The depletion of oil reserves, spiralling fuel costs, concerns about the security of global energy supplies, and belated worldwide recognition of fossil-fuel induced climate change have sparked an urgent and unprecedented demand for sustainable energy sources. Amongst all of these sources solar photovoltaic (PV) energy stands out as the only one with sufficient theoretical capacity to meet global electricity needs, but high costs of silicon based PV prohibit widespread take-up. In this programme, we focus on the development of organic photovoltaics (OPV) as a low cost technology with the potential to displace conventional power sources. The proposed programme links Imperial College London with four leading Chinese institutions, building on ICL's strengths in the physics and application of molecular electronic materials and devices and on our partners' strengths in speciality materials development and scale-up. A collaborative programme between the UK and China in this area is particularly timely, given the pressing need for alternative power sources that are capable of meeting the rapid development rate and large energy demand of China. Our proposal focuses on solution-processable organic molecules and polymers which share many of the chemical, structural and rheological properties of the inks used in conventional printing and which are amenable to large-scale production through the existing printing and coating industries. Although the project is focused on fundamental research in enhancing the efficiency and lifetime of OPV devices, the technology developed in this project will be compatible with high throughput manufacturing processes for large-scale production. In addition, the programme stands to benefit from the capabilities in China for transferring technological developments into local production. Solution processable OPV devices are typically based on the combination of an electron donor material (usually a conjugated polymer) and an electron acceptor (typically a fullerene derivative) in a bulk heterojunction structure. Absorbed photons of light create excitons which dissociate at the donor/acceptor interface to yield separated charges. The composite film is sandwiched between two different electrodes which drive photocurrent generation through the asymmetry in their electron affinities. The power conversion efficiency of OPV devices currently stands at 5%, and increases in both efficiency and lifetime are required to stimulate commercialization. Device models indicate that power conversion efficiencies of 8 % or more are available with polymer materials possessing sufficiently high oxidation potential and electrode materials with higher work function than those currently available. In this proposal, new polymer and electrode materials will be developed which possess the required properties for higher efficiency, new material which offer higher device stability will be designed and evaluated, and processing techniques compatible with large scale, high volume production will be developed. The programme brings together the expertise of the ICL team in device design, fabrication, characterisation and processing with the expertise of four leading Chinese institutions in synthesis of specialized organic semiconductors and their application in light emitting devices. Application of materials and device designs to light emission will also be investigated where appropriate, in order to explore the potential for energy savings in the lighting market.

Our ancestors communicated by scratching on the walls of caves, took navigational decisions by looking at the stars and made medical diagnoses simply by listening to patients. A great deal of information is captured in these simple data streams; our ability to capture, process, and decide actions based on information pervades all aspects of human life. Today, one has the same challenges but the information is much more voluminous and the expectations for the outcomes far higher. When we write using our finger on an iphone, as our voice is recorded for doctors to assess our mood, when video is analysed for abnormal actions, or as telescopes look deep into the galaxies for black holes, stars, planets,... technically sophisticated systems translate streams of sequential data into processed and recognised patterns that can be actioned. Our relatively new ability to offload data analysis onto massive digital systems is transforming our world. However huge challenges remain. Groundbreaking mathematical innovation is rapidly expanding our depth of understanding in one area. This project aims to build on successful pilot collaborations to create tools that really merge this new maths with the existing data science, and then apply them to exemplar challenges to produce a more effective abstraction of the "capture, process, and decide" process. The evidence is now overwhelming that dimension reduction and high order methods can capture sequential data very effectively. The maths underpinning this provided the crucial step that resulted in the extension of Newton's calculus beyond Itô's theory to rough paths; its mathematical articulation, the signature of a stream, has significantly enhanced deep learning methods to develop online handwriting recognition with state-of-the-art accuracy. This project has the goal of developing and embedding the abstract mathematics around rough paths and complex streamed data into a few of the richest challenges involved in the "capture, process, and decide" task. The investigators and the world-leading project partners are connected by the shared challenge of improving this task with complex datasets of importance in four contexts: * Health * Human interfaces * Human Actions * Observing the Universe The specific base challenges we start from are: 1) Use face, speech data, with other self-reported mood data to better detect when an intervention to support someone with mental illness is or is not working. 2) When a person writes (in Chinese) with their finger on a sat-nav device or mobile phone, to better transcribe this signal into digital characters accurately and economically, and to recognise who wrote it. 3) By observing evolving images in video data, develop tools that can classify the human actions. 4) Develop measurement instruments, and nonlinear processing techniques for astronomical data that improve detection sensitivity for transients and make new observations, e.g. for planets orbiting stars. The technical challenges are deeply interconnected. This project is a near unique opportunity to bring these together to produce a validated common methodology, and to create substantial cross-fertilization. One recent example of how this can happen is worth highlighting. In 2013, Ben Graham (then University of Warwick, now Facebook) used the signature to quantify strokes from Chinese hand-written characters parsimoniously and efficiently. The capture stage is subtle and has appreciably improved the accuracy of the recognition process; the China-based partners on this project subsequently created an app which has been downloaded millions of times. While the handwriting context for rough paths is very well defined and successful, understanding motion of people in videos is at a successful but early stage! The contexts are clearly related, and link through faces with the mental health challenge, and through occlusion with transients in astronomy. It is all joined up!

