journal article·2020Open access

Enhancing the Performance of Fuel Cell Gas Diffusion Layers Using Ordered Microstructural Design

Daniel Niblett, Vahid Niasar, Stuart Holmes

Abstract

The Gas Diffusion Layer (GDL) is an important fibrous porous material within all fuel cells that manage the transport of electrons, heat and fluids in order to generate power. The microstructural morphology of electrically conductive solid porous media can be manipulated to produce structures with a larger effective electrical conductivity and reactant permeability when compared to current Gas Diffusion Layers (GDL) used in fuel cells. Using a numerical modelling approach, we simulated single phase flow and the electrical conductance in void and solid spaces, respectively. The simulations were completed in OpenFOAM which employs the finite volume approach. Simulations revealed that effective electrical conductivity is dependent on the electron path tortuosity τ E and the porosity . Therefore control of these micro-structural properties will allow for lower ohmic and mass transport losses. To aid the analysis, analytical and semi-empirical equations were developed based upon physical parameters to predict the effective electrical conductivity of connected porous media independent of isotropy. We propose that regular ordered structures via additive manufacturing techniques will allow for greater fuel cell performance.
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Research context

OpenAlex topics: Fuel Cells and Related Materials · Electrocatalysts for Energy Conversion · Advancements in Solid Oxide Fuel Cells

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (28)

Show source-provided references
1. 10.1149/2.1141409jes10.1149/2.1141409jes ↗
2. Tjaden B. Cooper S. J. Brett D. J. Kramer D. Shearing P. R. , “On the origin and application of the bruggeman correlation for analysing transport phenomena in electrochemical systems,” Current Opinion in Chemical Engineering (2016).10.1016/j.coche.2016.02.006 ↗
3. 10.1016/j.apenergy.2011.08.03710.1016/j.apenergy.2011.08.037 ↗
4. 10.1002/adma.20150355710.1002/adma.201503557 ↗
5. 10.1364/OME.3.00087510.1364/OME.3.000875 ↗
6. 10.1016/j.ijhydene.2016.08.17910.1016/j.ijhydene.2016.08.179 ↗
7. 10.1016/j.ijheatmasstransfer.2018.07.03010.1016/j.ijheatmasstransfer.2018.07.030 ↗
8. A mathematical model for performance of proton exchange membrane fuel cell as a nonlinear voltage processes
9. 10.1002/er.392710.1002/er.3927 ↗
10. 10.1016/j.apenergy.2012.02.00310.1016/j.apenergy.2012.02.003 ↗
11. 10.1016/j.apenergy.2013.02.03110.1016/j.apenergy.2013.02.031 ↗
12. 10.1002/er.376310.1002/er.3763 ↗
13. 10.1016/j.electacta.2015.11.07410.1016/j.electacta.2015.11.074 ↗
14. 10.1016/j.ijheatmasstransfer.2017.07.10210.1016/j.ijheatmasstransfer.2017.07.102 ↗
15. 10.1016/j.jpowsour.2006.06.09610.1016/j.jpowsour.2006.06.096 ↗
16. 10.1002/adma.1997009060410.1002/adma.19970090604 ↗
17. 10.1016/j.ijhydene.2015.12.11110.1016/j.ijhydene.2015.12.111 ↗
18. 10.3390/ma1007079610.3390/ma10070796 ↗
19. 10.1063/1.161163110.1063/1.1611631 ↗
20. 10.1103/PhysRevE.72.05631910.1103/PhysRevE.72.056319 ↗
21. 10.1016/j.cma.2006.08.00610.1016/j.cma.2006.08.006 ↗
22. 10.1016/j.jpowsour.2013.06.16610.1016/j.jpowsour.2013.06.166 ↗
23. 10.1149/1.247254710.1149/1.2472547 ↗
24. 10.1016/j.ijhydene.2011.12.05010.1016/j.ijhydene.2011.12.050 ↗
25. 10.1016/j.rser.2016.11.23510.1016/j.rser.2016.11.235 ↗
26. 10.1016/j.jpowsour.2012.06.09910.1016/j.jpowsour.2012.06.099 ↗
27. 10.1149/1.317687610.1149/1.3176876 ↗
28. 10.1007/s11242-015-0458-010.1007/s11242-015-0458-0 ↗