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310 Projects

  • 2013-2022
  • UKRI|EPSRC
  • OA Publications Mandate: No
  • 2015
  • 2019

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  • Funder: UKRI Project Code: EP/M021505/1
    Funder Contribution: 720,619 GBP

    Structural application of fibre-reinforced polymer (FRP) composite materials is one of the key factors leading to technological innovations in aviation, chemical, offshore oil and gas, rail and marine sectors. Motivated by such successes, FRP shapes and systems are increasingly used in the construction sector, such as for bridges and small residential buildings. An obstacle to a wider use of FRP materials in structural engineering is the current lack of comprehensive design rules and design standards. While the preparation of design guidance for static actions is at an advanced stage in the USA and EU, the design against dynamic loading is underdeveloped, resulting in cautious and conservative structural design solutions. Knowledge on the dynamic properties (natural frequencies, modal damping ratios, modal masses and mode shapes of relevant vibration modes) of FRP structures and their performance under dynamic actions (such as pedestrian excitation, vehicle loading, wind and train buffeting) needs to be advanced if to achieve the full economic, architectural and engineering merits in having FRP components/structures in civil engineering works. This project will provide a step change to design practice by developing new procedures and recommendations for design against dynamic actions. This will be achieved by: 1) Developing an instrumented bridge structure at the University of Warwick campus that will provide unique insight into both static and dynamic performance over the course of the project, and beyond; 2) Providing novel experimental data on dynamic properties and in-service vibration response of ten full-scale FRP structures; and 3) Critical evaluation of the numerical modelling and current vibration serviceability design approaches. The data collected will be delivered in a systematic form and made available, via an open-access on-line database for rapid and easy dissemination, to academic and industrial beneficiaries, as well as to agencies supporting the preparation of institutional, national and international consensus design guidance. Outcomes from this project will provide the crucial missing information required for the reliable design of light-weight FRP structures, and pave the way towards this structural material becoming a 'material of choice' for future large-scale bridges and other dynamically loaded structures. This medium to longer-term impact is aligned with national plans for the UK having a sustainable and resilient built environment.

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  • Funder: UKRI Project Code: 1652620

    New methods of construction are needed to advance the capability of aircraft structures, meet business demands & reduce manufacturing costs. One is the use of bonded assemblies for primary structure. FAA currently requires that unless the strength of the structure can be proven to match or exceed the design requirements, it must have mechanical fasteners to prevent critical failure. Bonded structures allow a significant reduction in weight due to using thinner skins. If 'Chicken rivets' are mandated, then this negates any benefit in terms of weight saving. The only current reliable way of testing the bonded assembly strength is proof loading - expensive & unrealistic for testing every part. An NDE method of testing a bonded assembly is needed to allow the use of lightweight bonded primary aerostructures. This must allow assessment that the desired strength is achieved, or identify areas of a weak-bonded area to allow repair. The project will investigate the application of phased array inspection approaches to determine bond strength, firstly studying current best practise with linear phased arrays and moving on to compare this to the recently developed nonlinear phased array approach.

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  • Funder: UKRI Project Code: EP/M027287/1
    Funder Contribution: 429,107 GBP

    With the widespread use of small mobile computing devices like smartphones and tablets, power efficiency has become a very important design criterion for hardware manufacturers like Intel, AMD, Infineon, ST, Qualcom, Nvidia, etc. This is due to the limited energy storage capacity of mobile devices, imposed by constraints on their size and weight, as well as by problems of heat dissipation. Similar considerations of power efficiency apply to implanted medical devices, wearable computing, UAV (unmanned airborne vehicles), satellites and sensor networks. Since chip design has become more and more automated, electronic design automation companies consider energy efficiency as a prime concern in circuit design. However, so far, there has been hardly any use of formal mathematical methods in energy efficient circuit design. Instead, the main techniques used in practice were either based on simulation or on semi-formal approaches reasoning about patterns and structural properties. Typical work areas are the following: 1. Power estimation (based on simulation), 2. Power verification (of structural (i.e., non-dynamic) properties), 3. Power optimisation (coarse high-level reasoning about size and structural patterns), and 4. Formal power verification (model checking applied to coarse abstractions based on activation/deactivation of blocks on the chip). In this project, we bring modern formal mathematical methods into automated circuit design. This yields a new domain of "5. Formal power optimisation". Here, efficient circuit design is achieved via solving the controller synthesis problem. This is to construct a controller that achieves (in every context) a combination of several objectives: (a) the functional correctness of the induced behaviour, as specified in the requirements specification, (b) a guaranteed limit on the peak energy consumption (i.e., an upper bound on the worst case), and (c) a low average energy consumption. While (a) and (b) are absolute constraints, the relative quality of the controller is measured in terms of how well it achieves objective (c). We solve the synthesis problem by applying modern mathematical techniques and tools from game theory (energy games, mean-payoff games), formal software verification (formal requirements specification and automata), and logic and algorithms (SAT and SMT solvers). Beyond theoretical advances and new techniques for the synthesis of energy efficient controllers, the project aims for practical application of controller synthesis in the new field of Formal Power Optimisation in circuit design. A prototype of a software tool that implements the new methods and applies them to power optimization in chip design will be evaluated on case studies provided by our industrial project partner Atrenta Inc.

