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Boosting Polymer Electrolyte Membrane Fuel Cells from Computational Modeling. Hydrogen Energy and Fuel Cells Primers

  • ID: 3947074
  • Book
  • 55 Pages
  • Elsevier Science and Technology
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Hydrogen Energy and Fuel Cell Primers is a series of concise books that present those coming into this broad and multidisciplinary field the most recent advances in each of its particular topics. Its volumes bring together information that has thus far been scattered in many different sources under one single title, which makes them a useful reference for industry professionals, researchers and graduate students, especially those starting in a new topic of research.

This volume, Boosting Polymer Electrolyte Membrane Fuel Cells from Computational Modeling, explores the use of multiscale computational modeling tools for the design and optimization of PEM fuel cells. Multiscale modeling is a rapidly emerging simulation approach which can potentially boost the R&D on PEMFCs through the development of an understanding of mechanisms and processes occurring at multiple spatio-temporal scales at multiple levels of materials, such as catalyst, catalyst support and ionomer. The book discusses concrete success stories on the application of this approach and their specific outcomes. It reviews the latest progresses in the field, including some contributions from the author himself. Special focus is given to multiscale modeling of degradation mechanisms and the durability prediction of the cells, as well as water transport and membrane degradation. Prior knowledge of electrochemistry and mathematics is assumed.

  • Explores the available tools for multiscale computational modelling applied to the design optimization of PEM fuel cells through
  • Discusses real world applications and the latest progresses in the field
  • Includes modelling of degradation mechanisms and durability prediction
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1. Introduction: the role of modeling in PEMFC R&D, introduction to modeling methods
2. Modeling methods for electrocatalysis and catalyst degradation
3. Modeling methods for processes in electrodes: water transport, charge transport, interplay with electrochemistry, degradation mechanisms
4. Modeling methods for complete cells (0D, 1D, 2D, 3D models)
5. Modeling methods for stacks and system-level
6. Conclusions, challenges and perspectives
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A. Franco, Alejandro
Alejandro A. Franco is Full Professor at the Laboratoire de Réactivité et Chimie des Solides (Université de Picardie Jules Verne -UPJV- and CNRS, Amiens), where he is involved in several teaching activities, including two lecture-series on "Fuel Cells” within the Erasmus Mundus Master on Materials for Energy Storage and Conversion (MESC) and on "Non-equilibrium thermodynamics” within the Doctoral School of UPJV. He headed the Modelling Group of Electrochemical Systems at CEA (Grenoble) in the period January 2006-January 2013. For almost 14 years, his research activities concerns understanding physico-electrochemical processes by means of multi-scale modelling approaches and numerical simulations, applied to electrochemical power generators such as Li-ion and Li-air batteries, supercapacitors, Polymer Electrolyte Fuel Cells (PEFCs) and Water Electrolyzers. He is the inventor of the MEMEPhys computational software and MS LIBER-T simulation package, scaling up ab initio and microstructural data at the electrochemical device level. He is author of several granted patents in the field of fuel cells and electrochemical devices, various publications in international peer-reviewed journals, book chapters, and oral presentations in international conferences. He has also organized international conferences and symposia, and edited international books on the topic of electrochemical energy conversion and storage and special issues of the journal Electrochimica Acta (2011 and 2013). He has delivered several invited tutorials on practical aspects of multi-scale modelling of electrochemical energy devices within the ISE, the american Electrochemical Society (ECS), and the European Centre for Atomic and Molecular Computing (CECAM).
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