http://theses.ncl.ac.uk/jspui/handle/10443/3889 2026-04-23T12:33:42Z 2026-04-23T12:33:42Z Barnett, Hector George http://theses.ncl.ac.uk/jspui/handle/10443/6743 2026-04-23T10:32:44Z 2025-01-01T00:00:00Z

Title: Characterisation of geological storage on the UKCS from interpretation of seismic reflection data Authors: Barnett, Hector George Abstract: This thesis investigates the impact of interpretation uncertainty on subsurface storage sites for the purposes of storing either hydrogen or carbon dioxide. 3D seismic and well data were used alongside complementary modelling methods to quantify uncertainties and sensitivities. The work investigates three themes, the interpretation of the complex internal structure of evaporites; the impact of geological uncertainties on salt cavern developments, and the variation in seismic response expected under different fluid saturations. The internal structure of the Zechstein Supergroup shows high levels of deformation and geometries that increase in complexity basin-ward. The internal deformation was interpreted and characterised, identifying six unique deformation styles which were parametrised and mapped spatially. This has implications for storage site suitability. Geological uncertainties were quantified for salt cavern developments, using a stochastic workflow that was developed to model potential cavern emplacement locations and hydrogen capacity. The potential hydrogen storage capacity in salt caverns in the UK sector of the Southern North Sea (80+ PWh) is far greater than any potential storage demand (100 TWh). Total energy storage demand could be met with as few as 73 caverns in an area 28 km2. The variation in the seismic response of siliciclastic reservoirs on the United Kingdom’s continental shelf was investigated after fluid substitution of non-hydrocarbon fluids to further understand seismic monitoring approaches. The results show that typical monitoring approaches, such as 4D amplitude comparisons, may not be suitable due to the limited change in elastic properties of the reservoir rocks once substituted with the pore filling fluid. This thesis quantifies and constrains the uncertainty of the subsurface for storage of non hydrocarbon fluids within the UKCS for both porous media and salt caverns. Description: PhD Thesis

2025-01-01T00:00:00Z Waiphara, Phatchareeya http://theses.ncl.ac.uk/jspui/handle/10443/6727 2026-04-10T09:01:16Z 2025-01-01T00:00:00Z

Title: Advancing Crop Monitoring and Disease Detection in Potatoes (Solanum tuberosum L.) Through High Throughput Phenotyping Utilizing Unmanned Aerial Vehicle and Remote Sensing Technology Authors: Waiphara, Phatchareeya Abstract: Due to increasing food demands and changing dietary preferences, the potato (Solanum tuberosum L.) has emerged as a key crop in various regions. This thesis, titled "Advancing Crop Monitoring and Disease Detection in Potatoes (Solanum tuberosum L.) through High Throughput Phenotyping Utilizing Unmanned Aerial Vehicles and Remote Sensing Technology," introduces an innovative approach to address the intricacies of potato crop physiology and phenotyping through the integration of unmanned aerial vehicles (UAVs), remote sensing, and machine learning technologies. This study examined the interaction among genotype, environmental factors, crop physiology, and yield prediction using high-throughput phenotyping and UAV-based remote sensing across various potato varieties over three growing seasons (2020-2022). The primary objective is to enhance our understanding of potato growth variations and how different potato varieties respond to and adapt to different field conditions. Multispectral imaging data were analysed using structure-from-motion (SfM) algorithms to generate canopy height, ground cover, and vegetation indices. These canopy parameters were then used to establish the relationship between UAV-based data and proximal data, providing the foundation for developing a predictive model for both yield estimation and disease detection. A strong correlation was observed between canopy height obtained from UAV and proximal measurement (R2=0.93). UAV data collection during the tuber initiation stage (UAV flight 2) showed the strongest correlation with ground-based measurements. As potato plants reached the tuber bulking stage (UAV flight 3), the correlation remained strong but became slightly less pronounced. However, as the plant reached the maturity stage, the correlation decreased dramatically. The results emphasise the critical importance of selecting appropriate approaches and timing for data collection to enhance the efficacy of plant phenotyping and genotyping studies. Maturation and yield predictive models have incorporated various crop parameters and machine learning techniques to improve predictive accuracy. The Random Forest (RF) approach demonstrated promising results, achieving an R2 of 78.31 in 2022 by using canopy volume, canopy area, canopy height, NDVI, and NDRE extracted from UAV flight 2 (tuber initiation stage). However, yield prediction accuracy varied across seasons due to environmental variability. Furthermore, the evaluation of potato maturity showed that the RF model outperformed the Partial Least Square Regression (PLSR) and Decision Tree models. In terms of tuber quality, this study investigated the accumulation of potato glycoalkaloids (PGAs) in relation to greening phenomena in potato tubers. Analysis from nine potato varieties showed significant variations in total PGA concentrations across different greening scores (0 5 scale), with the ‘Craigs Royal’ variety demonstrating the highest concentration (2635 ± 638 mg/kg FW) at a greening score of 5. Concerningly, some varieties, such as ‘Dundrod’ and ‘Anna’, also exceed the food safety limit (200 mg/kg FW) even at low greening levels. In contrast, non-green tubers remained within the safety limits (21.8-189.5 mg/kg FW). In summary, this research not only advances the domain of potato phenotyping and disease detection but also enhances the broader agricultural sector through the development of the pipeline for enhancing crop monitoring and disease detection through innovative image sensing and data analysis technologies. The thesis showcases the potential of UAV-based remote sensing for crop monitoring and enhancing disease detection and yield prediction by exploiting spectral responses and canopy characteristics obtained through high-throughput techniques. The integration of UAV-based phenotyping with machine learning methodologies represents a leap forward in our capacity to monitor crop health and boost productivity. Description: Ph. D. Thesis.

