Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Home
  • Home
EnglishFrançais
Journal of Materials Research Journal of Materials Research

Article contents

Multiscale imaging and transport modeling for fuel cell electrodes

Published online by Cambridge University Press:  01 February 2019

Jasna Jankovic [Opens in a new window] ,
Shawn Zhang ,
Andreas Putz ,
Madhu S. Saha  and
Darija Susac
Jasna Jankovic
Affiliation:
Materials Science and Engineering Department, University of Connecticut, Storrs, Connecticut 06269-3136, USA; and Research and Development Department, Automotive Fuel Cell Cooperation Corporation, Burnaby, British Columbia V5J3J8, Canada
Shawn Zhang
Affiliation:
Research and Development Department, DigiM Solution LLC, Burlington, Massachusetts 01803, USA
Andreas Putz
Affiliation:
Research and Development Department, MistyWest, Vancouver, British Columbia V5T2R5, Canada
Madhu S. Saha
Affiliation:
Materials Science and Engineering Department, University of Connecticut, Storrs, Connecticut 06269-3136, USA
Darija Susac
Affiliation:
Materials Science and Engineering Department, University of Connecticut, Storrs, Connecticut 06269-3136, USA
Corresponding
E-mail address:
jasna.jankovic@uconn.edu
Get access

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.

Keywords

microstructure simulation transmission electron microscopy (TEM)
Type
Invited Paper
Information
Journal of Materials Research , Volume 34 , Issue 4 , 28 February 2019 , pp. 579 - 591
Copyright
Copyright © Materials Research Society 2019 

Access options

Get access to the full version of this content by using one of the access options below.
If you should have access and can't see this content please contact technical support.

