X-ray Micro-Computed Tomography of Polymer Electrolyte Fuel Cells: What is the Representative Elementary Area?
Source abstract
Abstract
With the growing use of X-ray computed tomography (X-ray CT) datasets for modelling of transport properties, comes the need to define the representative elementary volume (REV) if considering three dimensions or the representative elementary area (REA) if considering two dimensions. The resolution used for imaging must be suited to the features of interest in the sample and the region-of-interest must be sufficiently large to capture key information. Polymer electrolyte fuel cells have a hierarchical structure, with materials spanning multiple length scales. The work presented here examines the nature of the REA throughout a 25 cm2 membrane electrode assembly (MEA), focusing specifically on the micron length scale. Studies were carried out to investigate key structural (volume fraction, layer and penetration thickness, pore diameters) and transport (effective diffusivity) properties. Furthermore, the limiting current density of the nine regions was modelled. Stochastic heterogeneity throughout the sample results in local variations throughout. Finally, effects of resolution were probed by imaging using a range of optical magnifications (4× and 20×). The correlated and competing effects of voxel resolution and sampling size were found to cause difficulties where loss of clarity in the boundaries between phases occurs with larger imaging volumes.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Fuel Cells and Related Materials · Advancements in Solid Oxide Fuel Cells · Electrocatalysts for Energy Conversion
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (48)
Show source-provided references
1. Quantitative X-ray tomography10.1179/1743280413Y.0000000023 ↗
2. X-ray computed tomography in Zernike phase contrast mode at 8 keV with 50-nm resolution using Cu rotating anode X-ray source10.1524/zkri.2007.222.11.650 ↗
3. Failure analysis of fuel cell electrodes using three-dimensional multi-length scale X-ray computed tomography10.1016/j.jpowsour.2016.08.092 ↗
4. Pore network modeling to explore the effects of compression on multiphase transport in polymer electrolyte membrane fuel cell gas diffusion layers10.1016/j.jpowsour.2016.10.039 ↗
5. Developments in X-ray tomography characterization for electrochemical devices10.1016/j.mattod.2019.05.019 ↗
6. Effect of gas diffusion layer properties on water distribution across air-cooled, open-cathode polymer electrolyte fuel cells: a combined ex-situ X-ray tomography and in-operando neutron imaging study10.1016/j.electacta.2016.06.068 ↗
7. Examining the effect of the secondary flow-field on polymer electrolyte fuel cells using X-ray computed radiography and computational modelling10.1016/j.ijhydene.2018.11.038 ↗
8. X-ray nano computed tomography of electrospun fibrous mats as flow battery electrodes10.1002/ente.201800338 ↗
9. Multi-scale imaging of polymer electrolyte fuel cells using X-ray micro- and nano-computed tomography, transmission electron microscopy and helium-ion microscopy10.1002/fuce.201800047 ↗
10. A structure and durability comparison of membrane electrode assembly fabrication methods: self-assembled vs hot-pressed10.1149/2.0051806jes ↗
11. Investigation of hot pressed polymer electrolyte fuel cell assemblies via X-ray computed tomography10.1016/j.electacta.2017.05.028 ↗
12. Understanding water transport in polymer electrolyte fuel cells using coupled continuum and pore-network models10.1002/fuce.201500213 ↗
13. 3D visualization of membrane failures in fuel cells10.1016/j.jpowsour.2017.01.129 ↗
14. 4D in situ visualization of electrode morphology changes during accelerated degradation in fuel cells by X-ray computed tomography10.1016/j.jpowsour.2017.03.058 ↗
15. Effective diffusivity in partially-saturated carbon-fiber gas diffusion layers: effect of through-plane saturation distribution10.1016/j.ijheatmasstransfer.2015.02.073 ↗
16. Unstructured pore network modeling with heterogeneous PEMFC GDL porosity distributions10.1149/1.3486095 ↗
17. Characterization of transport phenomena in porous transport layers using X-ray microtomography10.1016/j.jpowsour.2017.03.153 ↗