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  • Funder: UKRI Project Code: EP/M008053/1
    Funder Contribution: 598,783 GBP

    The UK Government has an ambitious target of reducing CO2 emissions by 80% by 2050, and energy demand reduction will have to play a major part in meeting this goal. While traditional research on mitigation of carbon emissions has focused on direct consumption of energy (how we supply energy, what types of fuel we use, and how we use them etc.), the role that materials and products might play in energy demand reduction is far less well studied. One third of the world's energy is used in industry to make products, such as buildings, infrastructure, vehicles and household goods. Most of this energy is expended in producing the key stock materials with which we create modern lifestyles - steel, cement, aluminium, paper, and polymers - and we are already very efficient in producing them. A step change in reducing the energy expended by UK industry can therefore only come about if we are able to identify new ways of designing, using, and delivering products, materials and services. Before firm recommendations can be made to decision-makers regarding the combined technical and social feasibility of new products and material strategies, a fundamental set of research questions will need to be addressed. These concern how various publics will respond to innovative proposals for product design, governance and use. For example, more energy efficient products may need to operate differently or look very different, while a significant shift from an ownership model to a service delivery model (e.g., direct car ownership to car clubs and rental) can also deliver considerable material efficiency and energy demand reduction. Will members of the wider public and key decision-makers welcome, oppose, or actively drive such supply chain innovations, and what are the implications of knowledge about public views for decision-makers in the corporate and government sector? Understanding the answers to these questions is the main focus of this project. The research led by Cardiff University, and partnered with the Green Alliance, will combine qualitative and quantitative social science methodologies - in particular expert interviews and workshops, deliberative research and a (GB) national survey. The project has 4 phases, spanning a 45 month period. Work Package 1 involves initial work with UK INDEMAND partners, and interviews with industry and policy representatives, to identify the assumptions being made about people and society in key pathways for materials energy demand reduction. Work Package 2 involves four workshops - held in Edinburgh, Cardiff, London and a rural location - where members of the public will deliberate the identified pathways to change. In Work Package 3 we will conduct a nationally representative survey of 1,000 members of the British public, further exploring public perspectives on ways of designing and changing our use of materials. A particularly innovative aspect of the project is a set of targeted policy engagement activities (in Work Package 4) where we will hold workshops, interviews and other direct stakeholder involvement, exploring the implications of the findings about public views with key decision-makers in UK businesses, policy and the political sphere (including Parliamentarians through the Green Alliance's Climate Leadership programme for MPs). Along with the empirical data gathered in Work Packages 1, 2, and 3, the activities in Work Package 4 will allow us to formulate clear recommendations for action on achieving a reduction in UK final energy consumption through bringing knowledge of social barriers and opportunities to bear on governmental policy and industry decision-making about innovative materials and products delivery/use.

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  • Funder: UKRI Project Code: EP/N001893/1
    Funder Contribution: 1,402,240 GBP

    This project aims to understand how novel energy storage technologies might best be integrated into an evolving, lower-carbon UK energy system in the future. It will identify technical, environmental, public acceptability, economic and policy issues, and will propose solutions to overcome barriers to deployment. As electricity is increasingly generated by highly-variable renewables and relatively inflexible nuclear power stations, alternatives to the use of highly-flexible fossil-fuelled generation as a means of balancing the electricity system will become increasingly valuable. Numerous technologies for storing electricity are under development to meet this demand, and as the cost of storage is reduced through innovation, it is possible that they could have an important role in a low-carbon energy system. The Energy Storage Supergen Hub is producing a UK roadmap for energy storage that will be the starting point for this project. The value of grid-scale storage to the electricity system has been assessed for some scenarios. For extreme cases comprising only renewable and nuclear generation, the value is potentially substantial. However, the value of energy storage to the UK depends on the costs and benefits relative to sharing electricity imbalances through greater European interconnection, demand-side electricity response, and wider energy system storage, and the optimal approaches to integrating energy storage at different levels across the whole energy system are not well understood. This project will take a broader approach than existing projects by considering energy system scenarios in which storage options are more integrated across the whole energy system, using a series of soft-linked energy and electricity system models. Demand-side response and increased interconnection will be considered as counterfactual technologies that reduces the need for storage. Three broad hypotheses will be investigated in this project: (i) that a whole energy system approach to ES is necessary to fully understand how different technologies might contribute as innovation reduces costs and as the UK energy system evolves; (ii) that a range of technological, economic and social factors affect the value of ES, so should all be considered in energy system scenarios; and, (iii) that the economic value of the difference between good and bad policy decisions relating to the role of energy storage in the transition to low-carbon generation is in the order of £bns. A broader, multidisciplinary approach, which extends beyond the techno-economic methodologies that are adopted by most studies, will be used to fully assess the value of energy storage. This project will therefore also examine public acceptability issues for the first time, compare the environmental impacts of storage technologies using life-cycle analyses, and examine important economic issues surrounding market design to realise the value of storage services provided by consumers. All of these analyses will be underpinned by the development of technology-neutral metrics for ES technologies to inform the project modelling work and the wider scientific community. These multidisciplinary considerations will be combined in a series of integrated future scenarios for energy storage to identify no-regrets technologies. The project will conclude by examining the implications of these scenarios for UK Government policy, energy regulation and research priorities. The analyses will be technical only to the point of identifying the requirements for energy storage, with absolutely no bias towards or against any classes of storage technology.

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  • Funder: UKRI Project Code: 1651735

    Future fusion power plants for clean energy production will need to operate with a mixture of different hydrogen isotopes, namely deuterium and tritium (D-T). The ITER experimental tokamak, currently being built in France, is an international fusion facility which will demonstrate burning plasma operation with D-T mixture. It is crucial to predict and optimise the fusion performance of ITER which requires deeper understanding of the effect of isotope mass on plasma confinement, transport and stability. The JET tokamak in the UK is in a phase of D-T experimental campaigns with both full tritium and deuterium-tritium operation. Together with the ITER-like combination of plasma facing components this phase addresses key aspects of operation with different hydrogen isotopes and will demonstrate ITER regimes in D-T. The project focuses on the analysis of JET-ILW edge plasma data in support of predictive models for the edge transport barrier. JET is in an excellent position for creating a high quality confinement and profile database suitable for studying core and edge contributions to the global confinement, to study the isotope scaling of the edge structure, to investigate the inter-ELM transport and the micro turbulence limiting the edge gradients.

