Poly (vinyl alcohol) hydrogel membrane as electrolyte for direct borohydride fuel cells

A direct borohydride fuel cell (DBFC) employing a poly (vinyl alcohol)hydrogel membrane electrolyte (PHME) is reported. The DBFC employs an AB(5) Misch metal alloy as anode and a goldplated stainless steel mesh as cathode in conjunction with aqueous alkaline solution of sodium borohydride as fuel and aqueous acidified solution of hydrogen peroxide as oxidant. Room temperature performances of the PHME-based DBFC in respect of peak power outputs; ex-situ cross-over of oxidant, fuel,anolyte and catholyte across the membrane electrolytes; utilization efficiencies of fuel and oxidant, as also cell performance durability are compared with a similar DBFC employing a NafionA (R)-117 membrane electrolyte (NME). Peak power densities of similar to 30 and similar to 40 mW cm(-2) are observed for the DBFCs with PHME and NME, respectively. The crossover of NaBH4 across both the membranes has been found to be very low. The utilization efficiencies of NaBH4 and H2O2 are found to be similar to 24 and similar to 59%, respectively for the PHME-based DBFC; similar to 18 and similar to 62%, respectively for the NME-based DBFC. The PHME and NME-based DBFCs exhibit operational cell potentials of similar to 1 center dot 2 and similar to 1 center dot 4 V, respectively at a load current density of 10 mA cm(-2) for similar to 100 h.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

An improved-performance liquid-feed solid-polymer-electrolyte direct methanol fuel cell operating at near-ambient conditions

Results on the performance of a 25 cm(2) liquid-feed solid-polymer-electrolyte direct methanol fuel cell (SPE-DMFC), operating under near-ambient conditions, are reported. The SPE-DMFC can yield a maximum power density of c. 200 mW cm(-2) at 90 C while operating with 1 M aqueous methanol and oxygen under ambient pressure. While operating the SPE-DMFC under similar conditions with air, a maximum power density of ca. 100 mW cm(-2) is achieved. Analysis of the electrode reaction kinetics parameters on the methanol electrode suggests that the reaction mechanism for methanol oxidation remains invariant with temperature. Durability data on the SPE-DMFC at an operational current density of 100 mA cm(-2) have also been obtained.

Thermal Degradation Processes in Poly(xylylene sulfides) Investigated by Comparative Direct Pyrolysis MS and Flash Pyrolysis GC/MS Experiments

The thermal degradation processes of two sulfur polymers, poly(xylylene sulfide) (PXM) and poly(xylylene disulfide) (PXD), were investigated in parallel by direct pyrolysis mass spectrometry (DPMS) and flash pyrolysis GC/MS (Py-GC/MS). Thermogravimetric data showed that these polymers decompose with two separate steps in the temperature ranges of 250-280 and 600-650 degrees C, leaving a high amount of residue (about 50% at 800 degrees C). The pyrolysis products detected by DPMS in the first degradation step of PXM and PXD were terminated by three types of end groups, -CH3, -CH2SH, and -CH=S, originating from thermal cleavage reactions involving a series of homolytic chain scissions followed by hydrogen transfer reactions, generating several oligomers containing some intact xylylene sulfide repeating units. The presence of pyrolysis compounds containing some stilbene-like units in the first degradation step has also been observed. Their formation has been accounted for with a parallel cleavage involving the elimination of H2S from the PXM main chains. These unsaturated units can undergo cross-linking at higher temperatures, producing the high amount of char residue observed. The thermal degradation compounds detected by DPMS in the second decomposition step at about 600-650 degrees C were constituted of condensed aromatic molecules containing dihydrofenanthrene and fenanthrene units. These compounds might be generated from the polymer chains containing stilbene units, by isomerization and dehydrogenation reactions. The pyrolysis products obtained in the Py-GC/MS of PXM and PXD at 610 degrees C are almost identical. The relative abundance in the pyrolysate and the spectral properties of the main pyrolysis products were found to be in generally good agreement with those obtained by DPMS. Polycyclic aromatic hydrocarbons (PAHs) were also detected by Py-GC/MS but in minor amounts with respect to DPMS. This apparent discrepancy was due to the simultaneous detection of PAHs together with all pyrolysis products in the Py-GC/MS, whereas in DPMS they were detected in the second thermal degradation step without the greatest part of pyrolysis compounds generated in the first degradation step. The results obtained by DPMS and PSI-GC/MS experiments showed complementary data for the degradation of PXM and PXD and, therefore, allowed the unequivocal formulation of the thermal degradation mechanism for these sulfur-containing polymers.

Solution of a System of Generalized Abel Integral Equations Using Fractional Calculus

A method is presented for obtaining useful closed form solution of a system of generalized Abel integral equations by using the ideas of fractional integral operators and their applications. This system appears in solving certain mixed boundary value problems arising in the classical theory of elasticity.

A direct adaptive neural command controller design for an unstable helicopter

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).

Satellite-derived direct radiative effect of aerosols dependent on cloud cover

Aerosols from biomass burning can alter the radiative balance of the Earth by reflecting and absorbing solar radiation(1). Whether aerosols exert a net cooling or a net warming effect will depend on the aerosol type and the albedo of the underlying surface(2). Here, we use a satellite-based approach to quantify the direct, top-of-atmosphere radiative effect of aerosol layers advected over the partly cloudy boundary layer of the southeastern Atlantic Ocean during July-October of 2006 and 2007. We show that the warming effect of aerosols increases with underlying cloud coverage. This relationship is nearly linear, making it possible to define a critical cloud fraction at which the aerosols switch from exerting a net cooling to a net warming effect. For this region and time period, the critical cloud fraction is about 0.4, and is strongly sensitive to the amount of solar radiation the aerosols absorb and the albedo of the underlying clouds. We estimate that the regional-mean warming effect of aerosols is three times higher when large-scale spatial covariation between cloud cover and aerosols is taken into account. These results demonstrate the importance of cloud prediction for the accurate quantification of aerosol direct effects.

