Research Papers

Solid Oxide Cell Microstructural Performance in Hydrogen and Carbon Monoxide Reactant Streams

[+] Author and Article Information
Zachary K. van Zandt

Department of Mechanical and
Aerospace Engineering,
University of Alabama in Huntsville,
301 Sparkman Drive,
Huntsville, AL 35899
e-mail: zkz0001@uah.edu

George J. Nelson

Department of Mechanical and
Aerospace Engineering,
University of Alabama in Huntsville,
301 Sparkman Drive,
Huntsville, AL 35899
e-mail: george.nelson@uah.edu

1Corresponding author.

Manuscript received November 20, 2015; final manuscript received June 20, 2016; published online August 1, 2016. Assoc. Editor: Jacob Bowen.

J. Electrochem. En. Conv. Stor. 13(1), 011009 (Aug 01, 2016) (11 pages) Paper No: JEECS-15-1010; doi: 10.1115/1.4034114 History: Received November 20, 2015; Revised June 20, 2016

A distributed charge transfer (DCT) model has been developed to analyze solid oxide fuel cells (SOFCs) and electrolyzers operating in H2–H2O and CO–CO2 atmospheres. The model couples mass transport based on the dusty-gas model (DGM), ion and electron transport in terms of charged species electrochemical potentials, and electrochemical reactions defined by Butler–Volmer kinetics. The model is validated by comparison to published experimental data, particularly cell polarization curves for both fuel cell and electrolyzer operation. Parametric studies have been performed to compare the effects of microstructure on the performance of SOFCs and solid oxide electrolysis cells (SOECs) operating in H2–H2O and CO–CO2 gas streams. Compared to the H2–H2O system, the power density of the CO–CO2 system shows a greater sensitivity to pore microstructure, characterized by the porosity and tortuosity. Analysis of the pore diameter concurs with the porosity and tortuosity parametric studies that CO–CO2 systems are more sensitive to microstructural changes than H2–H2O systems. However, the concentration losses of the CO–CO2 system are significantly higher than those of the H2–H2O system for the pore sizes analyzed. While both systems can be shown to improve in performance with higher porosity, lower tortuosity, and larger pore sizes, the results of these parametric studies imply that CO–CO2 systems would benefit more from such microstructural changes. These results further suggest that objectives for tailoring microstructure in solid oxide cells (SOCs) operating in CO–CO2 are distinct from objectives for more common H2-focused systems.

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Fig. 1

Basic structure of an SOC operating in fuel cell mode. The domain analyzed in the numerical SOC models is shown in comparison to a full SOC setup.

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Fig. 2

Model comparison to reversible SOC data presented by Ebbesen and Mogensen [18], the model prediction (solid lines) apply a base case tortuosity of 2.1. The shaded regions indicate estimates from sensitivity studies applied by varying the base case tortuosity by ±10% and by simulating operation under air and pure O2 as the cathode reactant.

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Fig. 3

Comparison of H2–H2O and CO–CO2 operations with variations in the porosity of the anode. The results show that CO–CO2 systems are dominated by concentration losses in the range of the study, while H2–H2O operations are more affected by ohmic losses.

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Fig. 4

Resultant power–current density curves from the variation of porosity in the anode. While the maximum power density is higher for H2–H2O for all the cases, the percentage increase in power density for CO–CO2 is considerably higher in comparison. This shows a higher sensitivity for the CO–CO2 system to changes in porosity.

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Fig. 5

Comparison of H2–H2O and CO–CO2 operations with variations in the pore diameter of the anode. The concentration and ohmic losses are similar to the porosity studies and show relatively minimal changes for the H2–H2O system as the pore diameter is increased.

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Fig. 6

Resultant power–current density curves from the variation of pore diameter in the anode. The overall increase in maximum power density for the CO–CO2 systems shows an even greater percentage change compared to the porosity studies.

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Fig. 7

Effective ionic conductivity as a function of the porosity of the fuel-side electrode

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Fig. 8

Calculated active area and ionic conductivity of the electrode for a given volume fraction of the ionic conductor

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Fig. 9

Effective diffusion coefficients calculated for Knudsen and binary diffusion using percolation theory. The secondary axis shows how the Knudsen number changes with respect to the porosity of the electrode.

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Fig. 10

Comparison of the effects of percolation theory when applied to H2–H2O and CO–CO2 atmospheres for SOFC/EC operations. The comparison is made at a high and low porosity to show the extreme variations due to percolation theory.

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Fig. 11

Catalytic effectiveness of hydrogen and carbon monoxide oxidation with respect to the first-order reaction approximation. The WGSR is included to show how other gas phase reactions may contribute to fuel consumption as a function of electrode microstructure.




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