Porous carbons prepared via templating methodologies have shown excellent performance for various energy storage applications, such as electrodes in batteries, supercapacitors and as gas storage materials. Despite the impressive performances often reported, various issues such as complex and multi-step synthesis strategies have impeded their implementation in practical devices, and so there is a need to develop new, low-cost and commercially viable strategies for their fabrication. This thesis explores an unconventional method for the preparation of templated carbons - a process termed ice-templating. Ice-templating, as will be discussed in the forthcoming chapters, is a relatively simple technique holds several advantages over more conventional templating strategies. Having its own difficulties and shortcomings, only a few papers had been published on ice-templated porous carbons (ITPCs) prior to the commencement of this PhD. This thesis describes the ways in which we explored and overcame these difficulties to successfully prepare a number of ice-templated porous carbons, before evaluating their performance as materials for various energy storage devices.

This research is themed around development of a tidal turbine simulation platform based on a three-dimensional oceanographic numerical modellling environment; more specifically, parameterization of effects of tidal turbine on flow current, turbulence, waves and sediment transport. In this context, the author adopts concepts in the current module, the turbulent module, the wave module and the sediment transport module of Finite-Volume, primitive equation Commmunity Ocean Model (FVCOM) to simulate the effects of tidal turbines. The retarding force concept is employed in the current module, working as an additional body force exerted on the water to simulate the turbine induced water deceleration. Three terms are added into the MY-2.5 turbulence closure to model turbine related turbulence generation, dissipation and turbulence length-scale interference. The built-in feature 'OBSTACLE' of the wave module is used to simulate the reduction of wave height caused by the turbine. The enhanced sediment suspension due to the turbine in motion is represented by an additional bottom shear stress term, entraining an extra portion of sediment particles from the bed into the water. Due to the fact that the bedload sediment transport module of FVCOM is not fully developed, it is not considered in this research; development of such a module is beyond the scope of this project. Coefficients of the turbine simulation terms are calibrated based on experimental data collected in the 'Total Environment Simulator laboratory flume' at the University of Hull, in which a prototype experiment was conducted. Small scale simulations carried out using ANSYS FLUENT also provided complementary calibration data. An idealized water channel model with mesh resolution fined down to the size of the simulated turbine is built to carry out the coefficient calibration. In general, the developed turbine simulation platform is capable of predicting reliable flow velocity, turbulent level, wave height and suspended sediment transport in the far wake region of the turbine, given proper values assigned to the relating coefficients. In addition, preliminary sensitivity tests are carried out to investigate the impact of these coefficients to the model's overall prediction to reveal the model's application range. Upon the satisfactory choices of the coefficients, the platform is applied to a 15m scale idealized single turbine case as well as a regional scale case based on the realistic hydrodynamics off the Anglesey coast, north-west of Wales. A series of single turbine tests are carried out with and without the turbine implementations, i.e. the coefficients represent turbine effects being switched on and off, in order to reveal the differences between the baseline case (no turbine) and case with turbine effects. Under realistic natural tidal and wave conditions, the Anglesey coast case showcases impact from a large scale turbine farm to both local and regional processes.

