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A Degradation Model for Solid Oxide Fuel Cell Anodes due to Impurities in Coal Syngas: Part I Theory and Validation
Author(s) -
Cayan F. N.,
Pakalapati S. R.,
Celik I.,
Xu C.,
Zondlo J.
Publication year - 2012
Publication title -
fuel cells
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.485
H-Index - 69
eISSN - 1615-6854
pISSN - 1615-6846
DOI - 10.1002/fuce.201100027
Subject(s) - anode , impurity , materials science , electrolyte , arsine , diffusion , syngas , oxide , hydrogen , chemical engineering , adsorption , analytical chemistry (journal) , solid oxide fuel cell , inorganic chemistry , chemistry , catalysis , thermodynamics , metallurgy , electrode , chromatography , organic chemistry , physics , phosphine , engineering
A new phenomenological one‐dimensional model is formulated to simulate the typical degradation patterns observed in solid oxide fuel cell (SOFC) anodes due to coal syngas contaminants such as arsenic (As) and phosphorous (P). The model includes gas phase diffusion and surface diffusion within the anode and the adsorption reactions on the surface of the Ni‐YSZ‐based anode. Model parameters such as reaction rate constants for the adsorption reactions are obtained through indirect calibration to match the degradation rates reported in the literature for arsine (AsH 3 ), phosphine (PH 3 ), hydrogen sulfide (H 2 S), and hydrogen selenide (H 2 Se) under accelerated testing conditions. Results from the model demonstrate that the deposition of the impurity on the Ni catalyst starts near the fuel channel/anode interface and slowly moves toward the active anode/electrolyte interface as observed in the experiments. Parametric studies performed at different impurity concentrations and operating temperatures show that the coverage rate increases with increasing temperature and impurity concentration, as expected. The calibrated model was then used for prediction of the performance curves at different impurity concentrations and operating temperatures. Good agreement is obtained between the predicted results and the experimental data reported in the literature.