18. Analysis of representative elementary volume and through-plane regional characteristics of carbon-fiber papers: diffusivity, permeability and electrical/thermal conductivity10.1016/j.ijheatmasstransfer.2018.07.030 ↗
19. Statistical representative elementary volumes of porous media determined using greyscale analysis of 3D tomograms10.1016/j.advwatres.2017.06.002 ↗
20. Morphological analyses of polymer electrolyte fuel cell electrodes with nano-scale computed tomography imaging10.1002/fuce.201300008 ↗
21. Reconstruction and effective transport properties of the catalyst layer in PEM fuel cells10.1149/1.3106136 ↗
22. Gas-diffusion-layer structural properties under compression via X-ray tomography10.1016/j.jpowsour.2016.08.020 ↗
23. TauFactor: an open-source application for calculating tortuosity factors from tomographic data10.1016/j.softx.2016.09.002 ↗
24. PoreSpy: a python toolkit for quantitative analysis of porous media images10.21105/joss.01296 ↗
25. Experimental measurement of effective diffusion coefficient of gas diffusion layer/microporous layer in PEM fuel cells10.1016/j.electacta.2011.12.110 ↗
26. Tuning MPL intrusion to increase oxygen transport in dry and partially saturated polymer electrolyte membrane fuel cell gas diffusion layers10.1149/2.0021907jes ↗
27. An analytical relationship for calculating the effective diffusivity of micro-porous layers10.1016/j.ijhydene.2015.06.067 ↗
28. Hydration and dehydration cycles in polymer electrolyte fuel cells operated with wet anode and dry cathode feed: a neutron imaging and modeling study10.1016/j.jpowsour.2017.03.155 ↗
29. Three-dimensional multiphase modeling of cold start processes in polymer electrolyte membrane fuel cells10.1016/j.electacta.2009.06.072 ↗
30. Oxygen transport resistance correlated to liquid water saturation in the gas diffusion layer of PEM fuel cells10.1016/j.ijheatmasstransfer.2013.12.059 ↗
31. Analysis of the role of the microporous layer in improving polymer electrolyte fuel cell performance10.1016/j.electacta.2018.02.100 ↗
32. Effects of an MPL on water and thermal management in a PEMFC10.1002/er.4262 ↗
33. Direct simulations of pore-scale water transport through diffusion media10.1149/2.0011907jes ↗
34. Understanding impacts of catalyst-layer thickness on fuel-cell performance via mathematical modeling10.1149/2.1161607jes ↗
35. Water transport mechanisms in PEMFC gas diffusion layers10.1149/1.3468615 ↗
36. Effective-diffusivity measurement of partially-saturated fuel-cell gas-diffusion layers10.1149/2.024211jes ↗
37. Effect of compression on liquid water transport and microstructure of PEMFC gas diffusion layers10.1016/j.jpowsour.2006.09.045 ↗
38. Capillary pressure and hydrophilic porosity in gas diffusion layers for polymer electrolyte fuel cells10.1016/j.jpowsour.2005.05.086 ↗
39. Pore-network modeling of liquid water transport in gas diffusion layer of a polymer electrolyte fuel cell10.1016/j.electacta.2007.06.061 ↗
40. Ex-situ characterisation of gas diffusion layers for proton exchange membrane fuel cells10.1016/j.jpowsour.2012.06.099 ↗
41. Ex-situ measurement of properties of gas diffusion layers of PEM fuel cells10.1016/j.egypro.2012.09.057 ↗
42. Pore Network Modeling and Synchrotron Imaging of Liquid Water in the Gas Diffusion Layer of Polymer Electrolyte Membrane Fuel Cells
43. Multi-scale structural analysis of gas diffusion layers10.1016/j.jpowsour.2017.03.086 ↗
44. Exploring the role of electrode microstructure on the performance of non-aqueous redox flow batteries10.1149/2.0611910jes ↗
45. Thermal conductivity in the three layered regions of micro porous layer coated porous transport layers for the PEM fuel cell10.1016/j.ijhydene.2015.07.169 ↗
46. The effect of non-uniform compression and flow-field arrangements on membrane electrode assemblies—X-ray computed tomography characterisation and effective parameter determination10.1016/j.jpowsour.2019.04.018 ↗
47. Representative resolution analysis for X-ray CT: a solid oxide fuel cell case study10.1016/j.cesx.2019.100043 ↗
48. The fractal nature of the three-phase boundary: a heuristic approach to the degradation of nanostructured solid oxide fuel cell anodes10.1016/j.nanoen.2017.06.028 ↗