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  • Funder: UKRI Project Code: EP/M008460/1
    Funder Contribution: 294,406 GBP

    A ring is a mathematical structure that models many types of symmetry. Most rings encountered "in nature" are noncommutative: the order of operations matters. This project will investigate deep relationships between noncommutative ring theory and geometry. Rings are studied through their modules: objects that echo the symmetry encoded in the ring. The structure of a ring depends subtly and powerfully on the geometry of families of modules over that ring, and this connection has led to many advances. This project will explore this connection between the geometry of families of modules and the algebraic structure of rings in depth. I will extend current methods and develop new ones, and will apply my results to important unsolved algebraic problems. An example of the power of this connection between geometry and algebra is given by the famous Virasoro algebra. The Virasoro algebra is renowned in mathematics and physics. It may be viewed as a mathematical model of statistical mechanics, and so is of deep importance to physics, particularly conformal field theory. The Virasoro algebra is a Lie algebra, rather than a ring; it can be turned into a ring by forming its so-called universal enveloping algebra. Although the Virasoro algebra had been intensively studied for many years, important basic questions about its universal enveloping algebra remained unanswered. Specifically, for at least 25 years mathematicians had been asking if the enveloping algebra of the Virasoro algebra had the noetherian property. (Rings that are noetherian are relatively well-behaved; those that are not noetherian are more exotic.) In recent joint work with Walton, I applied geometry to solve this problem: the enveloping algebra of the Virasoro algebra is not noetherian. Our work shows the power of geometric techniques to address purely algebraic problems. One key method of our proof that the enveloping algebra of the Virasoro algebra is not noetherian was to construct a simpler model, called the canonical birational commutative factor. Because it is simpler, the model is easier to study; on the other hand, passing to the model loses a great deal of information. In this project, I will develop a general method, which will apply to many more rings than the enveloping algebra of the Virasoro algebra, to construct other canonical factors that contain more information but are still amendable to study. A general construction of more complex canonical factors will be a significant advance. Through the new techniques this project will develop, I will answer many important questions in ring theory. I will use geometry to get more information about the enveloping algebra of the Virasoro algebra. I will explore whether the noetherian property described above can be detected through geometry. I will apply geometric methods to a large class of rings, of which the enveloping algebra of the Virasoro is only one example: to universal enveloping algebras of graded infinite-dimensional Lie algebras. Through these methods, I will show these rings are not noetherian. These rings are famously intractable, and this problem is inaccessible without the new methods that I will bring to bear.

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  • Funder: UKRI Project Code: EP/M006204/1
    Funder Contribution: 856,337 GBP

    In England alone, dementia affects more than 600,000 people with Parkinson's pathology constituting a significant and growing part of this. These numbers are increasing as the mean population age grows and represent a very substantial burden on the welfare system, the NHS and families. Parkinson's disease is a heterogeneous disease characterised by progressive neuronal loss, causing a decline in movement and other functions. Up to 80% of long-term survivors with Parkinson's develop dementia whereas a significant percentage reach early motor disability such as postural instability and falls. Currently there is no disease-modifying therapy, which in part is hindered by the lack of an objective marker that stratifies these patient subgroups and objectively measures their disease progression. Such a biomarker is urgently needed to facilitate the development of clinical trials that aim to slow down neurodegeneration and importantly to also inform prognosis and better plan care. Based on our preliminary work in serum samples, our prediction is that such a biomarker can be developed with technology that enables multiplexed sampling and quantitation of several disease-specific reactive protein changes that are present in low abundance in the peripheral circulation. This approach requires the identification of innovative biomarker-candidates and the availability of ultrasensitive, label-free protein detection methods. The current methods of screening proteins involve expensive and highly specialized pieces of equipment or are prone to low levels of sensitivity and/or complicated analytical procedures associated with significant (up to 200%) analytical error. Electrical detection methodologies are portable, highly sensitive, cheap, high throughput (measurement time of minutes - particularly important if many samples are being screened) and multiplexable (multiple proteins detected simultaneously giving, in relevant cases, a "fingerprint" of health). The interfacing of man-made electronics with biological receptor molecules can enable the specific and calibrated detection of markers of disease. Devices built around these principles have already had a profound impact on clinical diagnostics and the quality of life of those unfortunate enough to live with chronic diseases such as diabetes. An assessment of protein levels in biological fluid (urine, saliva, blood serum, spinal fluid) constitutes a critical reflection of current health and may be reflective of the disease progression. We have already shown that one of the body's responses to the small protein (alpha-synuclein) that accumulates in the brains of patient with Parkinson's disease is to generate anti-alpha-synuclein antibodies, which we have measured and correlated with the disease stage using electrochemistry. We have also shown that circulating microvesicles in the serum of patients have distinct bioactivity and protein composition. We propose to measure these microvesicle-associated proteins by integrated microfluidic multiplexed devises and in combination with our earlier data on auto-antibodies develop a multi-parameter kit to monitor disease progression. We are uniquely positioned to develop this technology and provide proof of concept in two extensively characterized longitudinal patient cohorts. Specifically, we will ask whether a combination of protein markers reflect the rate of progression to dementia or severe movement disability in carefully selected patient samples by correlating serial serum levels with detailed clinical assessments. In summary, we are seeking to solve a profound clinical challenge in the area of neurodegeneration by developing a unique multi-parameter receptor chemistry device that we believe will have unprecedented application and potency.

