Cen, Jiayi; (2024) Computational Modelling and Discovery of Future Lithium-ion Battery Cathodes. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Energy storage technologies provide flexible access to renewable energies that have intermittent availability and are key for transitioning towards green and sustainable energy. Lithium-ion batteries (LIBs) are currently one of the most promising electrical energy storage technologies for portable electronics due to their high energy and power densities. They are also ideal power sources for (hybrid-)electric vehicles in the automotive industry. With transportation accounting for more than a quarter of the total energy consumption worldwide, battery materials are driving the sustainability transformation. Current challenges in commercialising LIBs for the automotive industry involve meeting the ever-growing demand for higher energy density, improved electrode stability and cost reduction of electrode materials. Eliminating cobalt from cathode materials has been a popular strategy to reduce the cost. In this thesis, we use first-principles density functional theory (DFT) calculations to explore properties of cobalt-free oxides as intercalation cathodes. In the first part of the thesis, ab initio random structure searching (AIRSS) is used to explore structures in the Li-Ni-O phase diagram in search of potential cathode candidates. In the second part of the thesis, we study the intrinsic defect chemistry of a promising spinel cathode LiMn1.5Ni0.5O4 (LMNO) and investigate the response to cation doping. The theoretical insights from our studies complement experimental observations and guide researchers to design synthesis strategies for complex energy materials.

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