Coal will likely remain in an important position in the world energy mix in the foreseeable future because of its stability in supply and low cost in production. However, coal fired power generation industry has to substantially reduce its pollutant emission to survive in the future carbon constrained energy market. Oxycoal combustion with CO2 capture from flue gas is an emerging technology that can be adapted to both new and existing coal-fired power stations leading to a substantial reduction in carbon emission. Various assessments suggest that oxycoal technology is feasible and more favourable than other CCS (Carbon Capture and Storage) technologies, such as post-carbon capture. Currently, oxycoal combustion technology is still in its laboratory and technology demonstration stages and there is a significant knowledge gap in this new technology. A number of uncertainties exist in the combustion process where the changes in the heat transfer and combustion characteristics are, among others, the major concerns. Issues with system designs such as the optimum oxygen concentrations and its impact need to be investigated. Other complications include such as high concentrations of sulphur and mercury and changes in deposition and corrosion in the boiler and the downstream elements. If the technology is to be widely adopted in power generation industry for CCS then it is imperative that the impacts of these changes in the combustion processes are well understood, and that economic solutions to mitigating the problems encountered are identified.The proposed research aims to achieve an in-depth understanding of the oxycoal combustion processes, to develop key modelling capabilities for process prediction, and to provide guidelines to the power generation industry on design new and/or retrofitting existing power plant with oxycoal combustion technology. Because of the high costs of performing large scale tests, process modelling is commonly used as an alternative in technology development. In this project, advanced Computational Fluid Dynamics (CFD) techniques will be employed to perform detailed simulations on the oxycoal combustion processes. Because the oxycoal combustion is very different from the conventional air-coal combustion, new oxycoal specific CFD sub-programmes will be developed in order to achieve accurate modelling results. In parallel to the CFD modelling, well controlled practical measurements will be carried out to setup a comprehensive database on the oxycoal combustion and to provide validation to the CFD model development. In addition, a unique 3D flame monitoring system will be developed to monitor the oxycoal combustion flames. This integrated approach of advanced computational modelling, detailed experimental testing, and 3D flame imaging forms a mutual validating and complementary system to ensure a credible research output so that an in-depth understanding of the impact of oxycoal on flame characteristics, critical reaction kinetics, and devolatilsation and char reaction in the combustion processes may be achieved.The project consortium comprises of three academic centres of expertise from Leeds, Kent and the Imperial College. Three leading energy research institutes in China are joint force on the research. Collaborative research programmes have been arranged to carryout experimental testing and theoretical simulation in both UK and China. The project has also gained strong supported from leading power generation companies and commercial CFD developer providing practical advice on oxycoal combustion tests and combustion model development. The project provides a platform for the leading UK groups and leading Chinese partners to work together in tackling the significant issues related to the oxycoal combustion technology, which is expected to contribute significantly in cutting the CO2 and other greenhouse gases emissions in the power industry in both countries.

