G. Murgia

Bio: G. Murgia is an academic researcher from Center for Advanced Studies Research and Development in Sardinia. The author has contributed to research in topics: Electrolyte & Direct methanol fuel cell. The author has an hindex of 9, co-authored 13 publications receiving 499 citations. Previous affiliations of G. Murgia include Polaris Industries & University of Newcastle.

A Numerical Model of a Liquid-Feed Solid Polymer Electrolyte DMFC and Its Experimental Validation

Abstract: A one-dimensional, biphasic, multicomponent steady-state model based on phenomenological transport equations for the catalyst layer, diffusion layer, and polymeric electrolyte membrane has been developed for a liquid-feed solid polymer electrolyte direct methanol fuel cell (SPE- DMFC). The model employs three important requisites: (i) implementation of analytical treatment of nonlinear terms to obtain a faster numerical solution as also to render the iterative scheme easier to converge, (ii) an appropriate description of two-phase transport phenomena in the diffusive region of the cell to account for flooding and water condensation/evaporation effects, and (iii) treatment of polarization effects due to methanol crossover. An improved numerical solution has been achieved by coupling analytical integration of kinetics and transport equations in the reaction layer, which explicitly include the effect of concentration and pressure gradient on cell polarization within the bulk catalyst layer. In particular, the integrated kinetic treatment explicitly accounts for the nonhomogeneous porous structure of the catalyst layer and the diffusion of reactants within and between the pores in the cathode. At the anode, the analytical integration of electrode kinetics has been obtained within the assumption of macrohomogeneous electrode porous structure, because methanol transport in a liquid-feed SPE- DMFC is essentially a single-phase process because of the high miscibility of methanol with water and its higher concentration in relation to gaseous reactants. A simple empirical model accounts for the effect of capillary forces on liquid-phase saturation in the diffusion layer. Consequently, diffusive and convective flow equations, comprising Nernst-Plank relation for solutes, Darcy law for liquid water, and Stefan-Maxwell equation for gaseous species, have been modified to include the capillary flow contribution to transport. To understand fully the role of model parameters in simulating the performance of the DMCF, we have carried out its parametric study. An experimental validation of model has also been carried out. (C) 2003 The Electrochemical Society.

Molecular Dynamics Simulation of Penetrant Diffusion in Amorphous Polypropylene: Diffusion Mechanisms and Simulation Size Effects

Abstract: Amorphous, atactic polypropylene structures, consisting of 125, 729, and 2197 monomer repeat units folded into periodic cells, were generated to study the effects of simulation size on the transport of small molecules in simulations of amorphous polymers. The diffusion coefficients and solubilities of three particles having different sizes representative of He, Ar, and CO2 are calculated from 4 ns molecular dynamics simulations. A definite system size dependence is observed in the solubilities resulting from a bias against the formation of large cavities in the smaller structures. Surprisingly, this bias does not significantly affect the diffusivities of the penetrants in these structures despite their jumplike diffusive motion. We also find the characteristic length scale for the turnover from the anomalous to the diffusive regime to be insensitive to the simulation size but inversely dependent on penetrant size. This insensitivity to simulation size of the diffusivity and turnover is in contrast to that...

A Working Model of Polymer Electrolyte Fuel Cells Comparisons Between Theory and Experiments

Abstract: To describe the performance curves of a polymer electrolyte membrane fuel cell we present a Bernardi-Verbrugge-like model. The model contains an improved description of the cathode diffusion and reactive regions. This improvement was motivated by the need to correct the behavior of the Bernardi-Verbrugge model at high cell current densities, where concentration overpotentials and flooding phenomena start to appear. To achieve this goal, we derived a new expression for the overpotential of the cathode reactive region. The advantage of having such an expression is twofold: (i) elimination of strong nonlinearities in the solution scheme (with the result of having a fast and stable numerical code), and (ii) clear inclusion of concentration and flooding phenomena. Extensive applications of the model are presented. The comparison between the results of our simulations and experimental data show astonishingly good agreements.

Fundamental models for fuel cell engineering.

Abstract: 3.8.2. Temperature Distribution Measurements 4749 3.8.3. Two-Phase Visualization 4750 3.8.4. Experimental Validation 4751 3.9. Modeling the Catalyst Layer at Pore Level 4751 3.10. Summary and Outlook 4752 4. Direct Methanol Fuel Cells 4753 4.1. Technical Challenges 4754 4.1.1. Methanol Oxidation Kinetics 4754 4.1.2. Methanol Crossover 4755 4.1.3. Water Management 4755 4.1.4. Heat Management 4756 4.2. DMFC Modeling 4756 4.2.1. Needs for Modeling 4756 4.2.2. DMFC Models 4756 4.3. Experimental Diagnostics 4757 4.4. Model Validation 4758 4.5. Summary and Outlook 4760 5. Solid Oxide Fuel Cells 4760 5.1. SOFC Models 4761 5.2. Summary and Outlook 4762 6. Closing Remarks 4763 7. Acknowledgments 4763 8. References 4763

Modeling transport in polymer-electrolyte fuel cells.

Abstract: In this review, we have examined the different models for polymer-electrolyte fuel cells operating with hydrogen. The major focus has been on transport of the various species within the fuel cell. The different regions of the fuel cell were examined, and their modeling methodologies and equations were elucidated. In particular, the 1-D fuel-cell sandwich was discussed thoroughly because it is the most important part of the fuel-cell assembly. Models that included other effects such as temperature gradients and transport in other directions besides through the fuel-cell sandwich were also discussed. Models were not directly compared to each other; instead they were broken down into their constitutive parts. The reason for this is that validation of the models is usually accomplished by comparison of simulation to experimental polarization data (e.g., Figure 3). However, other data can also be used such as the net flux of water through the membrane. In fitting these data, the models vary not only in their complexity and treatments but also in their number and kind of fitting parameters. This is one reason it is hard to justify one approach over another by just looking at the modeling results. In general, it seems reasonable that the more complex models, which are based on physical arguments and do not contain many fitting parameters, are perhaps closest to reality. Of course, this assumes that they fit the experimental data and observations. This last point has been overlooked in the validation of many models. For example, a model may fit the data very well for certain operating conditions, but if it does not at least predict the correct trend when one of those conditions is changed, then the model is shown to be valid only within a certain operating range. This review has highlighted the important effects that should be modeled. These include two-phase flow of liquid water and gas in the fuel-cell sandwich, a robust membrane model that accounts for the different membrane transport modes, nonisothermal effects, especially in the directions perpendicular to the sandwich, and multidimensional effects such as changing gas composition along the channel, among others. For any model, a balance must be struck between the complexity required to describe the physical reality and the additional costs of such complexity. In other words, while more complex models more accurately describe the physics of the transport processes, they are more computationally costly and may have so many unknown parameters that their results are not as meaningful. Hopefully, this review has shown and broken down for the reader the vast complexities of transport within polymer-electrolyte fuel cells and the various ways they have been and can be modeled.