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14 Projects, page 1 of 2

  • Canada
  • UK Research and Innovation
  • 2026

10
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  • Funder: UKRI Project Code: BB/W018721/1
    Funder Contribution: 51,020 GBP
    Partners: University of Toronto, Celtic Renewables Ltd, LanzaTech, NTU, Metabolic Explorer, PhaSE Biolabs Ltd

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: EP/X02251X/1
    Funder Contribution: 313,239 GBP
    Partners: KCL, House of world Cultures, University of Toronto

    WOMUSIRAN investigates links between gender, Islam, migration and cultural appropriation, through the prism of Western art music in Iran. It traces the fate of female composers, teachers, scholars and practitioners, whose work and careers fell victim to the 1979 Revolution and to the subsequent tightened controls on women and music-making. The project presents a bottom-up history of the role of those pioneering female musicians in shaping Iran's cultural policies, impacting post-1979 diasporic communities, and contributing to present-day possibilities for women in Iran's re-emergent musical and cultural life. WOMUSIRAN resonates strongly with the current situation in Afghanistan. The project's objectives are to undertake a critical and contextual assessment of primary and secondary sources, to construct an oral history of key female musicians in Iran and diasporic communities, and to conduct comparative and contextual assessment of works by the case-study musicians. A further objective will be to locate these case studies within the frame of Intangible Cultural Heritage. These objectives will be achieved through an interdisciplinary methodology that draws on (ethno-)musicology, migration, gender and feminist studies, area studies and human rights, drawing on interviews, testimonies and archival material, alongside textual and musical assessment. The project will be carried out at the world-leading Centre for Iranian Studies at the University of Toronto (outgoing phase) and at the Music Department of King's College, London (return phase), with a two-month secondment at Silkroad (Boston) and a six-month placement at the Maison des Cultures du Monde (Paris). The outcome will be intersectoral, breaking down boundaries between academics and practitioners, enabling diasporic musicians to reconnect with their roots, giving a voice to a new generation of female and LGBTQ+ musicians, and creating channels of communication between those in Iran and the diaspora.

  • Funder: UKRI Project Code: EP/W002973/1
    Funder Contribution: 4,300,500 GBP
    Partners: University of Toronto, Manchester Cancer Research Centre, Astrazeneca Plc, University of Cambridge, GENTCORP LIMITED, Aalto University, Delft University of Technology, Apis Assay Technologies Ltd., University of Salford, IBM (United Kingdom)...

    Machine learning offers great promise in helping us solve problems by automatically learning solutions from data, without us having to specify all details of the solution as in earlier computational approaches. However, we still need to tell machine learning systems what problems we want them to solve, and this is currently undertaken by specifying desired outcomes and designing objective functions and rewards. Formulating the rewards for a new problem is not easy for us as humans, and is particularly difficult when we only partially know the goal, as is the case at the beginning of scientific research. In this programme we develop ways for machine learning systems to help humans to steer them in the process of collecting more information by designing experiments, interpreting what the results mean, and deciding what to measure next, to finally reach a conclusion and a trustworthy solution to the problem. The machine learning techniques will be developed first for three practically important problems and then generalized to be broadly applicable. The first is diagnosis and treatment decision making in personalized medicine, the second steering of scientific experiments in synthetic biology and drug design, and the third design and use of digital twins in designing physical systems and processes. An AI centre of excellence will be established at the University of Manchester, in collaboration with the Turing Institute and a number of partners from the industry and healthcare sector, and with strong connections to the networks of best national and international AI researchers.

  • Funder: UKRI Project Code: EP/V001914/1
    Funder Contribution: 7,671,800 GBP
    Partners: University of Toronto, Compound Semiconductor Centre, University of Salford, Qioptiq Ltd, NPL, BAE Systems, University of Melbourne, Airbus Defence and Space, SEAGATE TECHNOLOGY IRELAND, BIOTEN Ltd....

    Development of materials has underpinned human and societal development for millennia, and such development has accelerated as time has passed. From the discovery of bronze through to wrought iron and then steel and polymers the visible world around has been shaped and built, relying on the intrinsic properties of these materials. In the 20th century a new materials revolution took place leading to the development of materials that are designed for their electronic (e.g. silicon), optical (e.g. glass fibres) or magnetic (e.g. recording media) properties. These materials changed the way we interact with the world and each other through the development of microelectronics (computers), the world wide web (optical fibre communications) and associated technologies. Now, two decades into the 21st century, we need to add more functionality into materials at ever smaller length-scales in order to develop ever more capable technologies with increased energy efficiency and at an acceptable manufacturing cost. In pursuing this ambition, we now find ourselves at the limit of current materials-processing technologies with an often complex interdependence of materials properties (e.g. thermal and electronic). As we approach length scales below 100s of nanometres, we have to harness quantum effects to address the need for devices with a step-change in performance and energy-efficiency, and ultimately for some cases the fundamental limitations of quantum mechanics. In this programme grant we will develop a new approach to delivering material functionalisation based on Nanoscale Advanced Materials Engineering (NAME). This approach will enable the modification of materials through the addition (doping) of single atoms through to many trillions with extreme accuracy (~20 nanometres, less than 1000th the thickness of a human hair). This will allow us to functionalise specifically a material in a highly localised location leaving the remaining material available for modification. For the first time this will offer a new approach to addressing the limitations faced by existing approaches in technology development at these small length scales. We will be able to change independently a material's electronic and thermal properties on the nanoscale, and use the precise doping to deliver enhanced optical functionality in engineered materials. Ambitiously, we aim to use NAME to control material properties which have to date proven difficult to exploit fully (e.g. quantum mechanical spin), and to control states of systems predicted but not yet directly experimentally observed or controlled (e.g. topological surface states). Ultimately, we may provide a viable route to the development of quantum bits (qubits) in materials which are a pre-requisite for the realisation of a quantum computer. Such a technology, albeit long term, is predicted to be the next great technological revolution NAME is a collaborative programme between internationally leading UK researchers from the Universities of Manchester, Leeds and Imperial College London, who together lead the Henry Royce Institute research theme identified as 'Atoms to Devices'. Together they have already established the required substantial infrastructure and state-of-the-art facilities through investment from Royce, the EPSRC and each University partner. The programme grant will provide the resource to assemble the wider team required to deliver the NAME vision, including UK academics, research fellows, and postdoctoral researchers, supported by PhD students funded by the Universities. The programme grant also has significant support from wider academia and industry based both within the UK and internationally.

