Pore Network Modeling of Ion Transport Properties in Bicontinuous Electrolytes for Multifunctional Energy Storage Composites
Topic(s) : Multifunctional and smart composites
Co-authors :
Robert BÖHM (GERMANY), Davood PEYROW HEDAYATI (GERMANY), Willi ZSCHIEBSCH (GERMANY), Michael KUCHER (GERMANY)Abstract :
A new generation of energy storage devices have been recently introduced, namely structural batteries (SB) and structural supercapacitors (SSC). These devices are multifunctional carbon fiber reinforced polymer composites in which carbon fiber and the polymer play the dual role of structural composite and energy storage components. In SB and SSCs, polymeric electrolytes such as ionic-liquid gel, bicontinuous, and composite polymer electrolytes are used which provide both the load-carrying and ion transport functionalities. Among them, bicontinuous structural electrolyte (BSE) show the most promising multifunctional performance since they provide high mechanical stiffness and high ion conductivity. In BSEs two immiscible phases, typically a porous epoxy phase and a liquid phase, form an interconnected network. The solid phase acts as a support under mechanical stress while the porous network provides continuous pathways for ion transport.
Pore architecture parameters such as pore size, connection and distribution have a significant impact on the ion transportation in BSEs. Therefore, several methods have been developed for their measurement. Scanning electron microscopic images (SEM) or mathematical regeneration models have been already be used. However, these methods cannot capture the complete range of pore sizes form nano- to micro-scale and often exclude the pores at the lower size spectrum. In addition, the SEM approach can currently only be used on small samples of the electrolyte system, which can lead to upscaled localized defects. An alternative measurement method is the gas adsorption techniques, which are able to detect a wide range of pore sizes in larger sample sizes, allowing a more accurate distribution measurement. In the current study, an alternative pore network modeling (PNM) approach is used to model the ion transport properties in BSEs. This approach is an established technique for simulating multiphase transport in porous materials. However, PNM has not been employed to investigate BSEs in structural energy storage systems, where the widely-used FE modeling with continuous volume elements is not well suited to resolve finer details in the range from nano- to micro-scale. In addition, the PNM performs the simulation of similar sized networks in fractions of the time compared to conventional FE models. The developed PNM model uses experimentally-obtained pore size distribution obtained via gas adsorption techniques as input values and builds a fluid flow network consisting of pores and throats. Then, various approaches to generate pore and throat diameters based on the experimental data are compared. This method provides the unique opportunity to capture the effect of different pore sizes on the ionic conductivity of the BSE. Finally, the proposed method was validated by predicting the ionic conductivity in BSE and comparing the results with experimental measurements from the literature. Thereby, a good agreement was achieved.
Pore architecture parameters such as pore size, connection and distribution have a significant impact on the ion transportation in BSEs. Therefore, several methods have been developed for their measurement. Scanning electron microscopic images (SEM) or mathematical regeneration models have been already be used. However, these methods cannot capture the complete range of pore sizes form nano- to micro-scale and often exclude the pores at the lower size spectrum. In addition, the SEM approach can currently only be used on small samples of the electrolyte system, which can lead to upscaled localized defects. An alternative measurement method is the gas adsorption techniques, which are able to detect a wide range of pore sizes in larger sample sizes, allowing a more accurate distribution measurement. In the current study, an alternative pore network modeling (PNM) approach is used to model the ion transport properties in BSEs. This approach is an established technique for simulating multiphase transport in porous materials. However, PNM has not been employed to investigate BSEs in structural energy storage systems, where the widely-used FE modeling with continuous volume elements is not well suited to resolve finer details in the range from nano- to micro-scale. In addition, the PNM performs the simulation of similar sized networks in fractions of the time compared to conventional FE models. The developed PNM model uses experimentally-obtained pore size distribution obtained via gas adsorption techniques as input values and builds a fluid flow network consisting of pores and throats. Then, various approaches to generate pore and throat diameters based on the experimental data are compared. This method provides the unique opportunity to capture the effect of different pore sizes on the ionic conductivity of the BSE. Finally, the proposed method was validated by predicting the ionic conductivity in BSE and comparing the results with experimental measurements from the literature. Thereby, a good agreement was achieved.