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  • Funder: UKRI Project Code: EP/N014189/1
    Funder Contribution: 1,218,040 GBP

    The relentless growth of the amount, variety, availability, and the rate of change of data has profoundly transformed essentially all aspects of human life. The Big Data revolution has created a paradox: While we create and collect more data than ever before, it is not always easy to unlock the information it contains. To turn the easy availability of data into a major scientific and economic advantage, it is imperative that we create analytic tools that would be equal to the challenge presented by the complexity of modern data. In recent years, breakthroughs in topological data analysis and machine learning have paved the way for significant progress towards creating efficient and reliable tools to extract information from data. Our proposal has been designed to address the scope of the call as follows. To 'convert the vast amounts of data produced into understandable, actionable information' we will create a powerful fusion of machine learning, statistics, and topological data analysis. This combination of statistical insight, with computational power of machine learning with the flexibility, scalability, and visualisation tools of topology will allow a significant reduction of complexity of the data under study. The results will be output in a form that is best suited to the intended application or a scientific problem at hand. This way, we will create a seamless pathway from data analysis to implementation, which will allow us to control every step of this process. In particular, the intended end user will be able to query the results of the analysis to extract the information relevant to them. In summary, our work will provide tools to extract information from complex data sets to support user investigations or decisions. It is now well established that a main challenge of Big Data is how 'to efficiently and intelligently extract knowledge from heterogeneous, distributed data while retaining the context necessary for its interpretation'. This will be addressed first of all by developing techniques for dealing with heterogenous data. A main strength of topology is its ability to identify simple components in complex systems. It can also provide guiding principles on how to combine elements to create a model of a complex system. It also provides numerical techniques to control the overall shape of the resulting model to ensure that it fits with the original constraints. We will use the particular strengths of machine learning, statistics and topology to identify the main properties of data, which will then be combined to provide an overall analysis of the data. For example, a collection of text documents can be analysed using machine learning techniques to create a graph which captures similarities between documents in a topological way. This is an efficient way to classify a corpus of documents according to a desired set of keywords. An important part of our investigation will be to develop robust techniques of data fusion. This is important in many applications. One of our main applications will address the problem of creating a set of descriptors to diagnose and treat asthma. There are five main pathways for clinical diagnosis of asthma, each supported by data. To create a coherent picture of the disease we need to understand how to combine the information contained in these separate data sets to create the so called 'asthma handprint' which is a major challenge in this part of medicine. Every novel methodology of data analysis has to prove that its 'techniques are realistic, compatible and scalable with real- world services and hardware systems'. The best way to do that is to engage from the outset with challenging applications , and to ensure that theoretic and modelling solutions fit well the intended applications. We offer a unique synergy between theory and modelling as well as world-class facilities in medicine and chemistry which will provide a strict test for our ideas and results.

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  • Funder: UKRI Project Code: EP/M02105X/1
    Funder Contribution: 348,059 GBP

    Context: The invention of artificial lighting, dating from Joseph Wilson Swan and Thomas Edison's seminal contributions to the invention and commercialization of the incandescent light bulb in 1879, is arguably one of the most important inventions of humankind. Artificial lighting permits most human activities to continue past sundown, thus immeasurably increasing worldwide human productivity. Though Edison's device was much brighter than candle lighting, it was inefficient, converting only 0.2% of electricity into light. Since this seminal invention, many other lighting devices have been developed, from the tungsten lamp, to fluorescent tubes to halogen lighting to light-emitting diodes (LEDs) to organic light-emitting diodes (OLEDs). With each further iteration in lighting technology, the quality (pureness of colour), power efficiency and brightness of the light produced by the device have each improved. Light emission also enables information displays, televisions and computer screens. Producing devices that are energy efficient is of particular importance as, according to the US Department of Energy, it is estimated that 1/3 of commercial electricity use and 10% of household electricity consumption in the United States alone is dedicated towards artificial lighting. Artificial lighting represents a $15 Billion market in the United States alone and almost $91 Billion worldwide, corresponding to 20% of total worldwide energy output. The environmental impact related to this energy consumption is enormous and is estimated to be responsible for 7% of global CO2 emissions. Whereas inorganic LED and organic or polymer OLED lighting is now the state of the art in artificial lighting, their high cost and small active surface area are still barriers to wide adoption. In fact, for large surface area outdoor lighting applications, low-pressure sodium lamps are still the technology of first choice. Within this context, there is an urgent need to find alternative artificial lighting technologies that are of lower production cost, more energy efficient, colour tunable and can be used in environments not currently accessible to current LED and OLED technologies. It is implicit that in a similar manner to OLEDs, such a new lighting technology would have applications in visual displays, telecommunication and sensors. Organometallic complexes capable of harnessing light and/or electrical current and transforming such energy into useful work are at the heart of many important applications. An application that is of particular interest to my research group is energy-efficient visual displays and flat panel lighting based on either a phosphorescent light-emitting electrochemical cell (LEEC) architecture or an OLED architecture. Currently, most ionic transition metal complex-based (iTMC) LEECs rely on the use of a charged iridium(III) complex as the luminophoric material. These complexes can be readily solution processed. Iridium complexes phosphoresce and thus the maximum photoluminescence quantum efficiency (PLQY) theoretically attainable is unity. The external quantum efficiency (EQE) of a LEEC device has been found to scale proportionately to the solid-state PLQY and as such bright devices are possible. Despite the advantages listed above, LEECs incorporating iTMCs have several weaknesses: (i) low EQE; (ii) limited stability of the device and (iv) colour quality, particularly with reference to blue light emission. This grant proposal targets the development blue-emitting iridium(III) cationic complexes that will act as a luminophoric material in both LEEC and OLED devices. The two main goals are: 1. to obtain a LEEC that emits brightly in the blue region of the spectrum and that is stable over thousands of hours and that can quickly illuminate upon the application of an external voltage; to produce higher performance deep blue emitting OLEDs.

