The soluble lead flow battery: Image-based modelling of porous carbon electrodes. (1st August 2022)
- Record Type:
- Journal Article
- Title:
- The soluble lead flow battery: Image-based modelling of porous carbon electrodes. (1st August 2022)
- Main Title:
- The soluble lead flow battery: Image-based modelling of porous carbon electrodes
- Authors:
- Fraser, E.J.
Le Houx, J.P.
Arenas, L.F.
Dinesh, K.K.J. Ranga
Wills, R.G.A. - Abstract:
- Abstract: A novel numerical modelling framework coupling physics-based model equations and image-based input parameters is developed to simulate the behaviour of the soluble lead flow battery when reticulated vitreous carbon (RVC) electrodes are used. Experimental results are presented to validate the model. Open-source software OpenImpala is used to predict the macro-homogeneous properties of RVC from computed tomography scans of various grades of RVC. The process is repeated on manipulated datasets where a voxel dilation technique has been used to estimate the geometry of RVC electrodes with a range of thicknesses of electrodeposited material. The model predicts that with a region of free electrolyte dividing the electrodes, the electrolyte velocity is low within the electrodes. This is exacerbated by a build-up of deposit close to the inlet. By dividing the electrodes with only a porous separator, a deposit build-up is no longer seen, and the concentration within the electrodes is shown to be far more even. Finally, with an applied current density of 50 mA cm −2, the overpotential is predicted to be reduced by over 100 mV when 100 ppi RVC electrodes are used instead of 10 ppi electrodes. An experimentally validated voltage efficiency of over 80% is achieved. Graphical abstract: Unlabelled Image Highlights: Voxel dilation of CT data is used to estimate Pb/PbO2 geometry on RVC electrodes. Uneven current distribution both normal to and perpendicular to current collectorsAbstract: A novel numerical modelling framework coupling physics-based model equations and image-based input parameters is developed to simulate the behaviour of the soluble lead flow battery when reticulated vitreous carbon (RVC) electrodes are used. Experimental results are presented to validate the model. Open-source software OpenImpala is used to predict the macro-homogeneous properties of RVC from computed tomography scans of various grades of RVC. The process is repeated on manipulated datasets where a voxel dilation technique has been used to estimate the geometry of RVC electrodes with a range of thicknesses of electrodeposited material. The model predicts that with a region of free electrolyte dividing the electrodes, the electrolyte velocity is low within the electrodes. This is exacerbated by a build-up of deposit close to the inlet. By dividing the electrodes with only a porous separator, a deposit build-up is no longer seen, and the concentration within the electrodes is shown to be far more even. Finally, with an applied current density of 50 mA cm −2, the overpotential is predicted to be reduced by over 100 mV when 100 ppi RVC electrodes are used instead of 10 ppi electrodes. An experimentally validated voltage efficiency of over 80% is achieved. Graphical abstract: Unlabelled Image Highlights: Voxel dilation of CT data is used to estimate Pb/PbO2 geometry on RVC electrodes. Uneven current distribution both normal to and perpendicular to current collectors Reduced overpotential achieved compared to planar electrodes Experimentally validated voltage efficiency of over 80% … (more)
- Is Part Of:
- Journal of energy storage. Volume 52:Part A(2022)
- Journal:
- Journal of energy storage
- Issue:
- Volume 52:Part A(2022)
- Issue Display:
- Volume 52, Issue A (2022)
- Year:
- 2022
- Volume:
- 52
- Issue:
- A
- Issue Sort Value:
- 2022-0052-NaN-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-01
- Subjects:
- Image-based modelling -- Reticulated vitreous carbon -- Soluble lead flow battery -- Redox flow batteries -- Energy storage -- Porous electrodes
Energy storage -- Periodicals
Energy storage -- Research -- Periodicals
621.3126 - Journal URLs:
- http://www.sciencedirect.com/science/journal/2352152X ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.est.2022.104791 ↗
- Languages:
- English
- ISSNs:
- 2352-152X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21924.xml