Tortuosity in electrochemical devices: a review of calculation approaches
By Bernhard Tjaden, D. Brett, Paul R. Shearing. 2018
229 citations recorded by the source corpus.
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 have been developed to extract the tortuosity of a structure. These methods differ significantly in terms of calculation approach and data preparation techniques. Here, a review of tortuosity calculation procedures applied in the field of electrochemical devices is presented 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.
Subfields: Electrical and Electronic Engineering, Materials Chemistry, Metals and Alloys
View Paper: https://www.semanticscholar.org/paper/cd5d80651abe372c5109afc4b3bbc1e92664a9d3
Citations in the corpus
- Investigating electrode calendering and its impact on electrochemical performance by means of a new discrete element method model: Towards a digital twin of Li-Ion battery manufacturing (2020, unknown): “[62] The tortuosity factora here reported were calculated by solving the first Fick’s law and applying the MacMullin equation[63] through GeoDict[64] computational software for each Cartesian direction ( x , y , z ).”
- Tortuosity of porous media: Image analysis and physical simulation (2021, unknown): “Basically, the 18-neighbor-connectivity criterion is used in the LBM simulation because of the adoption of the D3Q19 lattice arrangement, while the RWM, FDM and FVM simulations follow the 6-neighbor-connectivity criterion which only permits direct exchange of dependent variables occurring between ad”