Gas Diffusion Layers in Fuel Cells and Electrolysers: A Novel Semi-Empirical Model to Predict Electrical Conductivity of Sintered Metal Fibres

Reza Omrani and Bahman Shabani
Additional contact information
Reza Omrani: School of Engineering, RMIT University, Bundoora East Campus, Melbourne 3083, Australia
Bahman Shabani: School of Engineering, RMIT University, Bundoora East Campus, Melbourne 3083, Australia

Energies, 2019, vol. 12, issue 5, 1-17

Abstract: This paper introduces novel empirical as well as modified models to predict the electrical conductivity of sintered metal fibres and closed-cell foams. These models provide a significant improvement over the existing models and reduce the maximum relative error from as high as just over 30% down to about 10%. Also, it is shown that these models provide a noticeable improvement for closed-cell metal foams. However, the estimation of electrical conductivity of open-cell metal foams was improved marginally over previous models. Sintered porous metals are widely used in electrochemical devices such as water electrolysers, unitised regenerative fuel cells (URFCs) as gas diffusion layers (GDLs), and batteries. Having a more accurate prediction of electrical conductivity based on variation by porosity helps in better modelling of such devices and hence achieving improved designs. The models presented in this paper are fitted to the experimental results in order to highlight the difference between the conductivity of sintered metal fibres and metal foams. It is shown that the critical porosity (maximum achievable porosity) can play an important role in sintered metal fibres to predict the electrical conductivity whereas its effect is not significant in open-cell metal foams. Based on the models, the electrical conductivity reaches zero value at 95% porosity rather than 100% for sintered metal fibres.

Keywords: porous metal; porosity; sintered metal fibre; metal foam; electrical conductivity; electrochemical; fuel cell (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/5/855/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/5/855/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:5:p:855-:d:211017

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().