Characterising, understanding and predicting the performance of structural power composites

Dramatic improvements in power generation, energy storage, system integration and light-weighting are needed to meet increasingly stringent carbon emissions targets for future aircraft and road vehicles. The electrification of transport could significantly reduce direct CO2 emissions; however, battery energy and power density limitations pose a major technological barrier. The introduction of multifunctional structural power composites (SPCs), which simultaneously provide mechanical load-bearing and electrochemical energy storage, offers new possibilities. By replacing conventional materials with SPCs, electrical performance requirements could be relaxed, and vehicle mass could be reduced; however, for SPCs to outperform monofunctional systems, significant performance and reliability improvements are still required. The use of computational models to support experimental efforts has so far been overlooked, despite wide recognition of the benefits of such a combined approach. The aim of this work was to develop predictive finite element models for structural supercapacitor composites (SSCs), and use them to investigate their mechanical, electrical, and electrochemical behaviour. A unit cell modelling technique was used to generate realistic mesoscale models of the complex microstructure of SSCs. The effects of composite manufacturing processes on the final performance of SSCs were investigated through characterisation and modelling of compaction and manufacturing defects. Numerical predictions of the elastic properties of SSCs were evaluated against data from the literature; and the presence of defects was shown to significantly degrade performance. Motivated by the large series resistance of SSCs, direct conduction models were developed to better understand electrical charge transport. Based on investigations of various current collector geometries, design strategies for the mitigation of resistive losses were proposed. To enable analysis of the combined mechanical-electrochemical behaviour of SSCs, an ion transport user element subroutine was developed but could not be validated. Overall, this work demonstrates that substantial improvements in the mechanical and electrical properties of SSCs are possible through control of the composite microstructure. The models developed in this work provide guidance for the optimisation of manufacturing processes and the design of new SSC architectures, and underpin the future certification and deployment of these emerging materials.Open Acces

High-resolution 3D direct-write prototyping for healthcare applications

The healthcare sector has much to benefit from the vast array of novelties erupting from the manufacturing world. 3D printing (additive manufacturing) is amongst the most promising recent inventions with much research concentrated around the various approaches of 3D printing and applying this effectively in the health sector. Amongst these methods, the direct-write assembly approach is a promising candidate for rapid prototyping and manufacturing of miniaturised medical devices/sensors and in particular, miniaturised flexible capacitive pressure sensors. Microstructuring the dielectric medium of capacitive pressure sensors enhances the sensitivity of the capacitive pressure sensor. The structuring has been predominantly achieved with photolithography and similar subtractive approaches. In this project high-resolution 3D direct write printing was used to fabricate structured dielectric mediums for capacitive pressure sensors. This involved the development and rheological characterisation of printability-tuned water soluble polyvinyl pyrrolidone (PVP) based inks (10%-30% polymer content) for stable high-resolution 3D printing. These inks were used to print water soluble micromoulds that were filled and cured with otherwise difficult to structure low G’ materials like PDMS. Our approach essentially decouples ink synthesis from printability at the micrometre scale. The developed micro moulding approach was employed for printing pyramidal micro moulds, that were used as templates for fabricating pyramid structured dielectric mediums for capacitive pressure sensing. The power of the approach was used to alter the microstructures and reap enhanced pressure sensing characteristics for effective miniaturised capacitive pressure sensors. A pressure sensing ring – that could be worn by doctors and surgeons – was prototyped with our approach and employed successfully to monitor in real-time the radial pulse signal of a 29 year old male volunteer. The print resolution of the inks was enhanced by formulating and rheologically characterising a PVP/PVDF polymer blend ink that would wet the printing nozzle less due to the hydrophobicity of the PVDF