Pt metal-CeO2 interaction: Direct observation of redox coupling between Pt-0/Pt2+/Pt4+ and Ce4+/Ce3+ states in Ce0.98Pt0.02O2-delta catalyst by a combined electrochemical and x-ray photoelectron spectroscopy study

Pt ions-CeO2 interaction in Ce1-xPtxO2-delta (x=0.02) has been studied for the first time by electrochemical method combined with x-ray diffraction and x-ray photoelectron spectroscopy. Working electrodes made of CeO2 and Ce0.98Pt0.02O2-delta mixed with 30% carbon are treated electrochemically between 0.0-1.2 V in potentiostatic (chronoamperometry) and potentiodynamic (cyclic voltametry) mode with reference to saturated calomel electrode. Reversible oxidation of Pt-0 to Pt2+ and Pt4+ state due to the applied positive potential is coupled to simultaneous reversible reduction of Ce4+ to Ce3+ state. CeO2 reduces to CeO2-y (y=0.35) after applying 1.2 V, which is not reversible; Ce0.98Pt0.02O2-delta reaches a steady state with Pt2+:Pt4+ in the ratio of 0.60:0.40 and Ce4+:Ce3+ in the ratio of 0.55:0.45 giving a composition Ce0.98Pt0.02O1.74 at 1.2 V, which is reversible. Composition of Pt ion substituted compound is reversible between Ce0.98Pt0.02O1.95 to Ce0.98Pt0.02O1.74 within the potential range of 0.0-1.2 V. Thus, Ce0.98Pt0.02O2-delta forms a stable electrode for oxidation of H2O to O-2 unlike CeO2. A linear relation between oxidation of Pt2+ to Pt4+ with simultaneous reduction in Ce4+ to Ce3+ is observed demonstrating Pt-CeO2 metal support interaction is due to reversible Pt-0/Pt2+/Pt4+ interaction with Ce4+/Ce3+ redox couple.

Effects of mass of charge on loop heat pipe operational characteristics

Experimental results on a loop heat pipe, using R134a as the working fluid, indicates that the liquid inventory in the compensation chamber can significantly influence the operating characteristics. The large liquid inventory in the compensation chamber, under terrestrial conditions, can result in loss of thermal coupling between the compensation chamber and the evaporator core. This causes the operating temperature to increase monotonically. This phenomenon, which has been experimentally observed, is reported in this paper. A theoretical model to predict the steady-state performance of a loop heat pipe with a weak thermal link between the compensation chamber and the core, as observed in the experiment, is also presented. The predicted and the experimentally determined temperatures correlate well.

Direct precipitation of lead zirconate titanate by the hydrothermal method

Direct precipitation of fine powders of lead zirconate titanate (PZT) in the complete range of solid solution, is investigated under hydrothermal conditions, starting from lead oxide and titania/zirconia mixed gels. The perovskite phase is formed in the temperature range of 165 – 340°C. Sequence of the hydrothermal reactions is studied by identifying the intermediate phases. The initial formation of PbO: TiO2 solid solution is followed by the reaction of the same with the remaining mixed gels giving rise to X-ray amorphous PZT phase. Further, through crystallite growth, the X-ray crystalline PZT is formed. This method can be extended for the preparation of PLZT powder as well. The resulting powders are sinterable to high density ceramics.

A simple circuit to aid direct measurement of capture cross sections of deep level impurities

An inexpensive and simple circuit to aid the direct measurement of majority carrier capture cross sections of impurity levels in the band gap of a semiconductor by the variable width filling pulse technique is presented. With proper synchronisation, during the period of application of the pulse, the device is disconnected from the capacitance meter to avoid distortion of the pulse and is reconnected again to the meter to record the emission transient. Modes of operation include manual triggering for long emission transients, repetitive triggering for isothermal and DLTS measurements and the DLTS mode which is to be used with signal analysers that already provide a synchronising pulse for disconnection.

On the direct parallel solution of systems of linear equations: New algorithms and systolic structures

The paper presents two new algorithms for the direct parallel solution of systems of linear equations. The algorithms employ a novel recursive doubling technique to obtain solutions to an nth-order system in n steps with no more than 2n(n −1) processors. Comparing their performance with the Gaussian elimination algorithm (GE), we show that they are almost 100% faster than the latter. This speedup is achieved by dispensing with all the computation involved in the back-substitution phase of GE. It is also shown that the new algorithms exhibit error characteristics which are superior to GE. An n(n + 1) systolic array structure is proposed for the implementation of the new algorithms. We show that complete solutions can be obtained, through these single-phase solution methods, in 5n−log2n−4 computational steps, without the need for intermediate I/O operations.

Determination of chemical shift anisotropy without a reference and of direct and indirect spin-spin couplings between heteronuclei

A method employing two liquid crystals of opposite diamagnetic anisotropies to determine chemical shift anisotropy without using any reference compound is described. It also provides individual values of the direct and the indirect spin-spin coupling constants between heteronuclei. The parameters for acetonitrile are reported.

New temperature fluctuation method for direct determination of thermal activation energy of deep levels in semiconductors

A new method is suggested where the thermal activation energy is measured directly and not as a slope of an Arrhenius plot. The sample temperature T is allowed to fluctuate about a temperature T0. The reverse-biased sample diode is repeatedly pulsed towards zero bias and the transient capacitance C1 at time t1 is measured The activation energy is obtained by monitoring the fluctuations in C1 and T. The method has been used to measure the activation energy of the gold acceptor level in silicon.