  • Funder: UKRI Project Code: NE/T01279X/1
    Funder Contribution: 2,130,390 GBP
    Partners: Forests, Resources and People, University of Minnesota, UNIVERSIDADE ESTADUAL DE MONTES CLAROS, Kenya Forestry Research Institute, University of Edinburgh, Instituto Federal, UBC, Federal University of Lavras, Pondicherry University, Higher Institute of Educational Sciences...

    The ecosystems of the dry tropics are in flux: the savannas, woodlands and dry forests that together cover a greater area of the globe than rainforests are both a source of carbon emissions due to deforestation and forest degradation, and also a sink due to the enhanced growth of trees. However, both of these processes are poorly understood, in terms of their magnitude and causes, and the net carbon balance and its future remain unclear. This gap in knowledge arises because we do not have a systematic network of observations of vegetation change in the dry tropics, and thus have not, until now, been able to use observations of how things are changing to understand the processes involved and to test key theories. Satellite remote sensing, combined with ground measurements, offers the ideal way to overcome these challenges, as it can provide regular, consistent monitoring at relatively low cost. However, most ecosystems in the dry tropics, especially savannas, comprise a mixture of grass and trees, and many optical remote sensing approaches (akin to enhanced versions of the sensors on digital cameras) struggle to distinguish changes between the two. Long wavelength radar remote sensing avoids this problem as it is insensitive to the presence of leaves or grass, and also is not affected by clouds, smoke or the angle of the sun, all of which complicate optical remote sensing. Radar remote sensing is therefore ideal to monitor tree biomass in the dry tropics. We have successfully demonstrated that such data can be used to accurately map woody biomass change for all 5 million sq km of southern Africa. In SECO we will create a network of over 600 field plots to understand how the vegetation of the dry tropics is changing. and complement this with radar remote sensing to quantify how the carbon cycle of the dry tropics has changed over the last 15 years. This will provide the first estimates of key carbon fluxes across all of the dry tropics, including the amount of carbon being released by forest degradation and deforestation and how much carbon is being taken up by the intact vegetation in the region. By understanding where these processes are happening, we will improve our knowledge of the processes involved. W will use these new data to improve the way we model the carbon cycle of the dry tropics, and test key theories. The improved understanding, formalised into a model, will be used to examine how the dry tropics will respond to climate change, land use change and the effects of increasing atmospheric CO2. We will then be able to understand whether the vegetation of the dry tropics will mitigate or exacerbate climate change, and we will learn what we need to do to maintain the structure of the dry tropics and preserve its biodiversity. Overall, SECO will allow us to understand how the vegetation of the dry tropics is changing, and the implications of this for the global carbon cycle, the ecology of savannas and dry forests, and efforts to reduce climate change. The data we create, and the analyses we conduct will be useful to other researchers developing methods to monitor vegetation from satellites, and also to those who model the response of different ecosystems to climate and other changes. Forest managers, ecologists and development practitioners can use the data to understand which parts of the world's savannas and dry forests are changing most, and how these changes might be managed to avoid negative impacts that threaten biodiversity and the livelihoods of the 1 billion, mostly poor, rural people who live in this region.

  • Funder: UKRI Project Code: BB/V018035/1
    Funder Contribution: 30,612 GBP
    Partners: BBK, SFU

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: EP/X012603/1
    Funder Contribution: 1,493,850 GBP
    Partners: KCL, University of Toronto, Polytechnic University of Milan, The Alan Turing Institute, Medical University of Graz

