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Polymers
Article . 2013 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Polymers
Article
License: CC BY
Data sources: UnpayWall
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Modeling and Simulation for Fuel Cell Polymer Electrolyte Membrane

Authors: Kei Morohoshi; Takahiro Hayashi;

Modeling and Simulation for Fuel Cell Polymer Electrolyte Membrane

Abstract

We have established methods to evaluate key properties that are needed to commercialize polyelectrolyte membranes for fuel cell electric vehicles such as water diffusion, gas permeability, and mechanical strength. These methods are based on coarse-graining models. For calculating water diffusion and gas permeability through the membranes, the dissipative particle dynamics–Monte Carlo approach was applied, while mechanical strength of the hydrated membrane was simulated by coarse-grained molecular dynamics. As a result of our systematic search and analysis, we can now grasp the direction necessary to improve water diffusion, gas permeability, and mechanical strength. For water diffusion, a map that reveals the relationship between many kinds of molecular structures and diffusion constants was obtained, in which the direction to enhance the diffusivity by improving membrane structure can be clearly seen. In order to achieve high mechanical strength, the molecular structure should be such that the hydrated membrane contains narrow water channels, but these might decrease the proton conductivity. Therefore, an optimal design of the polymer structure is needed, and the developed models reviewed here make it possible to optimize these molecular structures.

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Keywords

Monte Carlo method, fuel cell polyelectrolyte membrane, proton conductivity, Nafion, elastic modulus, polymer design, coarse-grained molecular dynamics, simulation modeling, gas permeability, dissipative particle dynamics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
gold
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