Improvement of direct methanol fuel cell performance by modifying catalyst coated membrane structure

A five-layer catalyst coated membrane (CCM) based upon Nation 115 membrane for direct methanol fuel cell (DMFC) was designed and fabricated by introducing a modified Nafion layer between the membrane and the catalyst layer. The properties of the CCM were determined by SEM, cyclic voltammetry, impedance spectroscopy, ruinous test and I-V curves. The characterizations show that the modified Nation layers provide increased interface contact area and enhanced interaction between the membrane and the catalyst layer. As a result, higher Pt utilization, lower contact resistance and superior durability of membrane electrode assembly was achieved. A 75% Pt utilization efficiency was obtained by using the novel CCM structure, whereas the conventional structure gave 60% efficiency. All these features greatly contribute to the increase in DMFC performance. The DMFC with new CCM structure presented a maximum power density of 260 MW cm(-2), but the DMFC with conventional structure gave only 200 mW cm(-2) under the same operation condition. (c) 2005 Elsevier B.V. All rights reserved.

A novel PTFE-reinforced multilayer self-humidifying composite membrane for PEM fuel cells

A novel polytetrafluoroethylene (PTFE)-reinforced multilayer self-humidifying composite membrane is developed. The membrane is composed of Nafion-impregnated porous PTFE composite as the central layer and nanosized SiO2 supported Pt catalyst imbedded into Nafion as the two side layers. The proton exchange membrane (PEM) fuel cells employing the self-humidifying membrane (20 mu m thick) under dry H-2/O-2 gave a peak power density of 0.95 W/cm(2) and an open-circuit voltage of 1.032 V. The good membrane performance is attributed to hygroscopic Pt-SiO2 catalyst at the two side layers, which results in enhanced anode side self-humidification function and decreased cathode polarization. (c) 2005 The Electrochemical Society.

Investigation of LSM1.1-ScSZ composite cathodes for anode-supported solid oxide fuel cells

La0.8Sr0.2Mn1.1O3 (LSM1.1)-10 mol% Sc2O3-Stabilized ZrO2 co-doped with CeO2 (ScSZ) composite cathodes were investigated for anode-supported solid oxide fuel cells (SOFCs) with thin 8 mol% Y2O3-stabilized ZrO2 (YSZ) electrolyte. X-ray diffraction (XRD) results indicated that the ScSZ electrolytes displayed good chemical compatibility with the nonstoichiometric LSM1.1 against co-firing at 1300 degrees C. Increasing the CeO2 content in the ScSZ electrolytes dramatically suppressed the electrode polarization resistance, which may be related to the improved surface oxygen exchange or the enlarged active area of cathode. The 5Ce10ScZr was the best electrolyte for the composite cathodes, which caused a small ohmic resistance decrease and the reduced polarization resistance and brought about the highest cell performance. The cell performances at lower temperatures seemed to rely on the electrode polarization resistance more seriously, than the ohmic resistance. Compared with the cell impedance at higher temperatures, the higher the 5Ce10ScZr proportion in the composite cathodes, the smaller the increment of the charge transfer resistance at lower temperatures. The anode-supported SOFC with the LSM1.1-5Ce10ScZr (60:40) composite cathode achieved the maximum power densities of 0.82 W/cm(2) at 650 degrees C and 2.24 W/cm(2) at 800 degrees C, respectively. (c) 2005 Elsevier B.V. All rights reserved.

Thermodynamic properties of ethanol and gasoline blended fuel

The heat capacities (C-p) of five types of gasohol (50 wt % ethanol and 50 wt % unleaded gasoline 93(#) (E50), 60 wt % ethanol and 40 wt % unleaded gasoline 93(#) (E60), 70 wt % ethanol and 30 wt % unleaded gasoline 93(#) (E70), 80 wt % ethanol and 20 wt % unleaded gasoline 93(#) (E80), and 90 wt % ethanol and 10 wt % unleaded gasoline 93(#) (E90), where the "93" denotes the octane number) were measured by adiabatic calorimetry in the temperature range of 78-320 K. A glass transition was observed at 95.61, 96.14, 96.56, 96.84, and 97.08 K for samples from the E50, E60, E70, E80, and E90 systems, respectively. A liquid-solid phase transition and a solid-liquid phase transition were observed in the respective temperature ranges of 118-153 and 155-163 K for E50, 117-150 and 151-164 K for E60, 115-154 and 154-166 K for E70, 113-152 and 152-167 K for E80, and 112-151 and 1581-167 K for E90. The polynomial equations of Cp and the excess heat capacities (C-p(E)), with respect to the thermodynamic temperature, were established through least-squares fitting. Based on the thermodynamic relationship and the equations obtained, the thermodynamic functions and the excess thermodynamic functions of the five gasohol samples were derived.

Seeing the forest for the fuel

We demonstrate a new approach to understanding the role of fuelwood in the rural household economy by applying insights from travel cost modeling to author-compiled household survey data and meso-scale environmental statistics from Ruteng Park in Flores, Indonesia. We characterize Manggarai farming households' fuelwood collection trips as inputs into household production of the utility yielding service of cooking and heating. The number of trips taken by households depends on the shadow price of fuelwood collection or the travel cost, which is endogenous. Econometric analyses using truncated negative binomial regression models and correcting for endogeneity show that the Manggarai are 'economically rational' about fuelwood collection and access to the forests for fuelwood makes substantial contributions to household welfare. Increasing cost of forest access, wealth, use of alternative fuels, ownership of kerosene stoves, trees on farm, park staff activity, primary schools and roads, and overall development could all reduce dependence on collecting fuelwood from forests. © 2004 Cambridge University Press.

Air pollution, Fuel Usage and Health Outcomes in Madre de Dios, Peru: a Comparative Cross Sectional Study

Air pollution is a common problem. Particulate matter generated from air pollution has been tied to adverse health outcomes associated with cardiovascular disease. Biomass fuels are a specific contributor to increased particulate matter and arise as a result of indoor heating, cook stoves and indoor food preparation. This is a two part cross sectional study looking at communities in the Madre de Dios region. Survey data was collected from 9 communities along the Madre de Dios River. Individual level household PM2.5 was also collected as a means to generate average PM data stratified by fuel use. Data collection was affected by a number of outside factors, which resulted in a loss of data. Results from the cross-sectional study indicate that hypertension is not a significant source of morbidity. Obesity is prevalent and significantly associated with kitchen venting method indicating a potential relationship.

Upgrading automation for nuclear fuel in-core management: from the symbolic generation of configurations to the neural adaptation of heuristics

FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

The numerical simulation of enclosure fires using a Cfd fire field model coupled with a pyrolysis based solid fuel combustion submodel—a first approximation

In this paper, we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid cellulosic fuels. A simple solid fuel combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddy-dissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D. The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment. The model is shown to be able to qualitatively predict behaviors similar to "flashover"—in the case of the open room—and "backdraft"— in the case of the initially closed room.