Speaker
Description
Proton exchange membranes (PEMs) has a crucial role in determining the fuel cell efficiency, durability, and performance of PEM fuel cells and water electrolysers. It governs proton transport while simultaneously acts as electronic insulators and gas separators. The current state of the art system employs composite membranes to enhance its efficiency manifold. Conventional macroscopic continuum models treat the membrane as a homogeneous medium with effective transport properties, enabling efficient computation but failing to capture localized variations arising from complex microstructures. At the other extreme, molecular- and atomistic-scale simulations provide detailed insight into proton transport mechanisms but are computationally prohibitive for device-scale analysis. In the detailed literature reported so far, there is lack of understanding in transport process through composite membranes which is simultaneously fast and effective to optimise the charge transfers. To bridge this gap, this work presents a multiscale homogenised transport model for porous composite PEM membranes, capable of capturing microstructural effects while remaining computationally tractable.
The proposed framework utilises a mesoscale, homogenisation-based approach, accounting the heterogeneous morphology of composite PEMs which is composed of hydrophilic ion-conducting water channels-hydrophobic polymer backbones. This is added with embedded inorganic or carbon-based additives. The membrane microstructure is embodied using a two-dimensional zonal arrangement where ion-impermeable hydrophobic regions co-occur with interconnected aqueous pathways which serve as proton transport channels. Additives are considered as charged obstacles within the proton conduction pathways, with their size, surface charge, spatial distribution, and orientation systematically incorporated into the model. Proton transport is described using a homogenised Nernst–Planck–Poisson formulation, in which diffusive and electromigrative fluxes dominate, while convective contributions are ignored under typical membrane operating conditions. Volume averaging is employed to upscale the governing equations from the microscale to the mesoscale, yielding effective transport equations that retain sensitivity to local geometry, interfacial area density, and surface charge effects. The homogenised Poisson equation captures electrostatic interactions arising from charged additives, while the homogenised Nernst–Planck equation resolves proton flux through the composite membrane structure. The model is used to predict effective proton conductivity under a range of structural and physicochemical conditions. Results for membranes without additives demonstrate that proton conductivity decreases with increasing segregation between hydrophilic and hydrophobic phases, highlighting the importance of percolated water channels. For composite membranes, the influence of additive arrangement (square, hexagonal, and cubic pitch), surface charge, and relative size with respect to hydrophobic domains is systematically analysed. Negatively charged additives are shown to significantly enhance proton conductivity by strengthening electromigration-driven flux, which constitutes the dominant contribution to overall transport. Furthermore, increasing additive size relative to the hydrophobic region leads to a pronounced increase in total proton flux, accompanied by only a marginal reduction in electric field strength, resulting in an overall enhancement of membrane conductivity.
Overall, the proposed multiscale homogenised model provides a robust and physically consistent framework for linking membrane microstructure to macroscopic proton transport performance. By balancing accuracy and computational efficiency, it offers a powerful tool for the rational design and optimisation of advanced composite proton exchange membranes for fuel cell and electrolyser applications.
| Country | India |
|---|---|
| Green Housing & Porous Media Focused Abstracts | This abstract is related to Green Housing |
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