    Modelling and simulation play important roles in designing everything from planes to cars to bridges. However, advances in connectivity and computing now enable models to be linked directly to a specific object or system, creating a "digital twin". Digital twins represent a computational surrogate for a particular object and are updated through time as more information becomes available. However, digital twins are not limited to manufactured objects alone. This project aims to develop digital twins of patients, where a model will track a patient through time. We focus on making digital twins of patients' hearts using detailed imaging data sets over the period of a clinical trial. This is the first step towards models that are updated in real-time, track the patient throughout their life and directly feed back into informing patient care. The digital twin approach builds on patient-specific computer models of the heart that are currently being evaluated to guide procedures in the UK at King's College London and in the US. These models are designed to optimise treatments for a specific patient's pathophysiology but only simulate a small number of heartbeats. Digital twins, which track a patient through time, will forecast disease progression and response to therapy. This represents the next step in simulation guided therapy, where the optimal treatment and, importantly, when to deliver it, will be predicted. This project will address the technical challenges in calibrating computer models of large numbers of patients, how to efficiently update these models through time as more data becomes available, how to analyse images of the heart recorded over the duration of a clinical trial and how to predict complex changes in shape and function of the heart. The approaches will be applied to study three patient groups in three studies. First, we will test if multi-scale cardiac biomechanics models can identify common causes of pump dysfunction in heart failure patients. Second, we will test if digital twins can predict which patients who have recovered from heart failure can stop their heart failure mediation. Thirdly, we will test if digital twin forecasts can be used to predict recovery and pre-empt the need for advanced heart failure therapy in newly diagnosed heart failure patients. This will provide the first demonstration of cardiac biomechanics digital twins using real clinical data to answer important clinical questions.

  • Funder: UKRI Project Code: NE/W006448/1
    Funder Contribution: 603,466 GBP
    Partners: Aurora Research Institute, TOWSON UNIVERSITY, AMHERST COLLEGE, University of Gothenburg, UAF, NAU, University of Lapland, University of Edinburgh, ORNL, COLGATE UNIVERSITY...

    The TundraTime project will address climate change impacts in tundra ecosystems including how warming is shifting tundra plant phenology - the timing of life events such as bud burst or flowering - and productivity - the increase in plant growth and biomass over time. We will answer the fundamental research question of whether climate warming is leading to longer tundra growing seasons and thus increasing plant productivity in the Arctic, with important implications for carbon cycling and wildlife. Critical knowledge gaps in the field of global change ecology are what role the high latitudes will play in the global carbon cycle and how Arctic food webs will be restructured in the future with accelerated warming. A critical unknown is whether shifting plant phenology is altering tundra carbon cycling and wildlife habitats. Projections of climate feedbacks from high-latitude ecosystems remain uncertain as we do not yet know if carbon losses from warming soils will be offset by increases in tundra productivity. Tundra plant responses to warming could be key for understanding the fate of wildlife populations in a rapidly changing Arctic. Forty years of satellite and field observations have revealed widespread changes in the tundra's surface that protects large stocks of frozen carbon below. Field studies indicate that plants are coming into leaf earlier in spring, bare ground is becoming vegetated, and plants are now growing taller. While there is scientific consensus that climate change is reshaping Arctic ecosystems, great uncertainty persists about what the greening observed from space means in terms of change on-the-ground. The TundraTime project will answer the fundamental research questions of whether climate warming is leading to longer periods of plant growth and increases in plant productivity in the Arctic. We will test specific hypotheses of whether tundra ecosystems are experiencing: A) increases in productivity, B) shifts in phenology and C) asynchrony of above- and below-ground plant growth. To explore these questions, we will integrate high-resolution drone and time-lapse camera imagery with satellite and in-situ data from 12 focal Arctic research sites. Our findings will inform biome-wide projections of tundra vegetation change and global-scale predictions of climate feedbacks to unprecedented rates of warming. If tundra plant productivity is responding directly to the warmer and longer Arctic growing seasons then tundra productivity will trap more carbon in tundra ecosystems and restructure wildlife habitats. However, if instead tundra plant growing seasons are shifting earlier, then projections of increases in tundra vegetation with warming may be overestimates and earlier timing of key forage could alter migratory behaviour and ultimately wildlife populations. And, if the above- and below-ground responses of tundra plants are asynchronous, plant growth in the now extended snow-free autumns could instead be occurring below ground, which would overturn how satellite data and Earth-system models estimate plant productivity and carbon storage in warming tundra ecosystems. The TundraTime project will test the drivers of Arctic greening by resolving the uncertainty around what role shifting plant phenology plays in the increased tundra productivity with warming. This research will bridge critical scale gaps to resolve the uncertainty between satellite and in-situ observations of changes in the timing of plant growth with accelerating climate warming.

  • Funder: UKRI Project Code: NE/W003104/1
    Funder Contribution: 450,327 GBP
    Partners: University of Leicester, Nagoya University, University of Oulu, FMI, UNIS, UAF, University of Saskatchewan, Beihang University, GFZ German Research, INGV - Ist. Naz. Geofisica Vulcanologia...

