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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.

Two of the most critical global challenges currently being faced are energy security and climate change. In the UK, more than £100 bn of investment in new UK power stations and grid infrastructure is projected within the next decade, both to replace ageing plant and to allow for the incorporation of renewable sources. Such changes will involve a paradigm shift in the ways in which we generate and transmit electricity. Since a central element of all items of power plant is electrical insulation, meeting our future challenges through the deployment of new innovative plant, this will require the development and exploitation of new high performance insulation material systems. Polymer nanocomposites have demonstrated clear potential, but the lack of detailed understanding of the underlying physics and chemistry is a major impediment to the technological realisation of this potential. In certain laboratory studies, nanodielectrics materials have out-performed unfilled and traditional micro-composite insulating materials. However, entirely contrary results have also been elsewhere. Undoubtedly, this variability in macroscopic behaviour comes about as a consequence of our inability to define and control the key factors that dictate the dielectric behaviour of nanocomposites. The overarching aim of this project is to resolve this issue such that the potential of dielectric nanocomposites - nanodielectrics - can be fully exploited. As such, the project is totally aligned with the EPSRC Materials for Energy theme in which it is accepted that "in the field of advanced materials it will be necessary to strengthen approaches to the rational design and characterisation of advanced materials and their integration into structures and systems". It also aligns with the Advanced Materials theme of the "Eight Great Technologies", it which it is accepted that "these materials are essential to 21st century manufacturing in a UK market worth £170 billion per annum and representing 15 per cent of GDP". Our research hypothesis is that the macroscopic properties of nanodielectrics cannot be reliably controlled without understanding the processes that occur at the interfaces between the matrix material and the nanoparticles, because these regions directly affect two critical issues. First, interfacial interactions will affect the nanoparticle dispersion, which has a major bearing on many physical properties and, second, the nature of the interface determines the local density of states in the system, and thereby the material's overall electrical characteristics. To understand such local processes is challenging and we propose to do this through a combination of computation simulation and experiment, where both aspects are closely aligned, thereby allowing the simulation to direct experiment and the experimental result to refine the simulation. The work programme has been divided in 3 distinct themes, which will progressively move the work from fundamentals to exploitation. Theme 1 will therefore concentrate on model systems, where simulation and experiment can be most closely aligned. Theme 2 will then seek to deploy the key messages to the development of technologically relevant systems and processes. Throughout, Theme 3 will engage with a range of stakeholders that will range from key industry players (equipment manufacturer s, energy utilities, standards bodies) to the general public t maximise the reach and significance of its ultimate impact (economic, environmental, societal). We see the involvement of our Industrial Users Group as being particularly important, both in helping to guide the project and in terms of ensuring acceptance of the technologies that will ultimately arise.

We are all familiar with the concept of travel, and visiting York from Glasgow is conceptually a trial matter. When we reflect on this process, however, there are lots of potential questions we might ask about the mode of transport, the route and the potential to get lost. A similar range of questions could be asked about chemical reactions. We select starting materials and seek to transform them into products. The route we choose is equally complex. Now, however, the participants are much smaller and very special methods are needed to view them. Furthermore, with an optimal solution we get the most product from the least starting material using the least amount of energy and other resources as possible. If think of a reaction that is undertaken on the 1,000,000 tonne scale it is also clearly vital to minimise waste. In Chemistry, there is a very special and often expensive method called nuclear magnetic resonance spectroscopy (NMR) that allows us to take pictures of the participants as they travel from starting materials to products. This methods is normally very insensitive and hence very expensive large magnets are required. If we want to use this technology to deliver clean and efficient chemistry on an industrial scale we need to find a way to work with smaller lower cost magnets, ideally using the Earth's magnetic field. In this project we aim to develop a new method using such low-magnetic field NMR devices to follow the route taken by molecules during their conversion into high value products in both laboratory and industrial settings. We will use a special form of hydrogen gas, known as parahydrogen to increase the sensitivity of the NMR measurement to a level that will allow to achieve this goal. Parahydrogen was actually the fuel of the space shuttle and one might view it here as acting like a molecular microscope whilst at the same time removing (filtering) any unwanted signals from spectators to the reaction of interest. We will build-up our understanding of the reactions route by taking our NMR pictures which contains precise information about the identity of the participants (molecules) at different times after the start of the reaction. This means that we will monitor the same process several times in order to produce the necessary molecular level picture that will ultimately allow us to optimise our chosen reaction. The enhanced level of information that will be provided by our new device will enable scientists and industrialists to develop and optimise reactions in a way that was previously impossible and hence contribute more positively to society.

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.

We propose to prepare and study a new class of synthetic ion channels based on dynamic metal-organic complexes that possess a pore-like central channel that will allow for substrate transport across a lipid bilayer. These complexes are obtained through the condensation of simple organic building blocks around octahedral metal ion templates. The modular nature of these complexes and the dynamic nature of their imine bonds will allow us to tune the assemblies to confer different physical properties upon them, while retaining their overall structures. Through tuning we will identify the key characteristics of complexes that can be inserted into lipid bilayers. This project builds upon preliminary investigations that have shown that heptyl-chain-bearing derivatives allowed chloride ions to pass across a membrane, providing a point of departure for our investigations. In other key precedent work we established that it is possible to induce reconstitution of the complexes into entirely different structures in the presence of different templating anions. We will investigate ways to exploit this phenomenon as an approach to controlling flux across a membrane by reversibly triggering reconstitution to form complexes that do not possess central channels, thus inhibiting ion transport. Development of these tuneable, gating ion channels will pave the way to new industrial processes that are driven by the effective separation of high value compounds from impure mixtures, and new chemical transformations involving the selective gating of intermediate species between vesicular reaction chambers. In future, our technologies may also facilitate new treatments for those who suffer from forms of channelopathy.

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.

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.

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.

The overall goal is to synthesise, characterise and test Metal- Organic Frameworks (MOF) for Gas separations of interest in the petrochemicals industry. Specifically, the work will initially focus on producing several members of a family that have been shown to exhibit good potential in certain gas separations of interest. MOFs containlng single- or mixed metals will be investigated in order to try to fine tune this MOF for specific gas separations. Subsequently, other MOF systems wlll be explored based on the results of modeling studies. Overall, the materials will be tested through dynamlc and equilibrium adsorption tests to estimate their performance. This project relies on: (i) developing materials relevant to the energy sector and (ii) studying their surface interactions with gas molecules. lt is thus directly llnked to the EPSRC research areas of Materials Engineerlng, Surface Science and Energy Efficiency.

The sulfonyl group, -SO2-, is frequently represented in both agrochemical and pharmaceutical active ingredients. This collaborative proposal will deliver organophosphorus-based bioisosteric mimics of this important functional group giving access to new chemical space and IP opportunities. This will be achieved through the development of new synthesis methods for phosphines, phosphonates and phosphinates that by-pass toxic PCl3 and other difficult-to-handle halophosphine intermediates. The project falls within the EPSRC's remit, specifically involving research in the areas of Synthetic Organic Chemistry and Chemical Biology and Biological Chemistry.