Computational Modeling of Structural Energy Storage
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Flexible structural energy storage is a rapidly emerging area with tantalizing applications such as integrated devices in textiles and smart suits, portable electronic devices and electric vehicles (EV). Due to several outstanding properties, graphene oxide (rGO)/ aramid nanofiber (ANF) composite material has emerged as a compelling choice as a structural electrode for supercapacitors and batteries. A key question of significant technological relevance pertains to what kind of nanoscale architecture motifs may lead to enhanced ionic diffusivity — the key characteristic dictating the overall performance of the electrode. In this work, we attempt to address this precise question, through multiphysics computational modeling in the context of several experimentally realizable nanoarchitectures, namely, “layered” and “house of cards” nanostructures. We investigate different arrangements (staggered, aligned and square) with various degrees of waviness of the rGO nanosheets inside the ANF polymer matrix. Nanoarchitecture modeling results indicate that decreasing waviness of the rGO sheets can enhance the ion diffusivity in the staggered and aligned arrangements of the electrode material, while this effect is stronger in staggered arrangement than aligned arrangement. The results obtained from nanoarchitecture computational modeling are compared to the porous media approach. It is shown that the widely used porous electrode theory such as Bruggeman or Millington-Quirk relations, overestimates the effective diffusion coefficient. Also, the results from nanoarchitecture modeling are validated with experimental measurements obtained from impedance spectroscopy (EIS) and cyclic voltammetry (CV). The effective diffusion coefficients obtained from nanoarchitectural modeling show better agreement with experimental measurements. The effective properties obtained from nanoarchitecture modeling is used to simulate cyclic voltammetry (CV) of rGO/ANF structural supercapacitors. Various electrochemical kinetics evaluated to characterize structural supercapacitors. The insights obtained from this study can lead to a more effective design of electrode architectures. Finally, the effect of temperature on solid polymer Li-ion batteries is investigated through a 1D model that predicts the discharge behavior of flexible pouch cells at different temperatures. The simulations results show a good agreement with experimental measurements and yields fundamental insight which is essential for future developments in flexible solid polymer Li-ion batteries.