Multiscale Optimization of Novel Materials for Clean Energy Applications

Abstract

The pursuit of clean energy systems has paved the way for the development of advanced lithium-oxygen (Li-O2) batteries. However, their practical application is hindered due to limited discharge capacity and energy density. Such drawbacks stem primarily from the accumulation of the insulating Li2O2 discharge product, causing pore blockage and surface passivation within the cathode structure. This impedes efficient mass transport, truncating the discharge process. Therefore, it is imperative to design hierarchical cathode structure that can improve the discharge capacity by enhancing product storage sites without pore blockage.

This PhD thesis addresses the pivotal question: How can we mitigate pore blockages while optimizing the discharge product accumulation sites in the porous cathode structure of a Li-O2 battery, ensuring uninterrupted mass transport? For that, initially, a one-dimensional continuum modelling was performed, offering a comprehensive understanding of hypothetical hierarchical cathode designs based on distributed tortuosity and porosity. Among these designs, cathodes with distributed porosity showcased a 56% enhancement in discharge capacity due to optimized oxygen mass transport and effective product distribution. This study became a major motivation for the development of multiscale modelling framework that may guide in designing the electrode structures and generating missing structural and transport data to evaluate their cell level performance.

The developed multiscale model is spanning over two length scales including cluster and cell scales. The cluster scale involves molecular structures containing few atoms to several thousand atoms and simulates species energy barriers, reaction pathways and species transport (both in solid electrode and liquid electrolyte). Whereas cell scale comprised of configuration of a single cell of battery and determines the voltage profiles, current distributions, and solid discharge product deposition inside battery’s cell. In current approach, the cluster scale is complemented by reactive force field molecular dynamic (ReaxFF-MD) and involves the designing of the electrode structures and generating missing structural and transport data for species. It is found that specifically hierarchical zeolite templated carbon (ZTC) RHO-ZTC emerged as a promoter of mass transport delivering diffusivities of lithium ions and oxygen in the range of 1.75×10-10 – 2.69×10-11 m2 ·s-1 and 1.17×10-10 – 1.53×10-11 m2 ·s-1 , respectively. Using generated data from ReaxFF-MD, an effective diffusivity correlation was formulated, assisting in evaluating the electrode performance at cell scale using two-dimensional continuum model. Further the proposed methodology, underpinned by experimental validation, is applied to evaluate the performance of hierarchical ZTC structures. Among various hierarchical ZTCs, the hierarchical RHO-ZTC based Li-O2 battery cell exhibited exceptional performance, achieving a peak discharge capacity and energy density of 2556 mAhgc -1 and 174 Whkgc -1 , respectively, when operated at a current density of 0.1 mAcm-2 . Overall, it is found that Li-O2 batteries based on hierarchical ZTCs exhibited 1.7-2.6 times larger discharge capacity compared to conventional Super P carbon. This enhanced performance is attributed to the efficient distribution of oxygen supply (due to higher effective diffusivities), and poor clogging of hierarchical pores (due to Li2O2 deposition) inside the cathode structures.

Finally, the scope of the developed multiscale approach is expanded to probe the influence of air-impurities such H2O (i.e., relative humidity) and CO2 on practical Li-O2 battery’s capacity. Surprisingly, water and carbon dioxide boost the discharge capacity by 34 %, and 21 %, respectively compared to pure O2 supply from air. The results presented in the thesis demonstrate the efficacy of our multiscale methodology, suggesting that this methodology could be widely applied to assess a myriad of materials for energy applications.

Date of Award	21 Dec 2023
Original language	American English
Supervisor	AHMED ALHAJAJ (Supervisor)