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
Table of Contents
1. Introduction: the role of modeling in PEMFC R&D, introduction to modeling methods2. 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