    The UK along with the rest of the world is becoming increasingly dependent on technological systems, including satellite communications, global positioning systems, and power grids, that are at risk from space weather. Many space weather hazards originate in the ionosphere, the ionised upper part of the atmosphere at altitudes of 90 km and above, where solar wind energy channelled by the Earth's magnetic field can cause a variety of unpredictable and deleterious effects. It causes electrical currents to flow, which heat the atmosphere in a process known as Joule heating, which in turn can cause the atmosphere to expand upwards, producing drag on satellites, hence making their orbits harder to predict and reducing their lifetimes. It produces horizontal motions of the ionosphere which modify the neutral winds in the thermosphere through friction. It produces the auroras, associated with particle precipitation from the magnetosphere above, which modify the ionospheric structure. Moreover, it gives rise to plasma instabilities which cause the ionosphere to become corrugated, scattering radio waves from satellites consequently disturbing communications and GPS. Although the large-scale distribution of such space weather hazards is relatively well reproduced in global circulation models, the physics occurring on spatial scales smaller than the model grid is poorly understood, which holds back improvements in forecasting. The FINESSE project will exploit a new and unique NERC-funded incoherent scatter radar system, EISCAT_3D, located in northern Scandinavia, to study these sub-grid space weather scales. EISCAT_3D will be able to determine the ionospheric structure in a box roughly 200 km to a side horizontally and 800 km vertically, at an unprecedented spatial and temporal resolution, to image the processes leading to space weather effects. FINESSE will also exploit a next-generation coherent scatter radar to measure ionospheric motions, three neutral wind imagers to measure the interaction between the thermosphere and the ionosphere, three all-sky auroral cameras to view regions of precipitation from the magnetosphere above, a fine-scale auroral imager to observe auroral structures on spatial and temporal scales even finer than EISCAT_3D can probe, and a radio telescope and network of GPS receivers to look at the scintillation of radio signals from both cosmic sources and satellites. The main aims of FINESSE are as follows. 1) To determine the small-scale sources of Joule heating, to place these within the context of the larger picture of polar auroral disturbances, to determine the link between Joule heating and satellite drag, and to incorporate these results to improve forecast models. 2) To determine the cause of small-scale ionospheric structuring, and to understand how this leads to scintillation of radio signals. 3) To probe auroral dynamics at the very smallest temporal and spatial scales to understand the physics of coupling between the magnetosphere and ionosphere, the role auroral processes play in heating and structuring the ionosphere and atmosphere, and the instability that leads to substorms (explosive releases of energy into the nightside auroral ionosphere). FINESSE will liaise with space weather forecasters and other stakeholders to disseminate this greater understanding of small-scale processes in producing space weather hazards and to translate it into significant economic benefit to the UK.

  • Funder: UKRI Project Code: NE/W006650/1
    Funder Contribution: 652,019 GBP
    Partners: University of Gothenburg, McGill University, Swansea University, Natural England, SNH, JNCC

    Human activities have already raised global species extinction rates a thousand-fold and have pushed an additional million species towards extinction. Biodiversity is also rapidly changing on more local scales as climate change drives the redistribution of species, and pressures such as overharvesting and habitat fragmentation intensify in many areas. Understanding how biodiversity influences ecosystem functions, such as carbon capture and fisheries productivity, is a crucial challenge directly relevant to meeting the UN sustainable development goals, and UK policy imperatives of harnessing biodiversity to achieve sustainable economic growth and using nature-based solutions to help meet 'net-zero' emissions by 2050. Since the mid- 1990s, several hundred experiments have tested how changes in biodiversity influence ecosystem functions and services, with many studies indicating that biodiversity loss does not reduce functioning as long as the single best-performing species is retained. However, these studies have focused on local-scale interactions between species in small habitat units such as grassland plots, field enclosures, or aquarium tanks; we therefore lack studies that consider BEF relationships on the larger landscape-, regional- or even national- scales most relevant to the public, ecosystem managers, and policy makers. Ecological theory suggests that biodiversity is more important for ecosystem services as scale increases due to greater environmental variation, but it cannot currently be evaluated in real ecosystems because we lack BEF studies across scales and environmental gradients. In this project we aim to bridge the gap between experiments and relevant larger scales by using Great Britain's intertidal forests as a model system. These highly productive and valuable ecosystems occur extensively around the GB's varied and complex coastlines and are formed by a manageable suite of seaweed species which can be easily manipulated across multiple distinct environmental gradients. To meet our overall aim, we will incorporate multiple environmental factors into experiments, observations and models delivered across three inter-linked work packages which together provide a generalised approach and scaling relationships for BEF. Our first work package uses a 100km stretch of the south Wales coastline - which incorporates gradients in wave exposure and turbidity - as an accessible template to experimentally test the causal effect of intertidal forest biodiversity on ecosystem functioning from small patches to the whole coastline. Our second package combines a network of standardised observations in intertidal forests around GB, with satellite remote sensing and statistical modelling, to test how BEF relationships scale-up -- from 1 m to 1000km scales -- in naturally assembled communities. The third and final work package uses the new experimental and observational data to inform dynamic models, allowing us to test how species traits such as dispersal and environmental tolerances interacts with environmental variability to determine BEF relationships across scales. A key innovation here is the explicit - and empirically informed - integration of spatial environmental variability in multiple environmental factors. These will be generalised to represent how the environment varies in a range of different ecosystems from forests, to agricultural landscapes, and to coral reefs. The advancement of our project aim will deliver a revised appreciation of the role of diversity in ecosystems and demonstrate a generalizable approach for upscaling biodiversity - ecosystem functioning relationships. We anticipate that this will feed into predictions for how biodiversity changes will influence ecosystem functioning and services on large, relevant- scales, in intertidal forests and beyond, with a range of applications from natural capital models, to the design of large-scale ecosystem restoration projects.

