University of Warwick

UKRI Gateway to Research · FY 2024 · 2024-09

Adsorption of atoms and molecules on surfaces is of central importance to many processes in nature and industry, like cloud formation, heterogeneous catalysis, or thin-film growth. From a simple perspective, an incoming particle must transfer enough of its excess energy to the substrate or otherwise it will recoil. Experiments on hyperthermal H atom scattering from surfaces of the three major material classes - insulators, metals, and semiconductors - have been performed to study how much energy is transferred during the H atom's collision with the surface. It was found that the effectiveness of the energy transfer strongly depends on the nature of the underlying substrate. So far, the energy transfer between H atom and surface could only be modelled with frameworks that were specifically designed for the nature of the underlying material, but a universal method that is capable to describe the energy transfer between high-energetic atom with an arbitrary surface is yet lacking. The aim of this fellowship is to design a new simulation tool that can describe energy transfer between H atoms and the surfaces of the three major material classes. Combined with electronic structure methods and machine learning, we will extend a mixed quantum-classical surface hopping dynamics approach that has been used earlier for NO scattering from Au(111) to make it generally applicable to any material surface. Firstly, we will apply this new methodology to scattering dynamics on simple, analytic 1D-Hamiltonians describing different materials. Subsequently, we will develop a full-dimensional machine learning potential for H atoms at clean, H- and Li-covered Ge(111) to study the role of the electronic, and phononic effects as well as of the different surface binding sites on the energy transfer. The acquired knowledge will enable us to engineer surface modifications that control energy transfer processes, relevant to improve fusion reactor containment and radiation protection

UKRI Gateway to Research · FY 2024 · 2024-09

This fellowship will be essential for enhancing my publication track record, taking further steps in turning my thesis into a book, disseminating my research beyond academia, and publishing a policy report. More specifically, I will: (a) Publish two further articles based on the work undertaken as part of my PhD. The first of these is a collaboration with Prof Ben Clift. It further develops the idea of a "politics of economic method" and will be ready for submission to New Political Economy in 2025. The second article is a collaboration with Dr Iacopo Mugnai and is concerned with developing a theory of successful ideational innovation within central banks. We are planning to submit the finished version to the Journal of Common Market Studies in early 2025. Together with my other published articles, these papers will help establish me firmly as a promising emerging scholar at the intersection of International Political Economy and Comparative Political Economy. Moreover, they represent my first venture into co-authorship, thus helping me gain new skills that complement those I have obtained through the previous publication of single authored articles. (b) Revise my thesis and turn it into a book. I already have an agreement with the editors of Oxford University Press (OUP), who showed great interest in my thesis and want to send a full revised draft of the thesis to external reviewers by the end of this calendar year. The ESRC fellowship will allow me to dedicate large blocks of time to this project, thus making it very likely that I will have a formal publishing contract by mid 2025. (c) Disseminate my research findings beyond academia. I have identified around 15 think tanks across the UK and Germany, who regularly publish research findings from external academics in either blog or article form, and who are likely to show an interest in my research. During my ESRC fellowship I will build on my existing connections with many of these bodies with the aim of summarising and presenting my findings in different formats for different audiences. (d) Take part in an institutional visit at the University of Sheffield, where I will be mentored by the leading political economy expert on macroprudential policy, Prof Andrew Baker. Sheffield also houses several important scholars (e.g. Prof Andrew Hindmoor, Prof Colin Hay, Dr Liam Stanley) in the areas of financial regulation, depoliticisation, and expert governance, all topics my research speaks to and it is home to one of the world's largest political economy research institutes (SPERI). As such it is the perfect place to enlarge my professional networks. (e) Write a policy report on designing equitable macroprudential frameworks that are attuned to local context. The report will be written under the mentorship of Prof Andrew Baker, who has significant experience in writing policy reports and briefings, and who took a personal interest in this part of my research, and it will be published by SPERI. (f) Further extend my professional networks and get feedback on my work by co-organising a panel on "epistemic governance" within central banks at the Finance & Society conference, presenting my book at the IPEG workshop, and attending the PSA and CES conferences in April and July of 2025 respectively. (g) Draft grant applications for the Leverhulme and British Academy postdoctoral fellowships.