2025-01-01T00:00:00Z Alharbi, Adhwa Abdulghani http://theses.ncl.ac.uk/jspui/handle/10443/6723 2026-04-10T08:18:44Z 2025-01-01T00:00:00Z

Title: Amine-Decorated Polymer Immobilised Ionic Liquid Stabilised Metal Nanoparticles: Synthesis and Applications in Catalysis Authors: Alharbi, Adhwa Abdulghani Abstract: Polymer-immobilised ionic liquid (PIIL) phase catalysis has gained attention due to the increased demand for efficient synthetic protocols and sustainable transformation processes. New methods are needed to improve the sustainability of current chemical processes. The Doherty-Knight group has been focused on developing modified polymer-immobilised ionic liquids to stabilise and modify the reactivity of nanoparticle catalysts. The first chapter explores the unique physical and chemical properties of ionic liquids (ILs) that make them suitable for various applications, including the stabilisation of metal nanoparticles (NPs), as well as the synthesis and application of polymer-immobilized ionic liquids (PIILs). Chapter 2 describes the synthesis of monomers and heteroatom-functionalised polymer immobilised ionic liquids as supports for the stabilisation of RuNPs. The amino-modified catalyst was found to catalyse the aqueous hydrolysis of NaBH4 efficiently to produce hydrogen under mild conditions. RuNP@NH2-PIILS exhibited higher activity than RuNP@NH2 PEGPIILS. Notably, RuNP@NH2-PIIL achieves one of the highest turnover frequencies (TOF) reported for RuNP-based catalysts (171 molH2.molcat-1 .min-1). In addition, it was recycled up to five times. Chapter 3 highlights the efficiency of the RuNP@NH2-PEGPIILS catalyst for the reduction of quinolines to 1,2,3,4-tetrahydroquinoline (THQ) via 1,2-dihydroquinoline (DHQ). The initial TOF of 610 mol quinoline converted mol Ru-1 h-1 for the reduction of quinoline is among the highest to be reported for a metal nanoparticle-based catalyst with a conversion of 96% obtained after 4 h at 65°C. A wide range of substituted quinolines were successfully reduced to either the corresponding 1,2-dihydroquinoline or 1,2,3,4-tetrahydroquinoline in short reaction times. Hot filtration experiments showed that the active species was heterogeneous. Chapter 4 describes a comparison of RuNP@NH2-PEGPIILS and PtNP@NH2-PEGPIILS as catalysts for the dehydrogenation of DMAB and AB. It demonstrated that RuNP@NH2 PEGPIILS is a more efficient catalyst than PtNP@NH2-PEGPIILS for the dehydrogenation of DMAB and AB, as RuNP@NH2-PEGPIILS gave initial TOFs of 8,300 molesH2.molcat−1.h−1 and 21,200 molesH2.molcat−1.h−1, respectively, compared with 3,050 molesH2.molcat−1.h−1 and 8,500 molesH2.molcat−1.h−1, respectively, for PtNP@NH2-PEGPIILS. In addition, RuNP@NH2 PEGPIILS showed high stability and reusability for the hydrolysis of DMAB over multiple cycles. Chapter 5 describes the synthesis of a range of RuNPs and PtNPs stabilised by an amine modified ordered mesoporous silica immobilised ionic liquid (OMSIIL). The examined nanoparticles were shown to be highly efficient catalysts for hydrogen evolution from NaBH4. This work aims to achieve a deeper understanding of this system and identify more effective catalysts for scale-up purposes. Description: PhD Thesis

2025-01-01T00:00:00Z Ahmad, Shawana http://theses.ncl.ac.uk/jspui/handle/10443/6719 2026-04-09T10:35:35Z 2025-01-01T00:00:00Z