The traditional power system includes the centralised power generation, high voltage AC power transmission and three phase energy consumption. Electric energy conversion systems (ECSs) have been applied to the power generation, energy storage and power consumption to convert energy between the electric form and other forms. In the future power system, the ratio of distributed power generation and storage will have a rapid increment with the development of power electronics technology. Thus, the robustness and stability are significant to the ECSs in the future power electronics enabled power system. This thesis deals with the design and analysis with theoretical contribution, and the implementation of a perturbation estimation based nonlinear adaptive control (NAC) on ECSs, i.e. the wind turbine (WT), the energy storage system (ESS) in converter based microgrid (MG), and the induction motor (IM), respectively, in simulation and experimental validation. The wind turbine is one of the most promising distributed power generation resources. The challenge in controlling a wind turbine is its nonlinear behaviour of aerodynamics under random wind speed. This makes it difficult to obtain the optimal control performance operating under the time-varying wind speed via conventional linear control method. In addition, as the future power system including plenty of distributed generation and consumption, typically in MG application, the ESS is necessary to balance the power difference between power generation and consumption. Due to the low stiffness and inertia of an islanded MG, the challenge is the stability problem and power quality of MG under unknown disturbance and unbalanced power demand. Moreover, other than the disturbance from power generation side, plenty of unknown disturbance also appears on the power consumption. The most popular workhorse for industrial application is the induction motor (IM), which is affected by the disturbance of unknown load torque under operation. The IM has highly coupled states and nonlinear interactions between states. The conventional vector control depending on the flux position is sensitive to parameter changes. And the use of a speed encoder increases the risk in the IM speed drive in the electric vehicle application. To cope with these challenges in the ECS applications, the perturbation estimation based control method is studied and applied to improve the robustness of the ECSs for power generation, storage and consumption of the future power system. In the control method, a state and perturbation observer is used to estimate the perturbation term, which includes the nonlinear interactions between states, external disturbance, parameter changes and unmodeled dynamics. In the WT pitch angle control, a nonlinear PI-based controller is designed with a perturbation observer to estimate and compensate the system nonlinearities and disturbance of WT system. In the ESS voltage control of islanded MG, a voltage controller is designed for the ESS in MG via estimating and compensating the unknown disturbance to reduce the voltage unbalance rate. In the IM speed drive, an NAC based speed controller is investigated to control the IM directly under the stationary frame to improve its robustness under disturbance and parameter uncertainty. Another contribution is to propose a speed sensorless NAC controller with a combined SPO to control the IM without the dependency of a speed sensor. The proposed control methods are compared with the conventional methods regarding their control performance. The results show that the perturbation estimation based method can improve the robustness of ECS under disturbance and parameter uncertainty in the renewable power generation, MG bus voltage regulation, and IM speed drive. However, the great observer bandwidth can amplify the sensor noise and reduce the robustness and stability of the closed loop system. In the study, the observer and controller bandwidth is set greater than the controller bandwidth and lower than the sensor noise bandwidth, with optimised bandwidth tuned via pole placement method and the closed loop stability of the ECS systems is analysed using Lyapunov theory.

In the current work, different architectures and photoactive materials have been investigated in order to fabricate low-temperature solution-processed solar cells using dip and spin coating methods. Inverted bulk heterojunction structure has been utilised in fabrication of polymer solar cells using dip coating method. In this structure, all layers except electrodes were deposited using dip coating method, which demonstrated an excellent potential to produce large-scale area PV devices. Formulation of solutions (using different solvents) of hole transport layer, active layer, and electron transport layer play a key role in producing uniform thin films as well as compatibility with dip coating method. The best PV device achieved ~ 3.4% power conversion efficiency. On the other hand, planar heterojunction structures have been employed to produce perovskite-based solar cells using one and two step spin coating methods (OSSCM & TSSCM). Thorough investigations of controlling the morphology of the perovskite films have been carried out using low-temperature processing methods. It was found that it is difficult to control the morphology via OSSCM without additives or using solvent engineering. Controlling the morphology of the perovskite films was achieved via TSSCM after optimizing process parameters such as the concentration of methylammonium iodide (MAI), allowed reaction time (Art), and thermal annealing. In this work it has been established that the best morphology of the perovskite film was achieved when the 1.0 wt% MAI solution was loaded at 60 sec on top of the pre-coated PbI2 followed by thermal annealing for two hours.

The rich coordination chemistry of transition metals renders them of interest for broad applications in energy conversion. For example, there is increasing interest in molecular light absorbers such as dye-sensitized photoelectrochemical solar cells (DSSCs) and hybrid inorganic/organic devices. Additionally, the properties of light emitting molecules are the subject of intense research, with applications in organic light emitting diodes (OLEDs) and photosensitisers of energy- and electron-transfer for solar energy conversion. This thesis can be broadly separated into two sections; (1) the study of a macrocyclic cobalt complex and its potential as a catalyst for the conversion of protons into H2 and (2) the synthesis and study of transition metal complexes as phosphorescent dopants for OLEDs. In part 1, the synthesis and characterisation of a series of cobalt compounds coordinated by the macrocyclic biquinazoline ligand, Mabiq, is presented. The solution and solid-state structures of the compounds were examined, alongside the electronic structures of paramagnetic 2 and 3. Electrochemistry data reveals that the reduction of 4 is possible to form a formally Co0 species, which shows promise in its activity with respect to H2 production. In part 2, the synthesis and characterisation of a range of mono- and bimetallic Pt(II) and Ir(III) complexes is presented. A series of readily synthesised tridentate proligands and their resulting complexes is presented that include pseudo-cyclometallating units to allow for mild reaction conditions. The complexes are weakly emissive, with PLQYs in the range 0.1 – 4%, attributed to varying rates of non-radiative decay. Two successful strategies in decreasing non-radiative decay are reported: the replacement of the chloride ancillary ligand with a stronger field acetylide ligand and the development of tetradentate proligands to improve the rigidity of the square planar complexes. The synthesis of hydrazone-based proligands, which offer two N^N^O-coordination sites bridged by a central pyrimidine ring is also reported. Coordination of a second Ir(III) centre results in a 6-fold enhancement of the PLQYs.

