A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-δ as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results.

A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-delta as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results. (C) 2013 The Electrochemical Society. All rights reserved.

Effect of substrate surface roughening and cold spray coating on the fatigue life of AA2024 specimens

The effects of cold spray coating and substrate surface preparation on crack initiation under cyclic loading have been studied on Al2024 alloy specimens. Commercially pure (CP) aluminum feedstock powder has been deposited on Al2024-T351 samples using a cold-spray coating technique known as high velocity particle consolidation. Substrate specimens were prepared by surface grit blasting or shot peening prior to coating. The fatigue behavior of both coated and uncoated specimens was then tested under rotating bend conditions at two stress levels, 180 MPa and 210 MPa. Scanning electron microscopy was used to analyze failure surfaces and identify failure mechanisms. The results indicate that the fatigue strength was significantly improved on average, up to 50% at 180 MPa and up to 38% at 210 MPa, by the deposition of the cold-sprayed CP-Al coatings. Coated specimens first prepared by glass bead grit blasting experienced the largest average increase in fatigue life over bare specimens. The results display a strong dependency of the fatigue strength on the surface preparation and cold spray parameters