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A network model to predict ionic transport in porous materials.
Filipe Henrique1, Paweł J Żuk2,3, Ankur Gupta1
1Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80303.
A new network model accelerates electric-double-layer charging predictions in porous electrodes by six orders of magnitude. This breakthrough enables efficient design of energy storage devices and analysis of electrode geometry effects.
Area of Science:
- Electrochemistry
- Materials Science
- Computational Modeling
Background:
- Understanding electric-double-layer (EDL) charging in porous media is crucial for developing advanced energy storage solutions.
- Current models face limitations due to high computational costs and simplified geometries, hindering progress in complex electrode designs.
Purpose of the Study:
- To develop a computationally efficient network model for predicting EDL charging dynamics in arbitrary porous networks.
- To overcome limitations of existing models by removing restrictions on EDL thickness and pore radii.
- To investigate the influence of pore network architecture on electrode performance.
Main Methods:
- Developed a network model based on modified Kirchhoff's laws for electrolyte transport in the Debye-Hückel limit.
- Utilized an equivalent circuit representation for simulating charge density and electric potential.
- Validated the model against direct numerical simulations, achieving significant speedups.
Main Results:
- The network model accurately predicts EDL charging dynamics, matching results from computationally intensive simulations.
- Achieved speedups of up to six orders of magnitude, enabling rapid simulation of large pore networks.
- Demonstrated the impact of pore connectivity and polydispersity on charging time scales, energy density, and power density.
Conclusions:
- The proposed network model offers a scalable and versatile tool for designing and optimizing porous electrodes for energy storage.
- Provides insights into geometric effects on electrode impedance spectroscopy.
- Facilitates the rational design of 3D-printed electrodes by efficiently simulating complex pore structures.