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14 Projects, page 1 of 2
  • Funder: UKRI Project Code: BB/W018721/1
    Funder Contribution: 51,020 GBP
    Partners: University of Toronto, Celtic Renewables Ltd, LanzaTech, NTU, Metabolic Explorer, PhaSE Biolabs Ltd

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: EP/X02251X/1
    Funder Contribution: 313,239 GBP
    Partners: KCL, House of world Cultures, University of Toronto

    WOMUSIRAN investigates links between gender, Islam, migration and cultural appropriation, through the prism of Western art music in Iran. It traces the fate of female composers, teachers, scholars and practitioners, whose work and careers fell victim to the 1979 Revolution and to the subsequent tightened controls on women and music-making. The project presents a bottom-up history of the role of those pioneering female musicians in shaping Iran's cultural policies, impacting post-1979 diasporic communities, and contributing to present-day possibilities for women in Iran's re-emergent musical and cultural life. WOMUSIRAN resonates strongly with the current situation in Afghanistan. The project's objectives are to undertake a critical and contextual assessment of primary and secondary sources, to construct an oral history of key female musicians in Iran and diasporic communities, and to conduct comparative and contextual assessment of works by the case-study musicians. A further objective will be to locate these case studies within the frame of Intangible Cultural Heritage. These objectives will be achieved through an interdisciplinary methodology that draws on (ethno-)musicology, migration, gender and feminist studies, area studies and human rights, drawing on interviews, testimonies and archival material, alongside textual and musical assessment. The project will be carried out at the world-leading Centre for Iranian Studies at the University of Toronto (outgoing phase) and at the Music Department of King's College, London (return phase), with a two-month secondment at Silkroad (Boston) and a six-month placement at the Maison des Cultures du Monde (Paris). The outcome will be intersectoral, breaking down boundaries between academics and practitioners, enabling diasporic musicians to reconnect with their roots, giving a voice to a new generation of female and LGBTQ+ musicians, and creating channels of communication between those in Iran and the diaspora.

  • Funder: UKRI Project Code: EP/W002973/1
    Funder Contribution: 4,300,500 GBP
    Partners: University of Toronto, Manchester Cancer Research Centre, Astrazeneca Plc, University of Cambridge, GENTCORP LIMITED, Aalto University, Delft University of Technology, Apis Assay Technologies Ltd., University of Salford, IBM (United Kingdom)...

    Machine learning offers great promise in helping us solve problems by automatically learning solutions from data, without us having to specify all details of the solution as in earlier computational approaches. However, we still need to tell machine learning systems what problems we want them to solve, and this is currently undertaken by specifying desired outcomes and designing objective functions and rewards. Formulating the rewards for a new problem is not easy for us as humans, and is particularly difficult when we only partially know the goal, as is the case at the beginning of scientific research. In this programme we develop ways for machine learning systems to help humans to steer them in the process of collecting more information by designing experiments, interpreting what the results mean, and deciding what to measure next, to finally reach a conclusion and a trustworthy solution to the problem. The machine learning techniques will be developed first for three practically important problems and then generalized to be broadly applicable. The first is diagnosis and treatment decision making in personalized medicine, the second steering of scientific experiments in synthetic biology and drug design, and the third design and use of digital twins in designing physical systems and processes. An AI centre of excellence will be established at the University of Manchester, in collaboration with the Turing Institute and a number of partners from the industry and healthcare sector, and with strong connections to the networks of best national and international AI researchers.

  • Funder: UKRI Project Code: EP/V001914/1
    Funder Contribution: 7,671,800 GBP
    Partners: University of Toronto, Compound Semiconductor Centre, University of Salford, Qioptiq Ltd, NPL, BAE Systems, University of Melbourne, Airbus Defence and Space, SEAGATE TECHNOLOGY IRELAND, BIOTEN Ltd....

    Development of materials has underpinned human and societal development for millennia, and such development has accelerated as time has passed. From the discovery of bronze through to wrought iron and then steel and polymers the visible world around has been shaped and built, relying on the intrinsic properties of these materials. In the 20th century a new materials revolution took place leading to the development of materials that are designed for their electronic (e.g. silicon), optical (e.g. glass fibres) or magnetic (e.g. recording media) properties. These materials changed the way we interact with the world and each other through the development of microelectronics (computers), the world wide web (optical fibre communications) and associated technologies. Now, two decades into the 21st century, we need to add more functionality into materials at ever smaller length-scales in order to develop ever more capable technologies with increased energy efficiency and at an acceptable manufacturing cost. In pursuing this ambition, we now find ourselves at the limit of current materials-processing technologies with an often complex interdependence of materials properties (e.g. thermal and electronic). As we approach length scales below 100s of nanometres, we have to harness quantum effects to address the need for devices with a step-change in performance and energy-efficiency, and ultimately for some cases the fundamental limitations of quantum mechanics. In this programme grant we will develop a new approach to delivering material functionalisation based on Nanoscale Advanced Materials Engineering (NAME). This approach will enable the modification of materials through the addition (doping) of single atoms through to many trillions with extreme accuracy (~20 nanometres, less than 1000th the thickness of a human hair). This will allow us to functionalise specifically a material in a highly localised location leaving the remaining material available for modification. For the first time this will offer a new approach to addressing the limitations faced by existing approaches in technology development at these small length scales. We will be able to change independently a material's electronic and thermal properties on the nanoscale, and use the precise doping to deliver enhanced optical functionality in engineered materials. Ambitiously, we aim to use NAME to control material properties which have to date proven difficult to exploit fully (e.g. quantum mechanical spin), and to control states of systems predicted but not yet directly experimentally observed or controlled (e.g. topological surface states). Ultimately, we may provide a viable route to the development of quantum bits (qubits) in materials which are a pre-requisite for the realisation of a quantum computer. Such a technology, albeit long term, is predicted to be the next great technological revolution NAME is a collaborative programme between internationally leading UK researchers from the Universities of Manchester, Leeds and Imperial College London, who together lead the Henry Royce Institute research theme identified as 'Atoms to Devices'. Together they have already established the required substantial infrastructure and state-of-the-art facilities through investment from Royce, the EPSRC and each University partner. The programme grant will provide the resource to assemble the wider team required to deliver the NAME vision, including UK academics, research fellows, and postdoctoral researchers, supported by PhD students funded by the Universities. The programme grant also has significant support from wider academia and industry based both within the UK and internationally.

