Fernando, N. R., 2024. Graphene derivatives for Li-ion batteries. Doctoral Thesis (Doctoral). Bournemouth University.
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Abstract
The growing demand for reducing carbon footprints in today’s economy underscores the urgent need to transition from fossil fuels to renewable alternatives. Depleted reserves of fossil fuels and escalating environmental concerns further highlight the necessity for viable alternatives to conventional energy sources. Among these alternatives, lithium-ion batteries have emerged as premier renewable energy reservoirs for consumer electronics, electric vehicles (EVs), and power networks due to their exceptional energy density, extended lifespan, lightweight design, and minimal maintenance requirements. However, conventional Li-ion batteries with graphite anodes fall short of meeting the escalating energy demands due to their limited nominal capacity of 372 mAh g⁻¹. To address this shortfall, there has been significant interest in replacing graphite anodes with high-capacity materials such as silicon and transition metal oxides (TMOs). Silicon possesses an impressive nominal Li- ion storage potential of 4200 mAh g⁻¹, while TMOs offer a storage capability of approximately 700 mAh g⁻¹, far surpassing that of graphite anodes. Yet, the adoption of silicon and TMOs faces significant challenges including restricted electrical conductivity, pronounced particle/electrode pulverisation during continuous lithiation/delithiation cycles, and rapid deterioration of Li-ion storage capacity. To mitigate these challenges effectively, integrating these materials with carbon nanostructures such as carbon nanofibers, graphene, and carbon nanotubes has emerged as a highly promising approach. Being highly electric conductive and mechanically robust, graphene is well-suited support for these high-capacitive materials. This PhD project introduces two graphene-based nanocomposites, graphene/NiO and graphene/Si, as promising anode materials for Li-ion batteries, offering potential solutions to the challenges. In Chapter 4, a graphene-incorporated NiO nanohybrid is introduced as an advanced anode for Li-ion batteries. The integration of graphene into NiO nanostructures is achieved through a novel one-step in situ hydrothermal process, yielding distinctive porous and conductive peony-like graphene/NiO nanohybrids. The integration of graphene enhances the current flow of NiO while also effectively regulating the restacking and aggregation of nanoparticles. Despite these advantages, practical challenges arise for NiO as a commercial anode in Li-ion batteries due to its limited availability and cost. As an alternative system, Chapter 5 presents an exfoliated graphene (EG) -Si nanocomposite as a commercial anodic product for Li-ion batteries. In addition to its rich presence on earth, silicon (Si) discloses the highest known gravimetric anode Li-ion storage potential of 4200 mAh g-1, making it a favourable choice for Li-ion batteries. It is widely utilised as the second most used industrial anode, following graphite. However, Si encounters critical challenges with severe volume alterations during Li-ion battery charging and discharging processes, leading to poor electrochemical performances. To address these drawbacks, the study presents an EG-Si composite, where the exfoliated graphene network acts as a mechanically supportive framework for high-capacity Si electrodes. The composite enhances electrode conductivity, preserves electrode integrity, and serves as a buffer to regulate Si volume alteration throughout the cycling. The exfoliated graphene composite showed an enhanced Li-ion storage capacity compared with natural graphite. Furthermore, the study investigates the influence of the mass ratio between Si and exfoliated graphene on the electrochemical energy storage performance to determine the optimal Si content for Li-ion batteries.
Item Type: | Thesis (Doctoral) |
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Additional Information: | If you feel that this work infringes your copyright please contact the BURO Manager. |
Uncontrolled Keywords: | Li-ion batteries; Si anodes; Graphene |
Group: | Faculty of Science & Technology |
ID Code: | 40471 |
Deposited By: | Symplectic RT2 |
Deposited On: | 07 Nov 2024 10:46 |
Last Modified: | 07 Nov 2024 10:46 |
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