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  • Funder: UKRI Project Code: EP/M021505/1
    Funder Contribution: 720,619 GBP

    Structural application of fibre-reinforced polymer (FRP) composite materials is one of the key factors leading to technological innovations in aviation, chemical, offshore oil and gas, rail and marine sectors. Motivated by such successes, FRP shapes and systems are increasingly used in the construction sector, such as for bridges and small residential buildings. An obstacle to a wider use of FRP materials in structural engineering is the current lack of comprehensive design rules and design standards. While the preparation of design guidance for static actions is at an advanced stage in the USA and EU, the design against dynamic loading is underdeveloped, resulting in cautious and conservative structural design solutions. Knowledge on the dynamic properties (natural frequencies, modal damping ratios, modal masses and mode shapes of relevant vibration modes) of FRP structures and their performance under dynamic actions (such as pedestrian excitation, vehicle loading, wind and train buffeting) needs to be advanced if to achieve the full economic, architectural and engineering merits in having FRP components/structures in civil engineering works. This project will provide a step change to design practice by developing new procedures and recommendations for design against dynamic actions. This will be achieved by: 1) Developing an instrumented bridge structure at the University of Warwick campus that will provide unique insight into both static and dynamic performance over the course of the project, and beyond; 2) Providing novel experimental data on dynamic properties and in-service vibration response of ten full-scale FRP structures; and 3) Critical evaluation of the numerical modelling and current vibration serviceability design approaches. The data collected will be delivered in a systematic form and made available, via an open-access on-line database for rapid and easy dissemination, to academic and industrial beneficiaries, as well as to agencies supporting the preparation of institutional, national and international consensus design guidance. Outcomes from this project will provide the crucial missing information required for the reliable design of light-weight FRP structures, and pave the way towards this structural material becoming a 'material of choice' for future large-scale bridges and other dynamically loaded structures. This medium to longer-term impact is aligned with national plans for the UK having a sustainable and resilient built environment.

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  • Funder: UKRI Project Code: 1652620

    New methods of construction are needed to advance the capability of aircraft structures, meet business demands & reduce manufacturing costs. One is the use of bonded assemblies for primary structure. FAA currently requires that unless the strength of the structure can be proven to match or exceed the design requirements, it must have mechanical fasteners to prevent critical failure. Bonded structures allow a significant reduction in weight due to using thinner skins. If 'Chicken rivets' are mandated, then this negates any benefit in terms of weight saving. The only current reliable way of testing the bonded assembly strength is proof loading - expensive & unrealistic for testing every part. An NDE method of testing a bonded assembly is needed to allow the use of lightweight bonded primary aerostructures. This must allow assessment that the desired strength is achieved, or identify areas of a weak-bonded area to allow repair. The project will investigate the application of phased array inspection approaches to determine bond strength, firstly studying current best practise with linear phased arrays and moving on to compare this to the recently developed nonlinear phased array approach.

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  • Funder: UKRI Project Code: EP/M027287/1
    Funder Contribution: 429,107 GBP

    With the widespread use of small mobile computing devices like smartphones and tablets, power efficiency has become a very important design criterion for hardware manufacturers like Intel, AMD, Infineon, ST, Qualcom, Nvidia, etc. This is due to the limited energy storage capacity of mobile devices, imposed by constraints on their size and weight, as well as by problems of heat dissipation. Similar considerations of power efficiency apply to implanted medical devices, wearable computing, UAV (unmanned airborne vehicles), satellites and sensor networks. Since chip design has become more and more automated, electronic design automation companies consider energy efficiency as a prime concern in circuit design. However, so far, there has been hardly any use of formal mathematical methods in energy efficient circuit design. Instead, the main techniques used in practice were either based on simulation or on semi-formal approaches reasoning about patterns and structural properties. Typical work areas are the following: 1. Power estimation (based on simulation), 2. Power verification (of structural (i.e., non-dynamic) properties), 3. Power optimisation (coarse high-level reasoning about size and structural patterns), and 4. Formal power verification (model checking applied to coarse abstractions based on activation/deactivation of blocks on the chip). In this project, we bring modern formal mathematical methods into automated circuit design. This yields a new domain of "5. Formal power optimisation". Here, efficient circuit design is achieved via solving the controller synthesis problem. This is to construct a controller that achieves (in every context) a combination of several objectives: (a) the functional correctness of the induced behaviour, as specified in the requirements specification, (b) a guaranteed limit on the peak energy consumption (i.e., an upper bound on the worst case), and (c) a low average energy consumption. While (a) and (b) are absolute constraints, the relative quality of the controller is measured in terms of how well it achieves objective (c). We solve the synthesis problem by applying modern mathematical techniques and tools from game theory (energy games, mean-payoff games), formal software verification (formal requirements specification and automata), and logic and algorithms (SAT and SMT solvers). Beyond theoretical advances and new techniques for the synthesis of energy efficient controllers, the project aims for practical application of controller synthesis in the new field of Formal Power Optimisation in circuit design. A prototype of a software tool that implements the new methods and applies them to power optimization in chip design will be evaluated on case studies provided by our industrial project partner Atrenta Inc.