UKRI Gateway to Research · FY 2024 · 2024-09

Numerous important open problems in Analysis, from such diverse areas as the compensated compactness theory of PDEs, the shape optimization of elastic materials, or the transport of geometric structures like vortex filaments in fluids and dislocation lines in crystalline materials, have at their core deep questions about "diffusely concentrating" sequences of maps, measures, or currents. Prototypical sequences of this kind display an increasing number of thin and repetitive structures as the typical length scale goes to zero. The challenge is to understand the asymptotic configurations that this "network" of structures can exhibit, which are usually highly restricted by the presence of a (linear) PDE constraint like divergence-freeness. Despite much progress in the related study of singularities in measures over the last decade, diffuse concentrations have remained shrouded in mystery. Building on the recent groundbreaking advances by the PI at the intersection of PDE Theory, Geometric Measure Theory, and the Calculus of Variations, the CONCENTRATE proposal aims at transformative progress in this highly active and rapidly evolving research area. As an application and guiding light to the theoretical investigation, the project will furthermore tackle the micro-to-macro homogenization of large-strain elasto-plasticity driven by the motion of dislocations, thus furnishing a rigorous and realistic model of plastic deformations. Often referred to as the "Holy Grail" of plasticity theory, such a homogenization result has so far proved elusive, despite much collective effort, since it requires a fine understanding of the diffuse concentrations encountered when passing from discrete dislocation lines to fields of dislocations. The PI's research leadership in these areas makes him uniquely placed to tackle the ambitious goals of this proposal through the development of novel mathematical tools and the solution of long-standing conjectures of both pure and applied character.

UKRI Gateway to Research · FY 2024 · 2024-09

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

UKRI Gateway to Research · FY 2024 · 2024-09

The Digital Telescope (DT) is a large array of small stationary telescopes which, in essence, produce a movie-like data stream of the entire visible sky. The telescope detectors are run at sub-second cadence (to minimize the effects of star trailing within each image), and sidereal tracking is achieved in software - hence the name Digital Telescope. This novel concept is quite different to a traditional telescope where motorised mechanisms are needed to make the telescope usable. Eliminating telescope movement greatly simplifies the mount requirements, and allows them to be packed tightly together. The DT uses commercially off the shelf equipment to minimise construction and maintenance costs. Software is key to a viable DT, with the main challenge being the data management and real-time reduction, but we can already demonstrate a fully functional real-time pipeline. The DT is able to cheaply monitor the whole visible sky to 20-21st magnitudes (cosmologically interesting sensitivities), detecting explosive, moving, and variable objects in near real time - including those in the near-Earth environment. We propose to build a prototype version of the DT that is capable of continuously monitoring an area of 134? × 7? using low noise scientific CMOS detectors. The sub-second cadence enables measurements of bright objects while greater sensitivity for fainter objects is obtained by stacking observations. This enables photometry of 20-21st magnitude objects at a cadence of 400 s. As the software stacking can be applied at any rate and along any vector, synthetic tracking/stacking of both stars and satellites (moving along any trajectory) is possible. Therefore, the same dataset can be used for both astronomical research via sidereal tracking or Space Domain Awareness (SDA) by tracking using satellite orbital elements. Additionally, by blind-stacking data along different trial vectors and rates, small (i.e. faint) and previously untracked space debris can be detected and catalogued. This prototype will demonstrate the capabilities of this novel concept and overcome the remaining challenges in constructing/operating an all-sky DT.

UKRI Gateway to Research · FY 2024 · 2024-08

This project will construct a new transmission electron microscope (TEM) platform for operando electrochemical imaging, designed to identify electrochemical processes at unprecedented spatial resolution while operating under application-relevant conditions. Better batteries and electrocatalysts are essential for realising a sustainable future. Yet the complexity of their electrochemistry - with intertwined dependence on side-reactions, valence evolution, structural changes, and more - cannot be predicted just by modelling. Peering inside an operating cell will reveal these processes directly, enabling the informed design of future energy materials. Resolving many of these critical aspects still reside beyond the resolution limits of current in-situ characterisation methods. The core objectives of AIDEChem are: (i) To develop a new graphene-enabled electrochemical cell that will grant a unique high-resolution TEM imaging and spectroscopy capability for probing electrochemistry in-situ. (ii) To reveal previously inaccessible processes occurring in candidate electrochemical systems, including batteries and electrocatalysts, at ground-breaking resolutions. The new platform will be used to expose the nanoscale dynamics that govern electrochemical nucleation of nanostructures, epitaxial electrodeposition, nanobubble deactivation of electrodes, and electrocatalyst evolution; electrochemistry that is largely inaccessible with current in-situ microscopy technology. With the new technical capability realised in this platform, AIDEChem will provide the insights that are mandatory for the informed design of effective electrochemical energy materials, optimally tailored for the desired application. Delivery of AIDEChem will be possible due to the PI's combination of research skills - encompassing in-situ TEM, nanoscale device fabrication, 2D materials, and electrochemistry - and the TEM, nanofabrication, and electrochemistry facilities at Warwick University.

