Impact of catalyst layer morphology on the performance of PEM fuel cell cathode via lattice Boltzmann simulation

Molaeimanesh, Gholam Reza; Bamdezh, M.A.; Nazemian, M.

doi:10.1016/j.ijhydene.2018.09.076

Cited by 28 publications

(12 citation statements)

References 54 publications

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“…The main modeling assumptions are as follows [52,53]: • Knudsen effects were not taken into account to simplify the model, as in [54,55] Isothermal operation is a reasonable assumption for fuel cell simulation on a local scale where numerous studies report a maximum temperature difference of less than 3 K within an MEA [56][57][58]. This assumption is especially well-suited to our fractal flow-field model, due to the symmetry associated with the fractal design.…”

Section: Modeling Assumptionsmentioning

confidence: 99%

Optimizing the architecture of lung-inspired fuel cells

Cho

Marquis

Trogadas

et al. 2020

Chemical Engineering Science

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A finite-element model of a polymer electrolyte membrane fuel cell (PEMFC) with fractal branching, lung-inspired flow-field is presented. The effect of the number of branching generations N on the thickness of the gas diffusion layer (GDL) and fuel cell performance is determined. Introduction of a fractal flow-field to homogenize reactant concentration at the flow-field | GDL interface allows for the use of thinner GDLs. The model is coupled with an optimized cathode catalyst layer microstructure with respect to platinum utilization and power density, revealing that the 2020 DoE target of ~ 8 kW/gPt is met at N = 4 generations, and a platinum utilization of ~ 36 kW/gPt is achieved at N = 6 generations. In terms of the overall fuel cell stack architecture, our results indicate that either the platinum loading or the number of cells in the stack can be reduced by ~ 75%, the latter option of which, when combined with a 100 µm GDL, can lead to > 80% increase in the volumetric power density of the fuel cell stack.

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Section: Modeling Assumptionsmentioning

confidence: 99%

Optimizing the architecture of lung-inspired fuel cells

Cho

Marquis

Trogadas

et al. 2020

Chemical Engineering Science

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“…Governing equations Equations (1), (3), (13), (19) Equations (26)(27)(28)(29) Boundary conditions Equations (44)(45)(46)(47) Equations (32)(33)(34)(35) Unknown variables…”

Section: Gdl and Channel Catalyst Layermentioning

confidence: 99%

“…Molaeimanesh et al 28 investigated morphology impacts on the CL of PEM fuel cell. In their approach, the cathode modeling was done by a 3D lattice Boltzmann agglomerate network.…”

Section: Introductionmentioning

confidence: 99%

Nonisothermal two‐phase modeling of the effect of linear nonuniform catalyst layer on polymer electrolyte membrane fuel cell performance

Sabzpoushan

Mosleh

Kavian

et al. 2020

Energy Science & Engineering

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“…Molaeimanesh and Akbari [267] proposed a 2D LBM agglomerate model to simulate electrochemical reaction in the catalyst layer. Then, they developed a 3D LBM agglomerate model to study the species distributions, electrical potential distribution in the electrolyte film and current density distribution at the interface of the CL [266]. The agglomerates of carbon black particles are considered as ellipsoids which can have different level of stretching.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Progress in 3D electrode microstructure modelling for fuel cells and batteries: transport and electrochemical performance

Zhang¹,

Bertei²,

Tariq³

et al. 2019

Prog. Energy

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Electrode microstructure plays an important role in the performance of electrochemical energy devices including fuel cells and batteries. Building a clear understanding of how the performance is affected by the electrode microstructure is necessary to design the optimal electrode microstructure, to achieve better device performance. 3D microstructure modelling enables us to perform simulations directly on a 3D electrode microstructure and thus link structure with performance. This paper provides an extensive review on the current state of the art in 3D microstructure modelling of transport and electrochemical performance for four promising electrochemical energy technologies: solid oxide fuel cells (SOFCs), proton exchange membrane fuel cells (PEMFCs), redox flow batteries (RFBs) and lithium ion batteries (LIBs). Each technology has different electrode microstructures and processes, and thus presents different challenges. The most commonly used modelling methods including the finite element method (FEM) and the finite volume method (FVM) are reviewed, together with the developing lattice Boltzmann method (LBM), with the advantages and disadvantages of each method revealed. Whilst FEM and FVM have been extensively applied in simulating SOFC and LIB electrodes where the methods are capable of dealing with single phase (gas or liquid) transport, they face challenges in simulating the multiphase phenomenon present in PEMFC and some RFB electrodes. LBM is, on the other hand, well suited in simulating gas-liquid two phase flow and applications in PEMFCs and RFBs, as well as single-phase phenomenon in SOFCs and LIBs. The review also points to current challenges in 3D microstructure modelling, including the

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Impact of catalyst layer morphology on the performance of PEM fuel cell cathode via lattice Boltzmann simulation

Cited by 28 publications

References 54 publications

Optimizing the architecture of lung-inspired fuel cells

Optimizing the architecture of lung-inspired fuel cells

Nonisothermal two‐phase modeling of the effect of linear nonuniform catalyst layer on polymer electrolyte membrane fuel cell performance

Progress in 3D electrode microstructure modelling for fuel cells and batteries: transport and electrochemical performance

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