Computational Modeling of Structural Energy Storage

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dc.contributor.advisorArdebili, Haleh
dc.contributor.committeeMemberSharma, Pradeep
dc.contributor.committeeMemberKulkarni, Yashashree
dc.contributor.committeeMemberRyou, Jae-Hyun
dc.contributor.committeeMemberRodrigues, Debora F.
dc.creatorAderyani, Sarah
dc.date.accessioned2020-06-04T02:58:49Z
dc.date.createdMay 2020
dc.date.issued2020-05
dc.date.submittedMay 2020
dc.date.updated2020-06-04T02:58:50Z
dc.description.abstractFlexible 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.
dc.description.departmentMechanical Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.citationPortions of this document appear in: Aderyani, S., P. Flouda, J. L. Lutkenhaus, and H. Ardebili. "The effect of nanoscale architecture on ionic diffusion in rGo/aramid nanofiber structural electrodes." Journal of Applied Physics 125, no. 18 (2019): 185106. And in: Aderyani, Sarah, Smit A. Shah, Ali Masoudi, Micah J. Green, Jodie L. Lutkenhaus, and Haleh Ardebili. "Comparison of Nanoarchitecture to Porous Media Diffusion Models in Reduced Graphene Oxide/Aramid Nanofiber Electrodes for Supercapacitors." ACS nano (2020).
dc.identifier.urihttps://hdl.handle.net/10657/6708
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectComputational Modeling, Structural Energy storage
dc.titleComputational Modeling of Structural Energy Storage
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2022-05-01
local.embargo.terms2022-05-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentMechanical Engineering, Department of
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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