UKRI Gateway to Research · FY 2024 · 2024-07

The current industrial approach to create metal products is unsustainable. Massive amounts of energy consumption, chemicals, water and the exhaustion of natural metal resources are the hallmark of metal production and processing industries. Metal Additive Manufacturing (AM) presents an opportunity to ameliorate metal processing and product manufacturing. While this is a known fact, a full scale industrial implementation of metal AM has been impossible until now due to the lack of consistent AM metal quality. DurAMat is the game-changer that will engender long-lasting performance properties of AM products used in severe exposure environments. DurAMat research will i) develop AM components from different alloy families sustainably ii) enable AM as preferred repair method for defunct metallic products and iii) enable AM for metal functionalisation. DurAMat's research combines experimental research with multiscale modelling and machine learning (ML) methods. DurAMat fills important knowledge gaps and will innovate AM metals (duplex steel alloys for marine, magnesium for bioresorbable implants) and coatings (biocomposite and AM metal coatings for corrosion and mechanical performance), technologies and services (AM for repair, ML for corrosion inhibitor selection), three computational models (multiscale and ML) and one device (add-on for Wire Arc Additive Manufacturing microstructure control). The DurAMat consortium consists of 6 Universities, 2 Research Centres and 5 Industrial Companies from 6 European Countries. It will train 10 doctoral candidates in a holistic approach, encompassing cross-disciplinary scientific knowledge transfer, teaching activities and cultivating interpersonal and transferable skills. DurAMat's impact forecasts, among others, a 30% energy reduction in the processing and manufacturing of products, 60% less end product failures reducing health hazards, eco pollution and casualties, and 20% cost benefit compared to conventional industry approaches.

UKRI Gateway to Research · FY 2024 · 2024-07

POSEIDON brings together an interdisciplinary and intersectoral team to deliver 10 professionally trained next-generation Early-Career Researchers to develop a step change in our capacity to identify, map, assess and predict offshore geohazards and in turn produce ground-breaking methods to prevent, mitigate and boost the resilience of current offshore infrastructure under a changing climate. The consortium is formed by experts across 7 EU countries with 7 universities, 2 research institutions, 4 industry partners and 1 government body to cover a full training programme on scientific and transferable skills. The programme will undertake critical research across scales (from micro to macro) for seeking the inner links and differences, with an eventual aim to ascertain the pathways and grow our capacity for the enhancement of the existing and the robust development of new offshore infrastructure in the frame of safety and resiliency. In addition to the informed design and implementation of the novel physical/numerical modelling and lab studies, our approach is unique in the solid integration and utilisation of state-of-the-art data science technologies (e.g. data mining, machine learning, etc.) to their full potential. Only through this systematic approach, we can achieve the objectives of understanding the impact of offshore geohazards on our offshore critical infrastructures and developing novel models, tools and designs for future OCIs, such as, wind turbines, pipelines and cables. The ESRs will enjoy a highly integrated, interdisciplinary and intersector training environment, enriched through secondments with the network of non-academics. POSEIDON enables critical learning across all training aspects to ensure that comprehensive, robust and implementable solutions are obtained and validated to face the OCIs climate-resilient building.

