While various chemical engineering techniques are employed to analyze flow within porous materials like oil reservoirs and water filtration systems, their application in certain energy storage systems remains underexplored.
Thus, the study introduces a model to predict electrolyte transport in complex networks of slender pores.
The framework accelerates numerical computations by six orders of magnitude without compromising accuracy.
The discovery is important not just for storing energy in vehicles and electronic devices but also for power grids.
In these grids, where energy demand changes, efficient storage is needed to prevent waste during low-demand times and ensure quick supply during high-demand times.
While various chemical engineering techniques are employed to analyze flow within porous materials like oil reservoirs and water filtration systems, their application in certain energy storage systems remains underexplored.
Thus, the study introduces a model to predict electrolyte transport in complex networks of slender pores. The framework accelerates numerical computations by six orders of magnitude without compromising accuracy.
This model is then used to investigate the influence of connections and pore size distribution on the charging time scale of electrical double layers and to predict structure-property relationships.
The discovery is important not just for storing energy in vehicles and electronic devices but also for power grids. In these grids, where energy demand changes, efficient storage is needed to prevent waste during low-demand times and ensure quick supply during high-demand times.