  • Funder: UKRI Project Code: NE/T01279X/1
    Funder Contribution: 2,130,390 GBP
    Partners: Forests, Resources and People, University of Minnesota, UNIVERSIDADE ESTADUAL DE MONTES CLAROS, Kenya Forestry Research Institute, University of Edinburgh, Instituto Federal, UBC, Federal University of Lavras, Pondicherry University, Higher Institute of Educational Sciences...

    The ecosystems of the dry tropics are in flux: the savannas, woodlands and dry forests that together cover a greater area of the globe than rainforests are both a source of carbon emissions due to deforestation and forest degradation, and also a sink due to the enhanced growth of trees. However, both of these processes are poorly understood, in terms of their magnitude and causes, and the net carbon balance and its future remain unclear. This gap in knowledge arises because we do not have a systematic network of observations of vegetation change in the dry tropics, and thus have not, until now, been able to use observations of how things are changing to understand the processes involved and to test key theories. Satellite remote sensing, combined with ground measurements, offers the ideal way to overcome these challenges, as it can provide regular, consistent monitoring at relatively low cost. However, most ecosystems in the dry tropics, especially savannas, comprise a mixture of grass and trees, and many optical remote sensing approaches (akin to enhanced versions of the sensors on digital cameras) struggle to distinguish changes between the two. Long wavelength radar remote sensing avoids this problem as it is insensitive to the presence of leaves or grass, and also is not affected by clouds, smoke or the angle of the sun, all of which complicate optical remote sensing. Radar remote sensing is therefore ideal to monitor tree biomass in the dry tropics. We have successfully demonstrated that such data can be used to accurately map woody biomass change for all 5 million sq km of southern Africa. In SECO we will create a network of over 600 field plots to understand how the vegetation of the dry tropics is changing. and complement this with radar remote sensing to quantify how the carbon cycle of the dry tropics has changed over the last 15 years. This will provide the first estimates of key carbon fluxes across all of the dry tropics, including the amount of carbon being released by forest degradation and deforestation and how much carbon is being taken up by the intact vegetation in the region. By understanding where these processes are happening, we will improve our knowledge of the processes involved. W will use these new data to improve the way we model the carbon cycle of the dry tropics, and test key theories. The improved understanding, formalised into a model, will be used to examine how the dry tropics will respond to climate change, land use change and the effects of increasing atmospheric CO2. We will then be able to understand whether the vegetation of the dry tropics will mitigate or exacerbate climate change, and we will learn what we need to do to maintain the structure of the dry tropics and preserve its biodiversity. Overall, SECO will allow us to understand how the vegetation of the dry tropics is changing, and the implications of this for the global carbon cycle, the ecology of savannas and dry forests, and efforts to reduce climate change. The data we create, and the analyses we conduct will be useful to other researchers developing methods to monitor vegetation from satellites, and also to those who model the response of different ecosystems to climate and other changes. Forest managers, ecologists and development practitioners can use the data to understand which parts of the world's savannas and dry forests are changing most, and how these changes might be managed to avoid negative impacts that threaten biodiversity and the livelihoods of the 1 billion, mostly poor, rural people who live in this region.

  • Funder: UKRI Project Code: BB/V018035/1
    Funder Contribution: 30,612 GBP
    Partners: BBK, SFU

    Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

  • Funder: UKRI Project Code: EP/X012603/1
    Funder Contribution: 1,493,850 GBP
    Partners: KCL, University of Toronto, Polytechnic University of Milan, The Alan Turing Institute, Medical University of Graz

