the polymer-solvent interaction parameter, chi, for each block. Under an extremely slow solvent evaporation rate, the time-dependent phase behavior during such a solution-to-film process was examined by freeze-drying the samples at different stages, corresponding to different copolymer concentrations, rho.

Flow injection electrochemical enzyme immunoassay based on the use of an immunoelectrode strip integrate immunosorbent layer and a screen-printed carbon electrode

A flow injection amperometric immunoassay system based on the use of screen-printed carbon electrode for the detection of mouse IgG was developed. An immunoelectrode strip, on which an immunosorbent layer and screen-printed carbon electrode were integrated, and a proposed flow cell have been fabricated. The characterization of the flow immunoassay system and parameters affecting the performance of the immunoassay system were studied and optimized. Amperometric detection at 0.0 V (versus Ag/AgCl) resulted in a linear detection range of 30-700 ng ml(-1), with a detection limit of 3 ng ml(-1). The signal variation among electrode strips prepared from variant batch did not exceed 8.5% (n = 7) by measuring 0.5 mug ml(-1) antigen standard solution.

Water soluble polyaniline and its blend films prepared by aqueous solution casting

Polyaniline (PAn) was doped with phosphonic acid containing hydrophilic tails. The solubility of the doped PAn in water was controlled by changing the length of hydrophilic chain in the dopant. When poly(ethylene glycol) monomethyl ether (PEGME) with molecular weight M-w = 550 was used as the hydrophilic chain of the dopant, the doped PAn was entirely soluble in water. The film cast from aqueous solution showed good electrochemical redox reversibility, Aqueous solution blending of PAn with poly(ethylene glycol) (PEG, M-w = 20 000) and poly(N-vinyl pyrrolidone) (PVP, M-w = 360 000) was achieved. Percolation threshold of the composite film was lower than 3 wt.%. Electrical conductivity of the composite film was in the range of 10(-1)-10(-5) S cm(-1), depending on molecular weight of the acid and the content of PAn in the composite. (C) 1999 Elsevier Science Ltd. All rights reserved.

Speaker Normalization Using Cortical Strip Maps: A Neural Model for Steady State Vowel Identification

Auditory signals of speech are speaker-dependent, but representations of language meaning are speaker-independent. Such a transformation enables speech to be understood from different speakers. A neural model is presented that performs speaker normalization to generate a pitchindependent representation of speech sounds, while also preserving information about speaker identity. This speaker-invariant representation is categorized into unitized speech items, which input to sequential working memories whose distributed patterns can be categorized, or chunked, into syllable and word representations. The proposed model fits into an emerging model of auditory streaming and speech categorization. The auditory streaming and speaker normalization parts of the model both use multiple strip representations and asymmetric competitive circuits, thereby suggesting that these two circuits arose from similar neural designs. The normalized speech items are rapidly categorized and stably remembered by Adaptive Resonance Theory circuits. Simulations use synthesized steady-state vowels from the Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)] vowel database and achieve accuracy rates similar to those achieved by human listeners. These results are compared to behavioral data and other speaker normalization models.

The numerical modelling of multi-physics phenomena: The shape casting process

In this paper a computer simulation tool capable of modelling multi-physics processes in complex geometry has been developed and applied to the casting process. The quest for high-quality complex casting components demanded by the aerospace and automobile industries, requires more precise numerical modelling techniques and one that need to be generic and modular in its approach to modelling multi-processes problems. For such a computer model to be successful in shape casting, the complete casting process needs to be addressed, the major events being:-• Filling of hot liquid metal into a cavity mould • Solidification and latent heat evolution of liquid metal • Convection currents generated in liquid metal by thermal gradients • Deformation of cast and stress development in solidified metal • Macroscopic porosity formation The above phenomena combines the analysis of fluid flow, heat transfer, change of phase and thermal stress development. None of these events can be treated in isolation as they inexorably interact with each other in a complex way. Also conditions such as design of running system, location of feeders and chills, moulding materials and types of boundary conditions can all affect on the final cast quality and must be appropriately represented in the model.

Multiphysics modeling and its application to the casting process

A modeling strategy is presented to solve the governing equations of fluid flow, temperature (with solidification), and stress in an integrated manner. These equations are discretized using finite volume methods on unstructured grids, which provide the capability to represent complex domains. Both the cell-centered and vertex-based forms of the finite volume discretization procedure are explained, and the overall integrated solution procedure using these techniques with suitable solvers is detailed. Two industrial processes, based on the casting of metals, are used to demonstrate the capabilities of the resultant modeling framework. This manufacturing process requires a high degree of coupling between the governing physical equations to accurately predict potential defects. Comparisons between model predictions and experimental observations are given.

Multiphysics modelling of the metals casting process

Metals casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena-heat conduction and solidification. However, to predict the formation of porosity (a factor of key importance in cast quality) requires the modelling of the interaction of the fluid flow, heat transfer, solidification and the development of stress-deformation in the solidified part of a component. In this paper, a model of the casting process is described which addresses all the main continuum phenomena involved in a coupled manner. The model is solved numerically using novel finite volume unstructured mesh techniques, and then applied to both the prediction of shape deformation (plus the subsequent formation of a gap at the metal-mould interface and its impact on the heat transfer behaviour) and porosity formation in solidifying metal components. Although the porosity prediction model is phenomenologically simplistic it is based on the interaction of the continuum phenomena and yields good comparisons with available experimental results. This work represents the first of the next generation of casting simulation tools to predict aspects of the structure of cast components.

Three-phase computations of the continuous casting process

In this paper, the continuous casting process for steel slab production is modelled using a mult-physics approach. For this purpose, a Finite Volume (FV) numerical model was constructed in 3D, with the following characteristics: Time dependent, turbulent fluid flow and heat transfer in the molten steel and flux regions, solidification of the skin layer, under prescribed heat loss boundary conditions, particle tracking simulation of argon bubbles injected with the metal into the mould, full coupling between bubbles and liquid through buoyancy and interfacial forces using a novel gas accumulation technique, and a full transient simulation of flux-metal interface behaviour under the influence of gravity and fluid inertial forces and bubble plume buoyancy. The unstructure mesh FV code PHYSICA developed at Greenwich was used for carry out the simulations with physical process data and properties supplied by IRSID SA.

Modeling of ingot development during the start-up phase of direct chill casting

Direct chill (DC) casting is a core primary process in the production of aluminum ingots. However, its operational optimization is still under investigation with regard to a number of features, one of which is the issue of curvature at the base of the ingot. Analysis of these features requires a computational model of the process that accounts for the fluid flow, heat transfer, solidification phase change, and thermomechanical analysis. This article describes an integrated approach to the modeling of all the preceding phenomena and their interactions.

Macro-segregation of multi-component alloys in shape casting simulation

The objective of this work is to present a new scheme for temperature-solute coupling in a solidification model, where the temperature and concentration fields simultaneously satisfy the macro-scale transport equations and, in the mushy region, meet the constraints imposed by the thermodynamics and the local scale processes. A step-by-step explanation of the macrosegregation algorithm, implemented in the finite volume unstructured mesh multi-physics modelling code PHYSICA, is initially presented and then the proposed scheme is validated against experimental results obtained by Krane for binary and a ternary alloys.