Title: Exciton dynamics in organic light emitting diodes Authors: Ahmad, Shawana Abstract: Organic light emitting diode (OLED) technology has gained significant attention over the past few decades due to its self-emissive displays, high contrast ratios, and energy efficiency compared to traditional lighting sources. However, substantial challenges remain in achieving OLED emitters with long lifetimes and high efficiency while also having narrowband emissions. Current high-performance thermally activated delayed fluorescence (TADF) emitters, which can achieve 100% internal quantum efficiency (IQE), predominantly utilise charge-transfer (CT) excited states that exhibit inherently broad emissions, typically with a full-width half maximum (FWHM)of70-120 nm. This broad emission necessitates the use of filters or optical microcavities to enhance colour purity, which often introduces trade offs in efficiency and lifespan. To address this, multi-resonant (MR) emitters have been developed, offering narrow emissions but large singlet-triplet gaps, resulting in less TADF. Additionally, advancements in computational methods are needed to study these molecules effectively. This thesis is structured into three key parts that aim to tackle these challenges by investigating the optimisation of compounds used in OLED devices, focusing on the interplay between structural and electronic properties, thoroughly understanding the mechanisms involved, benchmarking computational methods, and designing novel organic molecules for OLEDs, thereby contributing to the broader goal of making OLED technology a superior alternative to current display technologies. The first part of the thesis explores the conformational control of TADF emitters using non-covalent interactions. TADF emitters typically require a specific Donor-Acceptor (D-A) framework, where the highest and lowest energy states have minimal spatial overlap, achieved by maintaining a near 90-degree angle between the D and A units. However, overly rigid D-A bonds can hinder TADF efficiency by limiting molecular movement necessary for vibrational coupling, while excessive flexibility can lead to dispersed TADF rates, broader emissions, and increased non-radiative decay rates. Introducing explicit chemical bonds to increase rigidity often excessively alters the electronic structure of these emitters, hindering their ability to exhibit TADF. One strategy is introducing steric hindrance between D-A groups, such as methylation; however, this can lead to enforcing orthogonal dispositions between D-A groups. We’ve demonstrated by examining a series of D-A molecules with a B-N bond that the introduction of non-covalent interactions via oxygen and sulphur atoms significantly stabilises the twisted conformer necessary for efficient TADF. This stabilisation enhances spin-orbit coupling, thus improving intersystem crossing (ISC) and reverse intersystem crossing (rISC) rates. The studyhighlighted theimportanceofmethoxygroups at donor in enhancing conformational control, leading to more stable and efficient TADF properties, particularly in solid-state applications. The second part of thesis addresses the challenge of achieving narrowband emission in luminescent materials for high-resolution and energy-efficient OLED displays. Calculations of emission spectra typically require ground and excited state geometries and Hessians, making them challenging for large molecule due to the high computational costs involved. The DHO model was employed in this study to predict the emission FWHM for various organic molecules including π-π∗, charge transfer (CT), and multiple-resonance (MR) without extensive excited state optimisations, making it a valuable tool for high-throughput screening. In addition, it can also be extended to include off-diagonal coupling between excited states, accounting for non-Condon and non-Born-Oppenheimer effects, which are crucial for functional organic molecules, especially those exhibiting TADF. Furthermore, by combining quantum chemistry at both TDDFT and CC2 levels of theory with rate calculations within the semi-classical Marcus formalism, we demonstrate that incorporating heteroatoms like oxygen and sulphur into the B-N framework slightly increases emission FWHM but significantly enhances the ISC pathway compared to the spin-vibronic mechanism, simplifying triplet harvesting mechanisms. This, along with the DHO model, offers new avenues for designing high-efficiency MR-TADF emitters and improving high-throughput screening procedures. The third part of thesis focuses on multi-resonance TADF (MR-TADF) materials, which offer high colour purity and photoluminescence quantum yield but suffer from slow rISC rates, resulting in long-delayed fluorescence lifetimes. Previous studies have highlighted the importance of double excitations, not accounted for within the framework of Linear Response Time Dependent Density Functional Theory (LR-TDDFT). This study employs Mixed-Reference Spin-Flip Time-Dependent Density Functional Theory (MRSF-TDDFT) to overcome these limitations, providing accurate excited state energetics, including the crucial ∆EST, and outperforming traditional LR-TDDFT methods. By increasing the density of states to enhance coupling between singlet and triplet states, this method was used to explore the excited state properties of these materials. The results in this work set the foundation for computationally efficient in silico development of high-performing MR-TADF materials within the framework of MRSF TDDFT. Despite progress in developing MR-TADF, narrow blue MR-TADF emitters face significant challenges due to the high energy required for blue emission, leading to energy losses and efficiency roll-off. Inverse design and high-throughput computational screening offer powerful, resource-efficient approaches to discover new deep blue MR-TADF emitters compared to traditional methodologies. However, the scarcity of documented MR-TADF emitters complicates this process. To address this, we have used the stoned algorithm with SELFIES molecular representation to generate a diverse candidate dataset, followed by high-throughput computational screening. This multi-stage funnel approach systematically narrowed the candidate pool, but the structures at the end showed minimal variations from the initial hypothesis. Nevertheless, the SF-TDDFT and MRSF-TDDFT approach proves promising for studying the excited state properties of MR-TADF emitters. In summary, this thesis presents significant advancements in the optimisation of compounds for OLED devices, enhancing the understanding of structural and electronic properties, and developing computational methods for designing novel organic molecules. Description: PhD Thesis

2025-01-01T00:00:00Z