eprintid: 10188379
rev_number: 9
eprint_status: archive
userid: 699
dir: disk0/10/18/83/79
datestamp: 2024-04-25 09:25:43
lastmod: 2024-04-25 09:25:43
status_changed: 2024-04-25 09:25:43
type: thesis
metadata_visibility: show
sword_depositor: 699
creators_name: Cen, Jiayi
title: Computational Modelling and Discovery of Future Lithium-ion Battery Cathodes
ispublished: unpub
divisions: UCL
divisions: B04
divisions: C06
divisions: F56
note: Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
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.
date: 2024-03-28
date_type: published
oa_status: green
full_text_type: other
thesis_class: doctoral_open
thesis_award: Ph.D
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2253942
lyricists_name: Cen, Jiayi
lyricists_id: JCENX02
actors_name: Cen, Jiayi
actors_id: JCENX02
actors_role: owner
full_text_status: public
pages: 211
institution: UCL (University College London)
department: Chemistry
thesis_type: Doctoral
citation:        Cen, Jiayi;      (2024)    Computational Modelling and Discovery of Future Lithium-ion Battery Cathodes.                   Doctoral thesis  (Ph.D), UCL (University College London).     Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10188379/1/main-final-deposited.pdf