Multiscale imaging and transport modeling for fuel cell electrodes
Source abstract
Abstract
Transport properties, performance, and durability of a proton exchange fuel cell (PEMFC) highly depend on microstructure and spatial distribution of components in the gas diffusion layer (GDL), microporous layer (MPL), and catalyst layers (CLs) of the fuel cell. Modeling of transport properties and understanding of these effects are challenging due to limited understanding of actual three-dimensional (3D) structure of the components, especially over a wide range of length scales. In this work, 3D imaging on multiple scales, namely electron tomography on a nanoscale, focused ion beam—scanning electron microscopy on a microscale, and 3D X-ray microscopy on a macroscale, was applied to obtain 3D reconstructions of the actual CL, MPL, and GDL microstructure. Direct numerical simulations on 3D data sets with an upscaling approach were applied to demonstrate the capability to simulate overall electrical conductivity of the system. Details of the process, challenges, and results are described.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Fuel Cells and Related Materials · Enhanced Oil Recovery Techniques · Machine Learning in Materials Science
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (40)
Show source-provided references
1. 10.1149/1.216043510.1149/1.2160435 ↗
2. Mathias · 2010
3. 10.1016/j.jpowsour.2012.06.09910.1016/j.jpowsour.2012.06.099 ↗
4. 10.1038/ncomms622910.1038/ncomms6229 ↗
5. Bird · 2007 · 77
6. 10.1016/B978-012078142-3/50005-710.1016/B978-012078142-3/50005-7 ↗
7. 10.1016/j.electacta.2007.04.02810.1016/j.electacta.2007.04.028 ↗
8. 10.1021/ac025586h10.1021/ac025586h ↗
9. 10.1016/j.jpowsour.2006.04.10610.1016/j.jpowsour.2006.04.106 ↗
10. Gregr · 2010
11. 10.1021/ar300110210.1021/ar3001102 ↗
12. Hoogers · 2003 · 88
13. 10.1016/j.jpowsour.2014.10.12710.1016/j.jpowsour.2014.10.127 ↗
14. 10.1016/S0008-6223(00)00239-610.1016/S0008-6223(00)00239-6 ↗
15. 10.1149/06917.0213ecst10.1149/06917.0213ecst ↗
16. Secanell · 2017
17. 10.1149/2.0751412jes10.1149/2.0751412jes ↗
18. 10.1016/j.jpowsour.2010.09.04410.1016/j.jpowsour.2010.09.044 ↗
19. 10.1016/j.jpowsour.2013.10.13810.1016/j.jpowsour.2013.10.138 ↗
20. 10.1016/j.ijhydene.2012.02.09910.1016/j.ijhydene.2012.02.099 ↗
21. 10.1016/j.jpowsour.2017.01.10410.1016/j.jpowsour.2017.01.104 ↗
22. 10.1002/fuce.20160000810.1002/fuce.201600008 ↗
23. 10.1016/j.matchar.2014.05.01410.1016/j.matchar.2014.05.014 ↗
24. 10.1002/adfm.20110152510.1002/adfm.201101525 ↗
25. 10.1149/05002.0353ecst10.1149/05002.0353ecst ↗
26. 10.1016/j.jpowsour.2016.07.10710.1016/j.jpowsour.2016.07.107 ↗
27. 10.1016/j.jpowsour.2016.07.03710.1016/j.jpowsour.2016.07.037 ↗
28. 10.2217/iim.12.1310.2217/iim.12.13 ↗
29. 10.1016/S0076-695X(08)60412-310.1016/S0076-695X(08)60412-3 ↗
30. 26. DigiM I2S AI image processing whitepaper (2018). Available at: http://www.digimsolution.com/documents/32/AI_image_processing_2017JUL29.pdf (accessed March 15, 2018).
31. 10.1149/07711.1453ecst10.1149/07711.1453ecst ↗
32. 10.1149/1.235619210.1149/1.2356192 ↗
33. 10.1016/S1359-0294(01)00084-X10.1016/S1359-0294(01)00084-X ↗
34. 31. DigiM I2S Software: Available at: http://www.digimsolution.com/services/image-simulation/.
35. Secanell Gallart · 2007
36. 10.1016/j.apcatb.2008.09.03010.1016/j.apcatb.2008.09.030 ↗
37. 10.1016/j.elecom.2004.02.00610.1016/j.elecom.2004.02.006 ↗
38. Analysis of the catalyst layer of polymer electrolyte fuel cells
39. 10.1155/2008/92795010.1155/2008/927950 ↗
40. 10.1016/j.jpowsour.2012.11.10610.1016/j.jpowsour.2012.11.106 ↗