Coal will likely remain in an important position in the world energy mix in the foreseeable future because of its stability in supply and low cost in production. However, coal fired power generation industry has to substantially reduce its pollutant emission to survive in the future carbon constrained energy market. Oxycoal combustion with CO2 capture from flue gas is an emerging technology that can be adapted to both new and existing coal-fired power stations leading to a substantial reduction in carbon emission. Various assessments suggest that oxycoal technology is feasible and more favourable than other CCS (Carbon Capture and Storage) technologies, such as post-carbon capture. Currently, oxycoal combustion technology is still in its laboratory and technology demonstration stages and there is a significant knowledge gap in this new technology. A number of uncertainties exist in the combustion process where the changes in the heat transfer and combustion characteristics are, among others, the major concerns. Issues with system designs such as the optimum oxygen concentrations and its impact need to be investigated. Other complications include such as high concentrations of sulphur and mercury and changes in deposition and corrosion in the boiler and the downstream elements. If the technology is to be widely adopted in power generation industry for CCS then it is imperative that the impacts of these changes in the combustion processes are well understood, and that economic solutions to mitigating the problems encountered are identified.The proposed research aims to achieve an in-depth understanding of the oxycoal combustion processes, to develop key modelling capabilities for process prediction, and to provide guidelines to the power generation industry on design new and/or retrofitting existing power plant with oxycoal combustion technology. Because of the high costs of performing large scale tests, process modelling is commonly used as an alternative in technology development. In this project, advanced Computational Fluid Dynamics (CFD) techniques will be employed to perform detailed simulations on the oxycoal combustion processes. Because the oxycoal combustion is very different from the conventional air-coal combustion, new oxycoal specific CFD sub-programmes will be developed in order to achieve accurate modelling results. In parallel to the CFD modelling, well controlled practical measurements will be carried out to setup a comprehensive database on the oxycoal combustion and to provide validation to the CFD model development. In addition, a unique 3D flame monitoring system will be developed to monitor the oxycoal combustion flames. This integrated approach of advanced computational modelling, detailed experimental testing, and 3D flame imaging forms a mutual validating and complementary system to ensure a credible research output so that an in-depth understanding of the impact of oxycoal on flame characteristics, critical reaction kinetics, and devolatilsation and char reaction in the combustion processes may be achieved.The project consortium comprises of three academic centres of expertise from Leeds, Kent and the Imperial College. Three leading energy research institutes in China are joint force on the research. Collaborative research programmes have been arranged to carryout experimental testing and theoretical simulation in both UK and China. The project has also gained strong supported from leading power generation companies and commercial CFD developer providing practical advice on oxycoal combustion tests and combustion model development. The project provides a platform for the leading UK groups and leading Chinese partners to work together in tackling the significant issues related to the oxycoal combustion technology, which is expected to contribute significantly in cutting the CO2 and other greenhouse gases emissions in the power industry in both countries.

Coal will likely remain in an important position in the world energy mix in the foreseeable future because of its stability in supply and low cost in production. However, coal fired power generation industry has to substantially reduce its pollutant emission to survive in the future carbon constrained energy market. Oxycoal combustion with CO2 capture from flue gas is an emerging technology that can be adapted to both new and existing coal-fired power stations leading to a substantial reduction in carbon emission. Various assessments suggest that oxycoal technology is feasible and more favourable than other CCS (Carbon Capture and Storage) technologies, such as post-carbon capture. Currently, oxycoal combustion technology is still in its laboratory and technology demonstration stages and there is a significant knowledge gap in this new technology. A number of uncertainties exist in the combustion process where the changes in the heat transfer and combustion characteristics are, among others, the major concerns. Issues with system designs such as the optimum oxygen concentrations and its impact need to be investigated. Other complications include such as high concentrations of sulphur and mercury and changes in deposition and corrosion in the boiler and the downstream elements. If the technology is to be widely adopted in power generation industry for CCS then it is imperative that the impacts of these changes in the combustion processes are well understood, and that economic solutions to mitigating the problems encountered are identified.The proposed research aims to achieve an in-depth understanding of the oxycoal combustion processes, to develop key modelling capabilities for process prediction, and to provide guidelines to the power generation industry on design new and/or retrofitting existing power plant with oxycoal combustion technology. Because of the high costs of performing large scale tests, process modelling is commonly used as an alternative in technology development. In this project, advanced Computational Fluid Dynamics (CFD) techniques will be employed to perform detailed simulations on the oxycoal combustion processes. Because the oxycoal combustion is very different from the conventional air-coal combustion, new oxycoal specific CFD sub-programmes will be developed in order to achieve accurate modelling results. In parallel to the CFD modelling, well controlled practical measurements will be carried out to setup a comprehensive database on the oxycoal combustion and to provide validation to the CFD model development. In addition, a unique 3D flame monitoring system will be developed to monitor the oxycoal combustion flames. This integrated approach of advanced computational modelling, detailed experimental testing, and 3D flame imaging forms a mutual validating and complementary system to ensure a credible research output so that an in-depth understanding of the impact of oxycoal on flame characteristics, critical reaction kinetics, and devolatilsation and char reaction in the combustion processes may be achieved.The project consortium comprises of three academic centres of expertise from Leeds, Kent and the Imperial College. Three leading energy research institutes in China are joint force on the research. Collaborative research programmes have been arranged to carryout experimental testing and theoretical simulation in both UK and China. The project has also gained strong supported from leading power generation companies and commercial CFD developer providing practical advice on oxycoal combustion tests and combustion model development. The project provides a platform for the leading UK groups and leading Chinese partners to work together in tackling the significant issues related to the oxycoal combustion technology, which is expected to contribute significantly in cutting the CO2 and other greenhouse gases emissions in the power industry in both countries.