Management and Applications of Energy Storage Devices

This book reviews recent trends, developments, and technologies of energy storage devices and their applications. It describes the electrical equivalent circuit model of batteries, the technology of battery energy storage systems in rooftop solar-photovoltaic (PV) systems, and the implementation of second-life batteries in hybrid electric vehicles. It also considers a novel energy management control strategy for PV batteries operating in DC microgrids, along with the present state and opportunities of solid-state batteries. In addition, the book examines the technology of thin-film energy storage devices based on physical vapor deposition as well as the challenges of ionic polymer-metal composite membranes. Furthermore, due to the novel battery technology in energy storage devices, this book covers the structural, optical, and related electrical studies of polyacrylonitrile (PAN) bearing in mind the applications of gel polymer electrolytes in solid-state batteries. Since energy storage plays a vital role in renewable energy systems, another salient part of this book is the research on phase change materials for maximum solar energy utilization and improvement. This volume is a useful reference for readers who wish to familiarize themselves with the newest advancements in energy storage systems

Remote applications of electric potential sensors in electrically unshielded environments

The electric potential sensor is a novel, ultra high impedance sensor, previously developed at the University of Sussex. These sensors have been applied to a range of applications, including electrophysiology, non destructive testing of composite materials and novel nuclear magnetic resonance NMR probes. Some of these measurements can be made in a strongly coupled (≥100pF) mode, where the coupling capacitance is reasonably large and well dened, and ambient noise is therefore less problematic. However for many applications, there exists a requirement for this coupling to be much weaker. This weak and poorly dened coupling creates substantial problems with ambient noise often causing sensors to saturate and become unusable. In the past, therefore, these measurements have all been made inside electrically screened rooms and enclosures. The work discussed in this thesis explores the possibility of operating these sensors outside of electrically screened environments. A number of techniques for resilience against noise are explored and experiments to fully analyse and characterise the performance of the sensors are discussed. As a result of this work, further results are then shown for a number of experiments carried out in a busy lab environment, in the presence of noise sources, and with little or minimal screening used. In this case, data is shown for the collection of remote cardiac and respiratory data, imaging of the spatial distribution of charge on insulating materials, detecting electric eld disturbances for movement sensing and early results for a microscopic XY scanning application

Polyimides for piezoelectric materials, magnetoelectric nanocomposites and battery separators: synthesis and characterization

329 p.Se ha sintetizado una serie de poliimidas y copoliimidas que contienen grupos nitrilo en su estructura, y posteriormente han sido polarizadas por corona con objeto de dotarlas de comportamiento piezoeléctrico. Las condiciones de la polarización por corona han sido optimizadas para las muestras estudiadas, mostrando los coeficientes una buena estabilidad térmica y a lo largo del tiempo. Además, se ha estudiado la influencia en la piezoelectricidad de la unidad repetitiva con dos grupos nitrilo, observando que un incremento progresivo del contenido en el componente con dos grupos nitrilo (2CN) aumenta la respuesta piezoeléctrica. Los films poliméricos han demostrado alta estabilidad térmica mediante DSC y TGA, demostrando su uso a temperaturas superiores a 100ºC.Las propiedades dieléctricas de las muestras han sido determinadas mediante espectroscopia dieléctrica para comprender el comportamiento dieléctrico de los films de poliimida. Se ha analizado la contribución de los grupos nitrilo en las relajaciones dieléctricas y en los tipos de polarización que se ven implicados.El uso de poliimidas en nanocomposites magnetoeléctricos (ME) ha sido demostrado. Se ha medido el coeficiente magnetoeléctrico en un film de nanocomposite, preparado mediante un método de polimerización in-situ, usando nanopartículas esféricas de ferrita de cobalto como inclusión y una copoliimida amorfa, como matriz. Se han preparado diferentes fibras de poliimida mediante electrospinning (electrohilado), han sido caracterizadas y testadas como separadores para baterías de ion Litio

Correlative investigations into advanced silicon and silicon hybrid anode microstructures for high capacity Li-ion batteries