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  • Funder: UKRI Project Code: EP/M008053/1
    Funder Contribution: 598,783 GBP

    The UK Government has an ambitious target of reducing CO2 emissions by 80% by 2050, and energy demand reduction will have to play a major part in meeting this goal. While traditional research on mitigation of carbon emissions has focused on direct consumption of energy (how we supply energy, what types of fuel we use, and how we use them etc.), the role that materials and products might play in energy demand reduction is far less well studied. One third of the world's energy is used in industry to make products, such as buildings, infrastructure, vehicles and household goods. Most of this energy is expended in producing the key stock materials with which we create modern lifestyles - steel, cement, aluminium, paper, and polymers - and we are already very efficient in producing them. A step change in reducing the energy expended by UK industry can therefore only come about if we are able to identify new ways of designing, using, and delivering products, materials and services. Before firm recommendations can be made to decision-makers regarding the combined technical and social feasibility of new products and material strategies, a fundamental set of research questions will need to be addressed. These concern how various publics will respond to innovative proposals for product design, governance and use. For example, more energy efficient products may need to operate differently or look very different, while a significant shift from an ownership model to a service delivery model (e.g., direct car ownership to car clubs and rental) can also deliver considerable material efficiency and energy demand reduction. Will members of the wider public and key decision-makers welcome, oppose, or actively drive such supply chain innovations, and what are the implications of knowledge about public views for decision-makers in the corporate and government sector? Understanding the answers to these questions is the main focus of this project. The research led by Cardiff University, and partnered with the Green Alliance, will combine qualitative and quantitative social science methodologies - in particular expert interviews and workshops, deliberative research and a (GB) national survey. The project has 4 phases, spanning a 45 month period. Work Package 1 involves initial work with UK INDEMAND partners, and interviews with industry and policy representatives, to identify the assumptions being made about people and society in key pathways for materials energy demand reduction. Work Package 2 involves four workshops - held in Edinburgh, Cardiff, London and a rural location - where members of the public will deliberate the identified pathways to change. In Work Package 3 we will conduct a nationally representative survey of 1,000 members of the British public, further exploring public perspectives on ways of designing and changing our use of materials. A particularly innovative aspect of the project is a set of targeted policy engagement activities (in Work Package 4) where we will hold workshops, interviews and other direct stakeholder involvement, exploring the implications of the findings about public views with key decision-makers in UK businesses, policy and the political sphere (including Parliamentarians through the Green Alliance's Climate Leadership programme for MPs). Along with the empirical data gathered in Work Packages 1, 2, and 3, the activities in Work Package 4 will allow us to formulate clear recommendations for action on achieving a reduction in UK final energy consumption through bringing knowledge of social barriers and opportunities to bear on governmental policy and industry decision-making about innovative materials and products delivery/use.

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  • Funder: UKRI Project Code: EP/N001893/1
    Funder Contribution: 1,402,240 GBP

    This project aims to understand how novel energy storage technologies might best be integrated into an evolving, lower-carbon UK energy system in the future. It will identify technical, environmental, public acceptability, economic and policy issues, and will propose solutions to overcome barriers to deployment. As electricity is increasingly generated by highly-variable renewables and relatively inflexible nuclear power stations, alternatives to the use of highly-flexible fossil-fuelled generation as a means of balancing the electricity system will become increasingly valuable. Numerous technologies for storing electricity are under development to meet this demand, and as the cost of storage is reduced through innovation, it is possible that they could have an important role in a low-carbon energy system. The Energy Storage Supergen Hub is producing a UK roadmap for energy storage that will be the starting point for this project. The value of grid-scale storage to the electricity system has been assessed for some scenarios. For extreme cases comprising only renewable and nuclear generation, the value is potentially substantial. However, the value of energy storage to the UK depends on the costs and benefits relative to sharing electricity imbalances through greater European interconnection, demand-side electricity response, and wider energy system storage, and the optimal approaches to integrating energy storage at different levels across the whole energy system are not well understood. This project will take a broader approach than existing projects by considering energy system scenarios in which storage options are more integrated across the whole energy system, using a series of soft-linked energy and electricity system models. Demand-side response and increased interconnection will be considered as counterfactual technologies that reduces the need for storage. Three broad hypotheses will be investigated in this project: (i) that a whole energy system approach to ES is necessary to fully understand how different technologies might contribute as innovation reduces costs and as the UK energy system evolves; (ii) that a range of technological, economic and social factors affect the value of ES, so should all be considered in energy system scenarios; and, (iii) that the economic value of the difference between good and bad policy decisions relating to the role of energy storage in the transition to low-carbon generation is in the order of £bns. A broader, multidisciplinary approach, which extends beyond the techno-economic methodologies that are adopted by most studies, will be used to fully assess the value of energy storage. This project will therefore also examine public acceptability issues for the first time, compare the environmental impacts of storage technologies using life-cycle analyses, and examine important economic issues surrounding market design to realise the value of storage services provided by consumers. All of these analyses will be underpinned by the development of technology-neutral metrics for ES technologies to inform the project modelling work and the wider scientific community. These multidisciplinary considerations will be combined in a series of integrated future scenarios for energy storage to identify no-regrets technologies. The project will conclude by examining the implications of these scenarios for UK Government policy, energy regulation and research priorities. The analyses will be technical only to the point of identifying the requirements for energy storage, with absolutely no bias towards or against any classes of storage technology.

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  • Funder: UKRI Project Code: 1651735

    Future fusion power plants for clean energy production will need to operate with a mixture of different hydrogen isotopes, namely deuterium and tritium (D-T). The ITER experimental tokamak, currently being built in France, is an international fusion facility which will demonstrate burning plasma operation with D-T mixture. It is crucial to predict and optimise the fusion performance of ITER which requires deeper understanding of the effect of isotope mass on plasma confinement, transport and stability. The JET tokamak in the UK is in a phase of D-T experimental campaigns with both full tritium and deuterium-tritium operation. Together with the ITER-like combination of plasma facing components this phase addresses key aspects of operation with different hydrogen isotopes and will demonstrate ITER regimes in D-T. The project focuses on the analysis of JET-ILW edge plasma data in support of predictive models for the edge transport barrier. JET is in an excellent position for creating a high quality confinement and profile database suitable for studying core and edge contributions to the global confinement, to study the isotope scaling of the edge structure, to investigate the inter-ELM transport and the micro turbulence limiting the edge gradients.