UKRI Gateway to Research · FY 2024 · 2024-07

Breast cancer remains a leading cause of death in women aged 40-74y in the UK, underscoring the importance of improving early detection and treatment. One strategy proposed to improve early detection is risk-based screening. Here interventions are tailored, so that those most likely to be diagnosed with breast cancer receive more screening. A key component of this is risk assessment. Much research has considered risk models using classical risk factors, such as family history and hormonal factors. Recent evidence points to greater effectiveness of risk assessment over the short-term using information from screening mammograms, than all other risk factors combined. Currently, there are two main AI tools available for image-based short-term risk assessment, exemplifying progress in this domain: the open-source Mirai (developed by Yala & Barzilay, MIT) and a model developed by the Karolinska Institute. Of these, only the latter is commercially available, and is currently licensed by iCAD.     Despite the promise it holds, AI-driven risk-based screening is not currently implemented within the NHS Breast Screening Programme (NHSBSP) due to a multi-faceted gap: the absence of a robust, extensively validated, and easy to deploy AI-based risk prediction tool that demonstrates clinical utility and health-economic benefits in the UK context.    Our group has developed a deep-learning tool called BREST (Breast Risk Evaluation from Screening Test) for three-year risk assessment using screening mammograms. Supported by a CRUK grant and preliminary studies on the OPTIMAM’s OMI-DB database (18,800 NHS patients), BREST has AUC (Area Under the Curve) 0.70 to 0.71, matching Mirai (0.68 to 0.69). on the same test sets. However, to fully exploit BREST's potential and address the above gap, further development is crucial. Our project will advance BREST's development through three key objectives, each targeting a specific aspect of the gap identified: Performance enhancement and retrospective evaluation: Our project is set to optimise and significantly expand the training process for the BREST algorithm, utilizing a newly acquired, extensive, anonymised dataset from the NHSBSP, in collaboration with OPTIMAM. This dataset encompasses over 694,000 screening episodes and 2.93 million mammograms. By leveraging this vast resource, we aim to enhance BREST's predictive power and ensure robust performance across various scanner technologies and manufacturers, directly tackling the identified gap in performance and clinical validity.  User-friendly API development: We will develop a user-friendly Application Programming Interface (API) to facilitate future seamless integration of BREST into healthcare facilities' digital ecosystems and prospective studies. This API will be designed to support real-time risk assessments during breast cancer screenings, promoting broad compatibility and facilitating easy adoption across healthcare settings.  Health economic evaluation for AI-driven screening with BREST: Leveraging our previous work, we aim to quantitatively assess the potential cost-effectiveness of AI-driven, personalized screening within the NHS, using BREST-specific health-economic models. This includes setting AI-based risk thresholds to optimize screening intervals, reducing advanced cancer cases, and enhancing screening efficiency.  We aim to bridge a gap in implementing new AI-driven, personalized breast cancer screening in the UK. Work to address the above objectives will set the stage for prospective evaluation, commercialization, and ultimately integrating risk-adapted strategies within the NHSBSP.

UKRI Gateway to Research · FY 2024 · 2024-07

Diamond magnetometers are sensitive sensors of magnetic fields. Designing these to be fibre coupled means that a small mobile sensor head can be combined with the larger electronics needed to reach high sensitivity. We have built sensitive fibre-coupled diamond magnetometers, and in this project, we will build a version that will be suitable for assisting surgeons operating on breast cancers. Magnetometers are currently used in breast-cancer surgery in two ways: one of these is that a 5-mm-long magnetic cylinder can be placed where the cancer is during medical imaging, and then when the tumour is later removed (after radiotherapy and/or chemotherapy) the cylinder shows the surgeon which volume to remove. A magnetometer is used to find this magnetic cylinder. In addition to this, the surgeon wants to know where the cancer may have metastasized to. By injecting a magnetic liquid into the tumour region, and following where is goes with a magnetometer, secondary cancers can be removed also. While the first of these techniques is quite successful, the second is often less so, meaning that alternative methods must be used such as injecting a radioactive tracer. However, the radioactive tracers require significant extra work and cost for the hospital because of the health and safety precautions required. With a more sensitive magnetometer, these radioactive injections could be avoided. Building a sensitive magnetometer with a sensor head that is small enough and flexible enough for endoscopy and laparoscopy would provide new possibilities for doctors and patients. Endoscopy uses the body's natural openings to see inside the patient, while laparoscopy is known as keyhole surgery because an incision is made. The sensor head of the magnetometers currently used for breast surgery are rigid cylinders with a diameter of 18 mm and a length of at least 100 mm. The smaller sensor heads that we will build for this project could lead to new procedures based on magnetic endoscopy and laparoscopy. We will not do any work with patients or healthy volunteers as part of this project because currently we are focused on building the device. However, two of the co-investigators on this proposal are surgeons to ensure that we move quickly towards a useful device. One of these surgeons uses the 18-mm magnetometer during breast surgery.