There is a continuing need for global attention to focus on further development of devices to enable efficient energy storage. This must align with a new and stringent renewable energy target of 32 % for the European Union by 2030. Present materials used within Li-ion batteries currently have a limitation on the amount of energy they can store and for a specified duration. In order to advance the capacity of their most advanced cylindrical cells, Tesla, Samsung, LG and Sony at present use a small fraction of silicon in graphite-dominant anodes to overcome issues around volume expansion and to extend operational life. However, to date, no successful commercial product has been reported that contains silicon as the predominant lithium host material. The solutions offered so far in literature involve complex chemical synthesis or intricate processing routes, which are not realistic solutions to produce practical or cost-effective devices. The thesis core is based on innovative approaches to stabilising silicon-based anodes via additives, which can be conveniently synthesised or commercially available and are chemically compatible with the electrode components. This research work reports on the use of metal-organic frameworks, namely UiO-66 and UiO-67, to enhance the electrochemical performance of high-capacity silicon anodes in lithium-ion batteries. This research work also studied other hybrid anode systems, based on silicon-graphene and silicon-tin powders, using conventional formulation approaches to compare with an advanced electrode manufacturing technique. This study demonstrates that certain additives improve the flexural capability and mechanical integrity of electrode materials. These additives extend the durability of silicon anodes to enable extended reversible transfer of Li-ions, and hence enable a longer lifespan of the battery. This study reports the use of high-quality physicochemical characterisation from a variety of experimental techniques to correlate the anode’s microstructure, dynamics and atomic-scale structure with the maintained performance of the battery. Focused ion beam-scanning electron microscopy (FIB-SEM) tomography, in conjunction with impedance spectroscopy and associated physical characterisation, has been employed to capture and quantify key aspects of the evolution of internal morphology and resistance build up within anodes. FIB-SEM tomography has been employed to explore the hierarchical structure of battery electrodes and for diagnosing battery failure mechanisms with high-resolution imaging. This approach will enable us to observe and quantify failures in Li-ion batteries at the electrode level. It is anticipated that this study will influence major improvements in the design of Li-ion battery materials and their processing which in turn positively impact cell performance

Wearable pressure sensing for intelligent gesture recognition

The development of wearable sensors has become a major area of interest due to their wide range of promising applications, including health monitoring, human motion detection, human-machine interfaces, electronic skin and soft robotics. Particularly, pressure sensors have attracted considerable attention in wearable applications. However, traditional pressure sensing systems are using rigid sensors to detect the human motions. Lightweight and flexible pressure sensors are required to improve the comfortability of devices. Furthermore, in comparison with conventional sensing techniques without smart algorithm, machine learning-assisted wearable systems are capable of intelligently analysing data for classification or prediction purposes, making the system ‘smarter’ for more demanding tasks. Therefore, combining flexible pressure sensors and machine learning is a promising method to deal with human motion recognition. This thesis focuses on fabricating flexible pressure sensors and developing wearable applications to recognize human gestures. Firstly, a comprehensive literature review was conducted, including current state-of-the-art on pressure sensing techniques and machine learning algorithms. Secondly, a piezoelectric smart wristband was developed to distinguish finger typing movements. Three machine learning algorithms, K Nearest Neighbour (KNN), Decision Tree (DT) and Support Vector Machine (SVM), were used to classify the movement of different fingers. The SVM algorithm outperformed other classifiers with an overall accuracy of 98.67% and 100% when processing raw data and extracted features. Thirdly, a piezoresistive wristband was fabricated based on a flake-sphere composite configuration in which reduced graphene oxide fragments are doped with polystyrene spheres to achieve both high sensitivity and flexibility. The flexible wristband measured the pressure distribution around the wrist for accurate and comfortable hand gesture classification. The intelligent wristband was able to classify 12 hand gestures with 96.33% accuracy for five participants using a machine learning algorithm. Moreover, for demonstrating the practical applications of the proposed method, a realtime system was developed to control a robotic hand according to the classification results. Finally, this thesis also demonstrates an intelligent piezoresistive sensor to recognize different throat movements during pronunciation. The piezoresistive sensor was fabricated using two PolyDimethylsiloxane (PDMS) layers that were coated with silver nanowires and reduced graphene oxide films, where the microstructures were fabricated by the polystyrene spheres between the layers. The highly sensitive sensor was able to distinguish throat vibrations from five different spoken words with an accuracy of 96% using the artificial neural network algorithm