The bioelectronics field has incorporated an increasing variety of conducting polymers in applications that involve mixed ionic/electronic transport, yet there is still a lack of design rules to purposefully tune the electronic and ionic contributions to a material's conductivity, as well as processing methods to further control and understand their interplay. New undoped co-polymers were explored as electroactive materials in aqueous media. The range of materials allowed establishing a simple design rule with potential to be explored in other model semiconductors. The most hydrophilic system showed promising response when benchmarked with poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) in order to be employed in new operation modes of devices which rely on the electrochemical doping of the active layer, such as organic electrochemical transistors (OECTs). The capabilities of the most promising system were further exploited as an ion-to-electron converter by creating multicomponent systems that included a polar insulator to tune their ionic transport. The straight-forward and chemically inert blending approach showed enhanced transport of ionic species while maintaining their electronic transport as well as displaying characteristic response times linked to the presence of the polar phase. By using the semiconductor as a model system and controlling the volume of aggregates present in the solid-state by means of processing, a phenomenological description was given of ionic transport in different regions of semicrystalline polymers along with their associated decay rates. Finally, the effect of humidity in the charge transport of the undoped co-polymers was explored, with a focus on elucidating ionic contributions from electronic ones. The incorporation of a ionic conductor, Nafion, in a bilayer structure was explored and showed an intimate interaction between the proton conductor and the electronic conductor. The potential of the multilayer structures as humidity sensors and other remarkable features found in their charge transport make these promising systems for further applications in bioelectronics.

It is widely recognised that future smart grids will heavily rely upon intelligent communication and signal processing as enabling technologies for their operation. Traditional tools for power system analysis, which have been built from a circuit theory perspective, are a good match for balanced system conditions. However, the unprecedented changes that are imposed by smart grid requirements, are pushing the limits of these old paradigms. To this end, we provide new signal processing perspectives to address some fundamental operations in power systems such as frequency estimation, regulation and fault detection. Firstly, motivated by our finding that any excursion from nominal power system conditions results in a degree of non-circularity in the measured variables, we cast the frequency estimation problem into a distributed estimation framework for noncircular complex random variables. Next, we derive the required next generation widely linear, frequency estimators which incorporate the so-called augmented data statistics and cater for the noncircularity and a widely linear nature of system functions. Uniquely, we also show that by virtue of augmented complex statistics, it is possible to treat frequency tracking and fault detection in a unified way. To address the ever shortening time-scales in future frequency regulation tasks, the developed distributed widely linear frequency estimators are equipped with the ability to compensate for the fewer available temporal voltage data by exploiting spatial diversity in wide area measurements. This contribution is further supported by new physically meaningful theoretical results on the statistical behavior of distributed adaptive filters. Our approach avoids the current restrictive assumptions routinely employed to simplify the analysis by making use of the collaborative learning strategies of distributed agents. The efficacy of the proposed distributed frequency estimators over standard strictly linear and stand-alone algorithms is illustrated in case studies over synthetic and real-world three-phase measurements. An overarching theme in this thesis is the elucidation of underlying commonalities between different methodologies employed in classical power engineering and signal processing. By revisiting fundamental power system ideas within the framework of augmented complex statistics, we provide a physically meaningful signal processing perspective of three-phase transforms and reveal their intimate connections with spatial discrete Fourier transform (DFT), optimal dimensionality reduction and frequency demodulation techniques. Moreover, under the widely linear framework, we also show that the two most widely used frequency estimators in the power grid are in fact special cases of frequency demodulation techniques. Finally, revisiting classic estimation problems in power engineering through the lens of non-circular complex estimation has made it possible to develop a new self-stabilising adaptive three-phase transformation which enables algorithms designed for balanced operating conditions to be straightforwardly implemented in a variety of real-world unbalanced operating conditions. This thesis therefore aims to help bridge the gap between signal processing and power communities by providing power system designers with advanced estimation algorithms and modern physically meaningful interpretations of key power engineering paradigms in order to match the dynamic and decentralised nature of the smart grid.