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  • Funder: UKRI Project Code: EP/M008460/1
    Funder Contribution: 294,406 GBP

    A ring is a mathematical structure that models many types of symmetry. Most rings encountered "in nature" are noncommutative: the order of operations matters. This project will investigate deep relationships between noncommutative ring theory and geometry. Rings are studied through their modules: objects that echo the symmetry encoded in the ring. The structure of a ring depends subtly and powerfully on the geometry of families of modules over that ring, and this connection has led to many advances. This project will explore this connection between the geometry of families of modules and the algebraic structure of rings in depth. I will extend current methods and develop new ones, and will apply my results to important unsolved algebraic problems. An example of the power of this connection between geometry and algebra is given by the famous Virasoro algebra. The Virasoro algebra is renowned in mathematics and physics. It may be viewed as a mathematical model of statistical mechanics, and so is of deep importance to physics, particularly conformal field theory. The Virasoro algebra is a Lie algebra, rather than a ring; it can be turned into a ring by forming its so-called universal enveloping algebra. Although the Virasoro algebra had been intensively studied for many years, important basic questions about its universal enveloping algebra remained unanswered. Specifically, for at least 25 years mathematicians had been asking if the enveloping algebra of the Virasoro algebra had the noetherian property. (Rings that are noetherian are relatively well-behaved; those that are not noetherian are more exotic.) In recent joint work with Walton, I applied geometry to solve this problem: the enveloping algebra of the Virasoro algebra is not noetherian. Our work shows the power of geometric techniques to address purely algebraic problems. One key method of our proof that the enveloping algebra of the Virasoro algebra is not noetherian was to construct a simpler model, called the canonical birational commutative factor. Because it is simpler, the model is easier to study; on the other hand, passing to the model loses a great deal of information. In this project, I will develop a general method, which will apply to many more rings than the enveloping algebra of the Virasoro algebra, to construct other canonical factors that contain more information but are still amendable to study. A general construction of more complex canonical factors will be a significant advance. Through the new techniques this project will develop, I will answer many important questions in ring theory. I will use geometry to get more information about the enveloping algebra of the Virasoro algebra. I will explore whether the noetherian property described above can be detected through geometry. I will apply geometric methods to a large class of rings, of which the enveloping algebra of the Virasoro is only one example: to universal enveloping algebras of graded infinite-dimensional Lie algebras. Through these methods, I will show these rings are not noetherian. These rings are famously intractable, and this problem is inaccessible without the new methods that I will bring to bear.

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  • Funder: UKRI Project Code: EP/M006204/1
    Funder Contribution: 856,337 GBP

    In England alone, dementia affects more than 600,000 people with Parkinson's pathology constituting a significant and growing part of this. These numbers are increasing as the mean population age grows and represent a very substantial burden on the welfare system, the NHS and families. Parkinson's disease is a heterogeneous disease characterised by progressive neuronal loss, causing a decline in movement and other functions. Up to 80% of long-term survivors with Parkinson's develop dementia whereas a significant percentage reach early motor disability such as postural instability and falls. Currently there is no disease-modifying therapy, which in part is hindered by the lack of an objective marker that stratifies these patient subgroups and objectively measures their disease progression. Such a biomarker is urgently needed to facilitate the development of clinical trials that aim to slow down neurodegeneration and importantly to also inform prognosis and better plan care. Based on our preliminary work in serum samples, our prediction is that such a biomarker can be developed with technology that enables multiplexed sampling and quantitation of several disease-specific reactive protein changes that are present in low abundance in the peripheral circulation. This approach requires the identification of innovative biomarker-candidates and the availability of ultrasensitive, label-free protein detection methods. The current methods of screening proteins involve expensive and highly specialized pieces of equipment or are prone to low levels of sensitivity and/or complicated analytical procedures associated with significant (up to 200%) analytical error. Electrical detection methodologies are portable, highly sensitive, cheap, high throughput (measurement time of minutes - particularly important if many samples are being screened) and multiplexable (multiple proteins detected simultaneously giving, in relevant cases, a "fingerprint" of health). The interfacing of man-made electronics with biological receptor molecules can enable the specific and calibrated detection of markers of disease. Devices built around these principles have already had a profound impact on clinical diagnostics and the quality of life of those unfortunate enough to live with chronic diseases such as diabetes. An assessment of protein levels in biological fluid (urine, saliva, blood serum, spinal fluid) constitutes a critical reflection of current health and may be reflective of the disease progression. We have already shown that one of the body's responses to the small protein (alpha-synuclein) that accumulates in the brains of patient with Parkinson's disease is to generate anti-alpha-synuclein antibodies, which we have measured and correlated with the disease stage using electrochemistry. We have also shown that circulating microvesicles in the serum of patients have distinct bioactivity and protein composition. We propose to measure these microvesicle-associated proteins by integrated microfluidic multiplexed devises and in combination with our earlier data on auto-antibodies develop a multi-parameter kit to monitor disease progression. We are uniquely positioned to develop this technology and provide proof of concept in two extensively characterized longitudinal patient cohorts. Specifically, we will ask whether a combination of protein markers reflect the rate of progression to dementia or severe movement disability in carefully selected patient samples by correlating serial serum levels with detailed clinical assessments. In summary, we are seeking to solve a profound clinical challenge in the area of neurodegeneration by developing a unique multi-parameter receptor chemistry device that we believe will have unprecedented application and potency.

