B. Costello, J. Davis
Georgia Institute of Technology,
Keywords: simulation, energy storage, electrical, power, dielectric, nanoparticle, composite, materials, variation, variability, energy density, permittivity, breakdown field strength
Summary:With the growing demand to create new energy storage technologies, there are a variety of approaches to creating solid-state capacitive energy storage devices for portable applications. One common strategy that experimentalist are pursuing is to incorporate high-k dielectric nanoparticles (NPs) embedded in a high dielectric strength polymer matrix. To understand the limits and opportunities of this approach, it is imperative to better understand the heterogeneous electric field distributions within these nanocomposite materials. To this end, an in-house material composition simulator is coupled with a quasi-electrostatic analysis to generate a large number of material compositions that vary by NP volume fraction and by random changes in a material’s microstructure. Key dielectric properties based on the electric field behavior are extracted to study their variability at an applied DC voltage. The electric fields are computed throughout the simulated composite materials using a finite difference method to solve Laplace’s equation . From the calculated electric fields, key electrical parameters such as effective permittivity, effective breakdown field strength, maximum energy density, and the mean electric fields in the host are computed for more than 1500 different microstructures. In addition, the variability of these key electrical parameters is also classified according to certain features of the composite microstructures that are described as percolating, near-percolating, or non-percolating. In addition, this new simulator is also validated using measured data from fabricated capacitor devices in . Initial conclusions of this analysis reveal that the highest energy density samples that are created are in a non-percolating configuration in a range of 20% to 40% NP volume fraction that exhibit up to a 14% increase in energy density over a pure PVDF sample. These samples give the best combination of permittivity increases while still having a large enough effective breakdown field strength to increase the energy density of the material. Some of the lowest energy density samples are in near percolating configurations in the range of 10% to 25% NP volume fraction and have an energy density that is as much as 68% lower than the pure PVDF sample. In addition, the average energy density over all microstructures increases monotonically and culminates to an 8% increase in the energy density over pure PVDF at a volume fraction of 60%. The standard deviation for the energy density around these average values also increases monotonically until it saturates to a normalized standard deviation of 3%. The goal of this work is to provide a simulation framework that can quickly guide, and possibly optimize, the architectures of future nanocomposite materials.