    Modelling and simulation play important roles in designing everything from planes to cars to bridges. However, advances in connectivity and computing now enable models to be linked directly to a specific object or system, creating a "digital twin". Digital twins represent a computational surrogate for a particular object and are updated through time as more information becomes available. However, digital twins are not limited to manufactured objects alone. This project aims to develop digital twins of patients, where a model will track a patient through time. We focus on making digital twins of patients' hearts using detailed imaging data sets over the period of a clinical trial. This is the first step towards models that are updated in real-time, track the patient throughout their life and directly feed back into informing patient care. The digital twin approach builds on patient-specific computer models of the heart that are currently being evaluated to guide procedures in the UK at King's College London and in the US. These models are designed to optimise treatments for a specific patient's pathophysiology but only simulate a small number of heartbeats. Digital twins, which track a patient through time, will forecast disease progression and response to therapy. This represents the next step in simulation guided therapy, where the optimal treatment and, importantly, when to deliver it, will be predicted. This project will address the technical challenges in calibrating computer models of large numbers of patients, how to efficiently update these models through time as more data becomes available, how to analyse images of the heart recorded over the duration of a clinical trial and how to predict complex changes in shape and function of the heart. The approaches will be applied to study three patient groups in three studies. First, we will test if multi-scale cardiac biomechanics models can identify common causes of pump dysfunction in heart failure patients. Second, we will test if digital twins can predict which patients who have recovered from heart failure can stop their heart failure mediation. Thirdly, we will test if digital twin forecasts can be used to predict recovery and pre-empt the need for advanced heart failure therapy in newly diagnosed heart failure patients. This will provide the first demonstration of cardiac biomechanics digital twins using real clinical data to answer important clinical questions.

  • Funder: UKRI Project Code: NE/W006448/1
    Funder Contribution: 603,466 GBP
    Partners: Aurora Research Institute, TOWSON UNIVERSITY, AMHERST COLLEGE, University of Gothenburg, UAF, NAU, University of Lapland, University of Edinburgh, ORNL, COLGATE UNIVERSITY...

    The TundraTime project will address climate change impacts in tundra ecosystems including how warming is shifting tundra plant phenology - the timing of life events such as bud burst or flowering - and productivity - the increase in plant growth and biomass over time. We will answer the fundamental research question of whether climate warming is leading to longer tundra growing seasons and thus increasing plant productivity in the Arctic, with important implications for carbon cycling and wildlife. Critical knowledge gaps in the field of global change ecology are what role the high latitudes will play in the global carbon cycle and how Arctic food webs will be restructured in the future with accelerated warming. A critical unknown is whether shifting plant phenology is altering tundra carbon cycling and wildlife habitats. Projections of climate feedbacks from high-latitude ecosystems remain uncertain as we do not yet know if carbon losses from warming soils will be offset by increases in tundra productivity. Tundra plant responses to warming could be key for understanding the fate of wildlife populations in a rapidly changing Arctic. Forty years of satellite and field observations have revealed widespread changes in the tundra's surface that protects large stocks of frozen carbon below. Field studies indicate that plants are coming into leaf earlier in spring, bare ground is becoming vegetated, and plants are now growing taller. While there is scientific consensus that climate change is reshaping Arctic ecosystems, great uncertainty persists about what the greening observed from space means in terms of change on-the-ground. The TundraTime project will answer the fundamental research questions of whether climate warming is leading to longer periods of plant growth and increases in plant productivity in the Arctic. We will test specific hypotheses of whether tundra ecosystems are experiencing: A) increases in productivity, B) shifts in phenology and C) asynchrony of above- and below-ground plant growth. To explore these questions, we will integrate high-resolution drone and time-lapse camera imagery with satellite and in-situ data from 12 focal Arctic research sites. Our findings will inform biome-wide projections of tundra vegetation change and global-scale predictions of climate feedbacks to unprecedented rates of warming. If tundra plant productivity is responding directly to the warmer and longer Arctic growing seasons then tundra productivity will trap more carbon in tundra ecosystems and restructure wildlife habitats. However, if instead tundra plant growing seasons are shifting earlier, then projections of increases in tundra vegetation with warming may be overestimates and earlier timing of key forage could alter migratory behaviour and ultimately wildlife populations. And, if the above- and below-ground responses of tundra plants are asynchronous, plant growth in the now extended snow-free autumns could instead be occurring below ground, which would overturn how satellite data and Earth-system models estimate plant productivity and carbon storage in warming tundra ecosystems. The TundraTime project will test the drivers of Arctic greening by resolving the uncertainty around what role shifting plant phenology plays in the increased tundra productivity with warming. This research will bridge critical scale gaps to resolve the uncertainty between satellite and in-situ observations of changes in the timing of plant growth with accelerating climate warming.

  • Funder: UKRI Project Code: NE/W003104/1
    Funder Contribution: 450,327 GBP
    Partners: University of Leicester, Nagoya University, University of Oulu, FMI, UNIS, UAF, University of Saskatchewan, Beihang University, GFZ German Research, INGV - Ist. Naz. Geofisica Vulcanologia...