References

Kojima, K. and Fukazawa, K.: Current status and future outlook of fuel cell vehicle development in toyota. ECS Trans. 69, 231 (2015).CrossRefGoogle Scholar
Hoogers, G.: Fuel Cell Technology Handbook (CRC Press LLC, Boca Raton, London, New York, Washington, D.C., 2003); pp. 88–104.Google Scholar
Barbir, F.: PEM Fuel Cells: Theory and Practice, 2nd ed. (Academic Press, Cambridge, Massachusetts, 2005); pp. 73–112.CrossRefGoogle Scholar
More, K., Borup, R., and Reeves, K.: Identifying contributing degradation phenomena in PEM fuel cell membrane electrode assemblies via electron microscopy. ECS Trans. 3, 717 (2006).CrossRefGoogle Scholar
Lopez-Haro, M., Guétaz, L., Printemps, T., Morin, A., Escribano, S., Jouneau, P.H., Bayle-Guillemaud, P., Chandezon, F., and Gebel, G.: Three-dimensional analysis of Nafion layers in fuel cell electrodes. Nat. Commun. 5, 5229 (2014).CrossRefGoogle ScholarPubMed
Enz, S., Dao, T.A., Messerschmidt, M., and Scholta, J.: Investigation of degradation effects in polymer electrolyte fuel cells under automotive-related operating conditions. J. Power Sources 274, 521 (2015).CrossRefGoogle Scholar
Secanell, M., Jarauta, A., Kosakian, A., Sabharwal, M. and Zhou, J.: Encyclopedia of Sustainability Science and Technology, 2nd ed. (Springer-Verlag, New York, New York, 2017); ch. 37.Google Scholar
Weber, A.Z., Borup, R.L., Darling, R.M., Das, P.K., Dursch, T.J., Gu, W., Harvey, D., Kusoglu, A., Litster, S., Mench, M.M., Mukundan, R., Owejan, J.P., Pharoah, J., Secanell, M., and Zenyuk, I.V.: A Critical review of modeling transport phenomena in polymer-electrolyte fuel cells. J. Electrochem. Soc. 161, F1254 (2014).CrossRefGoogle Scholar
Secanell, M., Karan, K., Suleman, A., and Djilali, N.: Multi-variable optimization of PEMFC cathodes using an agglomerate model. Electrochim. Acta 52, 6318 (2007).CrossRefGoogle Scholar
Cetinbas, F.C., Advani, S.G., and Prasad, A.K.: Three dimensional proton exchange membrane fuel cell cathode model using a modified agglomerate approach based on discrete catalyst particles. J. Power Sources 250, 110 (2014).CrossRefGoogle Scholar
Epting, W.K. and Litster, S.: Effects of an agglomerate size distribution on the PEFC agglomerate model. Int. J. Hydrogen Energy 37, 8505 (2012).CrossRefGoogle Scholar
Cetinbas, F.C., Ahluwalia, R.K., Kariuki, N., De Andrade, V., Fongalland, D., Smith, L., Sharman, J., Ferreira, P., Rasouli, S., and Myers, D.J.: Hybrid approach combining multiple characterization techniques and simulations for microstructural analysis of proton exchange membrane fuel cell electrodes. J. Power Sources 344, 62 (2017).CrossRefGoogle Scholar
Thiele, S., Fürstenhaupt, T., Banham, D., Hutzenlaub, T., Birss, V., Ziegler, C., and Zengerle, R.: Multiscale tomography of nanoporous carbon-supported noble metal catalyst layers. J. Power Sources 228, 185 (2013).CrossRefGoogle Scholar
Sabharwal, M., Pant, L.M., Putz, A., Susac, D., Jankovic, J., and Secanell, M.: Analysis of catalyst layer microstructures: From imaging to performance. Fuel Cells 16, 734 (2016).CrossRefGoogle Scholar
Ziegler, C., Thiele, S., and Zengerle, R.: Direct three-dimensional reconstruction of a nanoporous catalyst layer for a polymer electrolyte fuel cell. J. Power Sources 196, 2094 (2011).CrossRefGoogle Scholar
Epting, W.K., Gelb, J., and Litster, S.: Resolving the three-dimensional microstructure of polymer electrolyte fuel cell electrodes using nanometer scale X-ray computed tomography. Adv. Funct. Mater. 22, 555 (2012).CrossRefGoogle Scholar
Jankovic, J., Susac, D., Soboleva, T., and Stumper, J.: Electron tomography based 3D reconstruction of fuel cell catalysts layers. ECS Trans. 50, 353 (2012).CrossRefGoogle Scholar
Leary, R., Midgley, P.A., and Thomas, J.M.: Recent advances in the application of electron tomography to materials chemistry. Acc. Chem. Res. 45, 1782 (2012).CrossRefGoogle ScholarPubMed
Boas, F.E. and Fleischmann, D.: CT artifacts: Causes and reduction techniques. Imaging Med. 4, 229 (2012).CrossRefGoogle Scholar
Salzer, M., Thiele, S., Zengerle, R., and Schmidt, V.: On the importance of FIB-SEM specific segmentation algorithms for porous media. Mater. Charact. 95, 36 (2014).CrossRefGoogle Scholar
Inoue, G., Yokoyama, K., Ooyama, J., Terao, T., Tokunaga, T., Kubo, N., and Kawase, M.: Theoretical examination of effective oxygen diffusion coefficient and electrical conductivity of polymer electrolyte fuel cell porous components. J. Power Sources 327, 610 (2016).CrossRefGoogle Scholar
Inoue, G. and Kawase, M.: Effect of porous structure of catalyst layer on effective oxygen diffusion coefficient in polymer electrolyte fuel cell. J. Power Sources 327, 1 (2016).CrossRefGoogle Scholar
Eikerling, M.: Water management in cathode catalyst layers of PEM fuel cells. J. Electrochem. Soc. 153, E58 (2006).CrossRefGoogle Scholar
Garboczi, E.J., Bentz, D.P., and Martys, N.S.: Digital images and computer modeling. Exp. Methods Phys. Sci. 35, 1 (1999).CrossRefGoogle Scholar
Oberbroeckling, K.J., Dunwoody, D.C., Minteer, A.S.D., and Leddy, J.: Density of Nafion exchanged with transition metal complexes and tetramethyl ammonium, ferrous, and hydrogen ions: commercial and recast films. Anal. Chem. 74, 4794 (2002).CrossRefGoogle ScholarPubMed
DigiM I2S AI image processing whitepaper (2018). Available at: http://www.digimsolution.com/documents/32/AI_image_processing_2017JUL29.pdf (accessed March 15, 2018).Google Scholar
Lezoray, O., Charrier, C., Cardot, H., and Lefevre, S., eds.: Machine learning in image processing. EURASIP J. Adv. Signal Process, December 2008, 927950 (2008).CrossRefGoogle Scholar
Shukla, S., Stanier, D., Saha, M.S., Zahiri, B., Tam, M., Stumper, J., and Secanell, M.: Characterization of inkjet printed electrodes with improved porosity. ECS Trans. 77, 1453 (2017).CrossRefGoogle Scholar
Bird, R.B., Warren, E. Stewart, and Lightfoot, E.N.: Transport Phenomena, 2nd ed. (John Wiley & Sons, Inc., New York, NY, 2007); pp. 77–83.Google Scholar
Blunt, M.J.: Flow in porous media pore-network models and multiphase flow. Curr. Opin. Colloid Interface Sci. 6, 197 (2001).CrossRefGoogle Scholar
DigiM I2S Software: Available at: http://www.digimsolution.com/services/image-simulation/.Google Scholar
Secanell Gallart, M.: Computational Modeling and Optimization of Proton Exchange Membrane Fuel Cells (Thesis, Victoria, 2007).Google Scholar
Pantea, D., Darmstadt, H., Kaliaguine, S., Sümmchen, L., and Roy, C.: Electrical conductivity of thermal carbon blacks: Influence of surface chemistry. Carbon 39, 1147 (2001).CrossRefGoogle Scholar
Antolini, E.: Carbon supports for low-temperature fuel cell catalysts. Appl. Catal., B 88, 1 (2009).CrossRefGoogle Scholar
Du, C.Y., Shi, P.F., Cheng, X.Q., and Yin, G.P.: Effective protonic and electronic conductivity of the catalyst layers in proton exchange membrane fuel cells. Electrochem. Commun. 6, 435 (2004).CrossRefGoogle Scholar
Suzuki, T., Murata, H., Hatanaka, T., and Morimoto, Y.: Analysis of the catalyst layer of polymer electrolyte fuel cells. R&D Rev. Toyota CRDL 39, 33–38 (2004).Google Scholar
Gregr, J. and Šafarova, V.: Electrical conductivity measurement of fibers and yarns. In 7th International Conference—TEXSCI 2010 (Czech Republic, 2010).Google Scholar
El-Kharouf, A., Mason, T.J., Brett, D.J.L., and Pollet, B.G.: Ex situ characterisation of gas diffusion layers for proton exchange membrane fuel cells. J. Power Sources 218, 393 (2012).CrossRefGoogle Scholar
Zhou, T. and Liu, H.: Effects of the electrical resistances of the GDL in a PEM fuel cell. J. Power Sources 161, 444 (2006).CrossRefGoogle Scholar
Mathias, M., Roth, J., Fleming, J. and Lehnert, W.: Handbook of Fuel Cells—Fundamentals, Technology and Applications (Wiley, New York, 2010); ch. 46.Google Scholar