The battery management system (BMS) plays a defining role in the safety and proper operation of any battery energy storage system (BESS). Without significant advances in the state-of-the-art of BMS algorithms, the future uptake of high power/energy density battery chemistries by consumers in safety-critical applications, is not feasible. Therefore, this thesis aims to provide a coherent body of work on the enhancement of the most important tasks performed by a modern BMS, that is, the estimation and monitoring of various battery states, e.g. state-of-charge (SOC), state-of-health (SOH) and state-of-power (SOP). The Kalman Filter is an elegant set of robust equations that is often utilised by designers in modern BMS, to estimate the battery states and parameters in real time. A nonlinear version of the KF technique, namely the Extended Kalman Filter (EKF) is applied throughout this thesis to estimate the battery’s states including SOC, as well as the battery’s impedance parameters. To this end, a suitable model structure for online battery modelling and identification is selected through a comparative study of the most popular electrical equivalent-circuit battery models for real-time applications. Then, a novel improvement to the EKF-based battery parameters identification technique is made through a deterministic initialisation of the battery model parameters through a broadband system identification technique, namely the pseudorandom binary sequences (PRBS). In addition, a novel decentralised framework for the enhancement of the EKF-based SOC estimation for those lithium-ion batteries with an inherently flat open-circuit voltage (OCV) response is formulated. By combining these techniques, it is possible to develop a more reliable battery states monitoring system, which can achieve estimation errors of less than 1%. Finally, the proposed BMS algorithms in this thesis are embedded on a low-cost microprocessor hardware platform to demonstrated the usefulness of the developed EKF-based battery states estimator in a practical setting. This a significant achievement when compared to those costly BMS development platforms, such as those based on FPGAs (field-programmable gate arrays).

The aim of this work was the determination of the effects of gelling the electrolytes used in electrolytic capacitors of the type Ta/Ta2O5/gel electrolyte/counter electrode. The investigation was divided between two main areas: firstly, the ionic conductivity of gel electrolytes was examined using Pt/Pt black electrodes; secondly, the influence of various electrolytes on the properties of tantalum and Ta/Ta2O5 electrodes, and on the electrolytic capacitors was examined. The conductivity of a series of gels prepared from fumed silica and 40% sulphuric acid showed a non-linear dependence on silica content, but was sensitive to the method of preparation. A standard mixing technique was developed and the reproducible conductivity of gels prepared by this method showed a linear decrease with increasing silica content.

This thesis studies the application of copper(I) complexes as the sensitizing component of dye sensitized solar cells (DSCs). Ruthenium(II) polypyridyl complexes have been widely studied and shown great success for the past two decades; however the metal is rare and expensive. A copper(I) based DSC could offer a viable alternative to using ruthenium(II) dyes, taking into account the cost and sustainability advantages. Interest in copper(I) DSCs has reignited over the past five years and the work in this thesis begins by reproducing the synthesis of one of the first reported complexes, [Cu(6,6’-dimethyl-2,2’-bipyridine-4,4’-dicarboxylic acid)2][Cl]. A more detailed study of the dye and its properties will be described, including assessing the effect of TiO2 film dye time on DSC performance, electrochemical studies and coupling the dye with a Co2+/3+ mediator. In the following chapters, improvements to the basic 2,2’-bipyridine framework are investigated. An experimental and computational investigation with a [Cu(2,2'-biquinoline-4,4'-dicarboxylic acid)2][HNEt3] complex is presented, where the 2,2’-biquinoline ligand has been chosen as a bulkier, more conjugated alternative to the 2,2’-bipyridine ligand. Although DSC efficiencies with this complex are comparatively low, an investigation into possible reasons for this is described. This thesis then considers functionalisation of a 2,2’-bipyridine ligand with halide and thiophene substituents. Several new ligands and copper(I) complexes are described and characterised. A top DSC efficiency of 1.41% was obtained with a [Cu(6,6'-dimethyl-[2,2'-bipyridine]-4,4'-diyl)bis(thiophene-2-carboxylic acid)2][PF6] dye. The synthetic route towards this complex and an analysis of its features, such as emissive behaviour, electrochemical properties and electron diffusion length, are described.