    The UK along with the rest of the world is becoming increasingly dependent on technological systems, including satellite communications, global positioning systems, and power grids, that are at risk from space weather. Many space weather hazards originate in the ionosphere, the ionised upper part of the atmosphere at altitudes of 90 km and above, where solar wind energy channelled by the Earth's magnetic field can cause a variety of unpredictable and deleterious effects. It causes electrical currents to flow, which heat the atmosphere in a process known as Joule heating, which in turn can cause the atmosphere to expand upwards, producing drag on satellites, hence making their orbits harder to predict and reducing their lifetimes. It produces horizontal motions of the ionosphere which modify the neutral winds in the thermosphere through friction. It produces the auroras, associated with particle precipitation from the magnetosphere above, which modify the ionospheric structure. Moreover, it gives rise to plasma instabilities which cause the ionosphere to become corrugated, scattering radio waves from satellites consequently disturbing communications and GPS. Although the large-scale distribution of such space weather hazards is relatively well reproduced in global circulation models, the physics occurring on spatial scales smaller than the model grid is poorly understood, which holds back improvements in forecasting. The FINESSE project will exploit a new and unique NERC-funded incoherent scatter radar system, EISCAT_3D, located in northern Scandinavia, to study these sub-grid space weather scales. EISCAT_3D will be able to determine the ionospheric structure in a box roughly 200 km to a side horizontally and 800 km vertically, at an unprecedented spatial and temporal resolution, to image the processes leading to space weather effects. FINESSE will also exploit a next-generation coherent scatter radar to measure ionospheric motions, three neutral wind imagers to measure the interaction between the thermosphere and the ionosphere, three all-sky auroral cameras to view regions of precipitation from the magnetosphere above, a fine-scale auroral imager to observe auroral structures on spatial and temporal scales even finer than EISCAT_3D can probe, and a radio telescope and network of GPS receivers to look at the scintillation of radio signals from both cosmic sources and satellites. The main aims of FINESSE are as follows. 1) To determine the small-scale sources of Joule heating, to place these within the context of the larger picture of polar auroral disturbances, to determine the link between Joule heating and satellite drag, and to incorporate these results to improve forecast models. 2) To determine the cause of small-scale ionospheric structuring, and to understand how this leads to scintillation of radio signals. 3) To probe auroral dynamics at the very smallest temporal and spatial scales to understand the physics of coupling between the magnetosphere and ionosphere, the role auroral processes play in heating and structuring the ionosphere and atmosphere, and the instability that leads to substorms (explosive releases of energy into the nightside auroral ionosphere). FINESSE will liaise with space weather forecasters and other stakeholders to disseminate this greater understanding of small-scale processes in producing space weather hazards and to translate it into significant economic benefit to the UK.

  • Funder: UKRI Project Code: NE/W006650/1
    Funder Contribution: 652,019 GBP
    Partners: University of Gothenburg, McGill University, Swansea University, Natural England, SNH, JNCC

    Human activities have already raised global species extinction rates a thousand-fold and have pushed an additional million species towards extinction. Biodiversity is also rapidly changing on more local scales as climate change drives the redistribution of species, and pressures such as overharvesting and habitat fragmentation intensify in many areas. Understanding how biodiversity influences ecosystem functions, such as carbon capture and fisheries productivity, is a crucial challenge directly relevant to meeting the UN sustainable development goals, and UK policy imperatives of harnessing biodiversity to achieve sustainable economic growth and using nature-based solutions to help meet 'net-zero' emissions by 2050. Since the mid- 1990s, several hundred experiments have tested how changes in biodiversity influence ecosystem functions and services, with many studies indicating that biodiversity loss does not reduce functioning as long as the single best-performing species is retained. However, these studies have focused on local-scale interactions between species in small habitat units such as grassland plots, field enclosures, or aquarium tanks; we therefore lack studies that consider BEF relationships on the larger landscape-, regional- or even national- scales most relevant to the public, ecosystem managers, and policy makers. Ecological theory suggests that biodiversity is more important for ecosystem services as scale increases due to greater environmental variation, but it cannot currently be evaluated in real ecosystems because we lack BEF studies across scales and environmental gradients. In this project we aim to bridge the gap between experiments and relevant larger scales by using Great Britain's intertidal forests as a model system. These highly productive and valuable ecosystems occur extensively around the GB's varied and complex coastlines and are formed by a manageable suite of seaweed species which can be easily manipulated across multiple distinct environmental gradients. To meet our overall aim, we will incorporate multiple environmental factors into experiments, observations and models delivered across three inter-linked work packages which together provide a generalised approach and scaling relationships for BEF. Our first work package uses a 100km stretch of the south Wales coastline - which incorporates gradients in wave exposure and turbidity - as an accessible template to experimentally test the causal effect of intertidal forest biodiversity on ecosystem functioning from small patches to the whole coastline. Our second package combines a network of standardised observations in intertidal forests around GB, with satellite remote sensing and statistical modelling, to test how BEF relationships scale-up -- from 1 m to 1000km scales -- in naturally assembled communities. The third and final work package uses the new experimental and observational data to inform dynamic models, allowing us to test how species traits such as dispersal and environmental tolerances interacts with environmental variability to determine BEF relationships across scales. A key innovation here is the explicit - and empirically informed - integration of spatial environmental variability in multiple environmental factors. These will be generalised to represent how the environment varies in a range of different ecosystems from forests, to agricultural landscapes, and to coral reefs. The advancement of our project aim will deliver a revised appreciation of the role of diversity in ecosystems and demonstrate a generalizable approach for upscaling biodiversity - ecosystem functioning relationships. We anticipate that this will feed into predictions for how biodiversity changes will influence ecosystem functioning and services on large, relevant- scales, in intertidal forests and beyond, with a range of applications from natural capital models, to the design of large-scale ecosystem restoration projects.