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Metadata

Name
"The current-voltage characteristics and partial pressure dependence of defect controlled electrochemical reactions on mixed conducting oxides"
Repository
ZENODO
Identifier
doi:10.5281/zenodo.5109587
Description
Oxygen exchange reaction rates on mixed conducting perovskite electrodes are described as a function of defect concentrations, see The current-voltage characteristics and partial pressure dependence of defect controlled electrochemical reactions on mixed conducting oxides for a detailed description.

Here, (exchange) currents, polarization resistances, \(p_{\rm{O_2}}\) dependencies and Tafel-slopes are calculated as function of&nbsp;\(p_{\rm{O_2}}\) and overpotential for different possible reaction mechnisms. The defect concentrations are taken from the model material La0.6Sr0.4FeO3-\(\delta\), and listed in Brouwer_Bias.csv as a function of&nbsp;\(p_{\rm{O_2}}\) and overpotential.

Model 7 describes a molecular mechanisms wothout adsorption limitation, model 8 includes adsorption limitation. Likewise Models 10 and 11 describe atomic mechanisms without and with adsorption limitation, respectively.

Overpotentials are listed in V, oxygen partial pressures in bar, defect concentrations in defects per unit cell and currents are in arbitrary units as are resistances.

Partial pressure and overpotential dependencies (p and n slopes) are given as \(\frac{\partial \ln j}{\partial\ln p_{\rm{O_2}}}\)(unitless) and \(\frac{\partial \ln j}{\partial\eta}\)(/V), and likewise with resistances instead of currents (rp and rn slopes), respectively.

The source code for this project is available at: https://github.com/AlexSchmid22191/EIS_R_Sim
Data or Study Types
multiple
Source Organization
Unknown
Access Conditions
available
Year
2021
Access Hyperlink
https://doi.org/10.5281/zenodo.5109587

Distributions

  • Encoding Format: HTML ; URL: https://doi.org/10.5281/zenodo.5109587
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.