A method for measuring relative in-plane diffusivity of thin and partially saturated porous media: An application to fuel cell gas diffusion layers

Tranter, Thomas G.; Stogornyuk, Pavel; Gostick, Jeff T.; Burns, A. D.; Gale, William F.

doi:10.1016/j.ijheatmasstransfer.2017.02.096

Cited by 20 publications

(23 citation statements)

References 45 publications

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“…These values also match well with the studies of TP diffusion Hwang and Weber ( 2012 ) and IP diffusion Tranter et al. ( 2017 ), Rashapov et al. ( 2015a ) and Rashapov and Gostick ( 2016 ).…”

Section: Methodssupporting

confidence: 90%

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Capillary Hysteresis in Neutrally Wettable Fibrous Media: A Pore Network Study of a Fuel Cell Electrode

Tranter¹,

Gostick²,

Burns

et al. 2017

Transp Porous Med

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Hysteresis in the saturation versus capillary pressure curves of neutrally wettable fibrous media was simulated with a random pore network model using a Voronoi diagram approach. The network was calibrated to fit experimental air-water capillary pressure data collected for carbon fibre paper commonly used as a gas diffusion layer in fuel cells. These materials exhibit unusually strong capillary hysteresis, to the extent that water injection and withdrawal occur at positive and negative capillary pressures, respectively. Without the need to invoke contact angle hysteresis, this capillary behaviour is re-produced when using a porescale model based on the curvature of a meniscus passing through the centre of a toroid. The classic Washburn relation was shown to produce erroneous results, and its use is not recommended when modelling fibrous media. The important effect of saturation distribution on the effective diffusivity of the medium was also investigated for both water injection and withdrawal cases. The findings have bearing on the understanding of both capillarity in fibrous media and fuel cell design.

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Section: Methodssupporting

confidence: 90%

“…In addition, our recent experiments for the in-plane diffusivity also report power law behaviour between 2 and 2.5 Tranter et al. ( 2017 ). Interestingly, although the dry networks exhibit significant anisotropy in absolute transport behaviour, the relative transport follows an almost identical pattern for both IP and TP directions.…”

Section: Resultsmentioning

confidence: 62%

Capillary Hysteresis in Neutrally Wettable Fibrous Media: A Pore Network Study of a Fuel Cell Electrode

Tranter¹,

Gostick²,

Burns

et al. 2017

Transp Porous Med

View full text Add to dashboard Cite

show abstract

“…Variation of the formation factor in the x, y and z directions with saturation of the GDL from μ-CT and numerical reconstructions compared to previously reported literature data for partially saturated Toray TGP-H-120 GDLs. 18,20 For the numerical and μ-CT reconstructions, x and y are in-plane directions and z is through-plane direction. Tranter et al 20 measured the inplane (IP) diffusivity of partially saturated Toray TGP-H-120 GDL with 5% PTFE.…”

Section: Resultsmentioning

confidence: 99%

“…Figure 11 also shows a comparison of the formation factors for partially saturated GDLs from μ-CT and CFM simulations to previously reported literature data for Toray TGP-H-120 GDLs. 18,20 Tranter et al 20 measured the in-plane diffusivity for partially saturated Toray TGP-H-120 GDL with 5% PTFE. The simulated formation in-plane (x and y) factors for the μ-CT and CFM simulations have a maximum formation factor difference of ± 0.05 compared to the experimental values in Reference 20.…”

Section: Resultsmentioning

confidence: 99%

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Virtual Liquid Water Intrusion in Fuel Cell Gas Diffusion Media

Sabharwal

Gostick

Secanell

2018

J. Electrochem. Soc.

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A cluster based full morphology (CFM) model is developed to predict liquid water intrusion in GDLs. The CFM model is used to simulate water intrusion into a dry GDL microstructure obtained from μ-CT. Numerical water saturation distributions are compared to experimental μ-CT reconstructions of the same GDL sample at varying saturation levels. A quantitative validation of the CFM model results is then provided by studying the number of voxels in the image that contain water in both the CFM model results and the μ-CT reconstructions. Results reveal that CFM simulations showed 56-95.7% agreement in the liquid water voxels when compared to the μ-CT simulations for saturations in the range of 29-92.3%. Gas transport simulations are then performed on μ-CT and CFM partially saturated GDLs in order to study the validity of the CFM model images to estimate transport properties of partially saturated GDLs. A maximum error of 20% was observed between the predicted effective diffusivities obtained from CFM simulations and those obtained directly from simulations on the μ-CT data for saturations below 40%. Effective diffusivity predictions from the CFM simulations agree well with in-plane effective diffusivities in literature while the through-plane effective diffusivities were underpredicted by a factor of 2.

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Accurately predicting transport properties of porous fibrous materials by machine learning methods

Cawte

Bazylak

2022

Electrochemical Science Adv

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Machine learning algorithms trained on data gathered from stochastically generated gas diffusion layers (GDLs) were used to predict key transport properties that govern effective mass transport behaviour in polymer electrolyte membrane fuel cells. Specifically, we present the largest database in the present literature of stochastically generated fibrous GDL substrates (containing over 2000 unique materials) and the associated structural and transport properties determined via pore network modelling. Seven established machine learning algorithms were trained to predict the effective single‐phase permeability (ksp) and diffusivity (Dsp), and the relative permeability (kr) and diffusivity (Dr) of the generated materials using well‐defined material properties as input features. Gradient boosting regression (GBR), artificial neural network, and support vector regression were the best performing predictors of the single‐phase properties, all of which exhibited statistically insignificant differences in error. GBR provided the best prediction accuracy of relative transport properties.

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A method for measuring relative in-plane diffusivity of thin and partially saturated porous media: An application to fuel cell gas diffusion layers

Abstract: This is a repository copy of A method for measuring relative in-plane diffusivity of thin and partially saturated porous media: an application to fuel cell gas diffusion layers.

Cited by 20 publications

References 45 publications

Capillary Hysteresis in Neutrally Wettable Fibrous Media: A Pore Network Study of a Fuel Cell Electrode

Capillary Hysteresis in Neutrally Wettable Fibrous Media: A Pore Network Study of a Fuel Cell Electrode

Virtual Liquid Water Intrusion in Fuel Cell Gas Diffusion Media

Accurately predicting transport properties of porous fibrous materials by machine learning methods

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