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  • Funder: UKRI Project Code: EP/N014189/1
    Funder Contribution: 1,218,040 GBP

    The relentless growth of the amount, variety, availability, and the rate of change of data has profoundly transformed essentially all aspects of human life. The Big Data revolution has created a paradox: While we create and collect more data than ever before, it is not always easy to unlock the information it contains. To turn the easy availability of data into a major scientific and economic advantage, it is imperative that we create analytic tools that would be equal to the challenge presented by the complexity of modern data. In recent years, breakthroughs in topological data analysis and machine learning have paved the way for significant progress towards creating efficient and reliable tools to extract information from data. Our proposal has been designed to address the scope of the call as follows. To 'convert the vast amounts of data produced into understandable, actionable information' we will create a powerful fusion of machine learning, statistics, and topological data analysis. This combination of statistical insight, with computational power of machine learning with the flexibility, scalability, and visualisation tools of topology will allow a significant reduction of complexity of the data under study. The results will be output in a form that is best suited to the intended application or a scientific problem at hand. This way, we will create a seamless pathway from data analysis to implementation, which will allow us to control every step of this process. In particular, the intended end user will be able to query the results of the analysis to extract the information relevant to them. In summary, our work will provide tools to extract information from complex data sets to support user investigations or decisions. It is now well established that a main challenge of Big Data is how 'to efficiently and intelligently extract knowledge from heterogeneous, distributed data while retaining the context necessary for its interpretation'. This will be addressed first of all by developing techniques for dealing with heterogenous data. A main strength of topology is its ability to identify simple components in complex systems. It can also provide guiding principles on how to combine elements to create a model of a complex system. It also provides numerical techniques to control the overall shape of the resulting model to ensure that it fits with the original constraints. We will use the particular strengths of machine learning, statistics and topology to identify the main properties of data, which will then be combined to provide an overall analysis of the data. For example, a collection of text documents can be analysed using machine learning techniques to create a graph which captures similarities between documents in a topological way. This is an efficient way to classify a corpus of documents according to a desired set of keywords. An important part of our investigation will be to develop robust techniques of data fusion. This is important in many applications. One of our main applications will address the problem of creating a set of descriptors to diagnose and treat asthma. There are five main pathways for clinical diagnosis of asthma, each supported by data. To create a coherent picture of the disease we need to understand how to combine the information contained in these separate data sets to create the so called 'asthma handprint' which is a major challenge in this part of medicine. Every novel methodology of data analysis has to prove that its 'techniques are realistic, compatible and scalable with real- world services and hardware systems'. The best way to do that is to engage from the outset with challenging applications , and to ensure that theoretic and modelling solutions fit well the intended applications. We offer a unique synergy between theory and modelling as well as world-class facilities in medicine and chemistry which will provide a strict test for our ideas and results.

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  • Funder: UKRI Project Code: EP/M02105X/1
    Funder Contribution: 348,059 GBP

    Context: The invention of artificial lighting, dating from Joseph Wilson Swan and Thomas Edison's seminal contributions to the invention and commercialization of the incandescent light bulb in 1879, is arguably one of the most important inventions of humankind. Artificial lighting permits most human activities to continue past sundown, thus immeasurably increasing worldwide human productivity. Though Edison's device was much brighter than candle lighting, it was inefficient, converting only 0.2% of electricity into light. Since this seminal invention, many other lighting devices have been developed, from the tungsten lamp, to fluorescent tubes to halogen lighting to light-emitting diodes (LEDs) to organic light-emitting diodes (OLEDs). With each further iteration in lighting technology, the quality (pureness of colour), power efficiency and brightness of the light produced by the device have each improved. Light emission also enables information displays, televisions and computer screens. Producing devices that are energy efficient is of particular importance as, according to the US Department of Energy, it is estimated that 1/3 of commercial electricity use and 10% of household electricity consumption in the United States alone is dedicated towards artificial lighting. Artificial lighting represents a $15 Billion market in the United States alone and almost $91 Billion worldwide, corresponding to 20% of total worldwide energy output. The environmental impact related to this energy consumption is enormous and is estimated to be responsible for 7% of global CO2 emissions. Whereas inorganic LED and organic or polymer OLED lighting is now the state of the art in artificial lighting, their high cost and small active surface area are still barriers to wide adoption. In fact, for large surface area outdoor lighting applications, low-pressure sodium lamps are still the technology of first choice. Within this context, there is an urgent need to find alternative artificial lighting technologies that are of lower production cost, more energy efficient, colour tunable and can be used in environments not currently accessible to current LED and OLED technologies. It is implicit that in a similar manner to OLEDs, such a new lighting technology would have applications in visual displays, telecommunication and sensors. Organometallic complexes capable of harnessing light and/or electrical current and transforming such energy into useful work are at the heart of many important applications. An application that is of particular interest to my research group is energy-efficient visual displays and flat panel lighting based on either a phosphorescent light-emitting electrochemical cell (LEEC) architecture or an OLED architecture. Currently, most ionic transition metal complex-based (iTMC) LEECs rely on the use of a charged iridium(III) complex as the luminophoric material. These complexes can be readily solution processed. Iridium complexes phosphoresce and thus the maximum photoluminescence quantum efficiency (PLQY) theoretically attainable is unity. The external quantum efficiency (EQE) of a LEEC device has been found to scale proportionately to the solid-state PLQY and as such bright devices are possible. Despite the advantages listed above, LEECs incorporating iTMCs have several weaknesses: (i) low EQE; (ii) limited stability of the device and (iv) colour quality, particularly with reference to blue light emission. This grant proposal targets the development blue-emitting iridium(III) cationic complexes that will act as a luminophoric material in both LEEC and OLED devices. The two main goals are: 1. to obtain a LEEC that emits brightly in the blue region of the spectrum and that is stable over thousands of hours and that can quickly illuminate upon the application of an external voltage; to produce higher performance deep blue emitting OLEDs.

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