A customized framework for 3-D morphological characterization of microporous layers

Nanjundappa, Abhishek; Alavijeh, Alireza Sadeghi; Hannach, Mohamed El; Harvey, David; Kjeang, Erik

doi:10.1016/j.electacta.2013.04.103

Cited by 47 publications

(54 citation statements)

References 48 publications

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“…To follow the nomenclature of this review, it has to be pointed out, that τ in Figure 10 ought to be replaced by τ 2 . Besides COMSOL Multiphysics, 142,143 researchers have calculated tortuosity by using programs such as Cast3M 144 or custom made models, which focus on a specific electrochemical device, such as Batts3d. 33,55,145 In addition to simulating mass and charge transport, the tortuosity is also computable by exploiting the mathematical similarity between Fourier's law of heat conduction and Fick's law of diffusion shown in Eq.…”

Section: Mesh Based Calculation Methodsmentioning

confidence: 99%

Tortuosity in electrochemical devices: a review of calculation approaches

Tjaden

Brett

Shearing

2016

International Materials Reviews

200

188

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The tortuosity of a structure plays a vital role in the transport of mass and charge in electrochemical devices. Concentration polarisation losses at high current densities are caused by mass transport limitations and are thus a function of microstructural characteristics. As tortuosity is notoriously difficult to ascertain, a wide and diverse range of methods has been developed to extract the tortuosity of a structure. These methods differ significantly in terms of calculation approach and data preparation techniques. Here, we review tortuosity calculation procedures applied in the field of electrochemical devices to better understand the resulting values presented in the literature. Visible differences between calculation methods are observed, especially when using porosity-tortuosity relationships and when comparing geometric and flux based tortuosity calculation approaches.

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Section: Mesh Based Calculation Methodsmentioning

confidence: 99%

Tortuosity in electrochemical devices: a review of calculation approaches

Tjaden

Brett

Shearing

2016

International Materials Reviews

200

188

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“…The substrate is generally treated with polytetrafluoroethylene (PTFE) to impart hydrophobicity to the fiber surfaces, discouraging liquid water condensation and accumulation. The MPL has become a common addition to modern GDLs due to its desirable effects on CL-GDL contact, membrane hydration and liquid water management [5][6][7][8][9][10]. Generally, the MPL is composed of carbon black nanoparticles and PTFE, and has pore sizes in the range of 10-100 nm.…”

Section: List Of Tablesmentioning

confidence: 99%

Liquid water saturation and oxygen transport resistance in polymer electrolyte membrane fuel cell gas diffusion layers

Muirhead

Banerjee

George

et al. 2018

Electrochimica Acta

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In this thesis, the relative humidity (RH) of the cathode reactant gas was investigated as a factor which influences gas diffusion layer (GDL) liquid water accumulation and mass transport-related efficiency losses over a range of operating current densities in a polymer electrolyte membrane (PEM) fuel cell. Limiting current measurements were used to characterize fuel cell oxygen transport resistance while simultaneous measurements of liquid water accumulation were conducted using synchrotron X-ray radiography. GDL porosity distributions were characterized with micro-computed tomography (μCT). The work presented here can be used by researchers to develop improved numerical models to predict GDL liquid water accumulation and to inform the design of next-generation GDL materials to mitigate mass transport-related efficiency losses. This work also contributes an extensive set of concurrent performance and liquid water visualization data to the PEM fuel cell field that can be used for validating multiphase transport models.iii

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“…Different methods have been tried, such as thresholding approaches as in (Nanjundappa et al, 2013) or surface evolution as in (Jørgensen et al, 2010). Other methods include the ones shown in (Salzer et al, 2012), such as threshold backpropagation or valley detection.…”

Section: Image Analysis and Segmentationmentioning

confidence: 99%

Prediction of Effective Properties of Porous Carbon Electrodes from a Parametric 3D Random Morphological Model

et al. 2017

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2Torben Prill et al.Abstract Pore structures have a major impact on the transport and electrical properties of electrochemical devices, such as batteries and electric double-layer capacitors (EDLCs). In this work we are concerned with the prediction of the electrical conductivity, ion diffusivity and volumetric capacitance of EDLC electrodes, manufactured from hierarchically porous carbons. To investigate the dependence of the effective properties on the pore structures, we use a structurally resolved parametric model of a random medium. Our approach starts from 3D FIB-SEM imaging, combined with automatic segmentation. Then, a random set model is fitted to the segmented structures and the effective transport properties are predicted using full field simulations by iterations of FFT on 3D pore space images and calculations based on the geometric properties of the structure model. A parameter study of the model is used to investigate the sensitivity of the effective conductivity and diffusivity to changes in the model parameters. Finally, we investigate the volumetric capacitance of the EDLC electrodes with a geometric model, make a comparison with experimental measurements and do a parameter study to suggest improved microstructures.

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A customized framework for 3-D morphological characterization of microporous layers

Cited by 47 publications

References 48 publications

Tortuosity in electrochemical devices: a review of calculation approaches

Tortuosity in electrochemical devices: a review of calculation approaches

Liquid water saturation and oxygen transport resistance in polymer electrolyte membrane fuel cell gas diffusion layers

Prediction of Effective Properties of Porous Carbon Electrodes from a Parametric 3D Random Morphological Model

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