Jankovic et al. supplementary material

Figure S1

File 932 KB

Full text views

Full text views reflects PDF downloads, PDFs sent to Google Drive, Dropbox and Kindle and HTML full text views.

Total number of HTML views: 30
Total number of PDF views: 187 *
View data table for this chart

* Views captured on Cambridge Core between 01st February 2019 - 19th January 2021. This data will be updated every 24 hours.

2 Cited by
Hostname: page-component-77fc7d77f9-qzt2x Total loading time: 0.198 Render date: 2021-01-19T07:06:37.724Z Query parameters: { "hasAccess": "0", "openAccess": "0", "isLogged": "0", "lang": "en" } Feature Flags last update: Tue Jan 19 2021 06:56:50 GMT+0000 (Coordinated Universal Time) Feature Flags: { "metrics": true, "metricsAbstractViews": false, "peerReview": true, "crossMark": true, "comments": true, "relatedCommentaries": true, "subject": true, "clr": true, "languageSwitch": true, "figures": false, "newCiteModal": false, "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true }

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Multiscale imaging and transport modeling for fuel cell electrodes
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Multiscale imaging and transport modeling for fuel cell electrodes
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Multiscale imaging and transport modeling for fuel cell electrodes
Available formats
×
×

Reply to: Submit a response

Your details

Conflicting interests

Do you have any conflicting interests? *