UKRI Gateway to Research · FY 2024 · 2024-07

This pioneering project breaks new ground through the first systematic investigation in comparative perspective of the economic, political and social dynamics of the emergence of new financial middle classes in emerging market democracies. How does the emergence of a new financial middle class - that is citizens with the ability to borrow, save and invest via the formal financial system - impact democratic consolidation in emerging market democracies and vice versa? In what ways do middle class aspirations for social protection and mobility, situated at the intersection of state designs to grow the middle class and ongoing dynamics of financial sector expansion, give rise to new constellations of financial and social policy provision? And to what extent do these new political dynamics narrow down democratic space in fostering close alignment between government interests and the policy preferences of a small group of comparatively well to do citizens, or enable new, more expansive forms of (financial) citizenship, conceptualised as the ability to access, participate in and mobilise around the governance of the financial system, and polity at large? These are the questions this project seeks to address through the generation of rich sets of new quantitative and qualitative data, deploying large N and small n analysis, with an empirical focus on Southeast Asia and Sub-Saharan Africa, where original fieldwork will be conducted. Its research objectives are threefold: i) to comprehensively map the rise of the financial middle class in emerging market democracies and their financial strategies and aspirations; ii) to systematically assess the impact of emerging market democracy middle classes on financial policymaking and social policy provision; and iii) to critically interrogate contentious political mobilisations around emerging discourses of financial governance and citizenship.

UKRI Gateway to Research · FY 2024 · 2024-07

Moving people and goods is worth over £100 billion to the UK economy (across transport modes), but it comes at a cost, with over 2000 deaths and 120,000 injuries every year. Connected and autonomous transport has the potential to make land, air, and marine journeys safer, faster, and more efficient, contributing to both our national health and carbon emissions goals. Additionally, the connected and autonomous transport systems' market globally is projected to be over £700 billion by 2030, so this sector could be a major driver of economic growth in the UK. The biggest challenge to delivering the potential of autonomous transport systems are provable quantified safety and consumer understanding. Without addressing these issues across all sectors, it will take us significantly longer to unlock the potential commercial and wider benefits. Over the last three years of the Future Leaders Fellowship (FLF), to find answers to various research questions in Connected and Autonomous Vehicles (CAVs) (i.e., land), the fellow has often looked to other transport domains like aviation and marine and benefitted by transferring learnings from them to CAV. This experience brought a realisation that "while aviation and marine are also introducing the autonomous system, the safety challenges are similar to CAVs". This realisation underpins the fellow's +3 FLF renewal vision. The vision for +3 Renewal of the UKRI FLF application is to translate the learnings on safety assurance of CAV to aviation and marine autonomous systems (aerial drones and unmanned vessels). While there are obvious differences between the transport domains (land, air and marine), the approach to safety assurance could potentially be similar if a first principles approach is taken. Safety assurance of autonomous transport systems in air and marine requires three key areas of research, standards, and regulation: 1) test scenarios; 2) test environment; and 3) safety argument. However, the safety assurance process needs to be underpinned with the correct and complete set of requirements definition for the system. As part of research on CAV, defining the Operational Design Domain (ODD) and behaviour capabilities of the autonomous system is fundamental to the requirements definition. An ODD (i.e., well-defined safe operating boundaries) is fundamental to any safety assurance process for autonomous systems. Operating conditions for the land include attributes like road type, weather type, type of actors (emergency vehicles, pedestrians), etc. (as per BSI PAS 1883 - fellow as technical author). While the operating conditions for aviation and marine will differ, the concept of ODD is transferable. Operating conditions for the sea could include attributes like current strength, wind speed and direction, salinity, water depth, etc. Operating conditions for air could include attributes like wind speed and direction, air density, fog, etc. However, a standard taxonomy concept still evades the industry, which will be one of the focuses of my +3yrs FLF. Another key aspect of safety assurance of autonomous systems in transport is the definition of safe behaviour. As a further part of the +3yrs FLF, the focus would be to create safe behaviour definitions by codifying the Rules of the Air and Rules of the Sea. Currently, Air Traffic Management (ATM) and Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) define the rules of air and sea for human-driven vehicles. We will take an ODD and behaviour-based approach to codify the rules using first-order logic. In addition, the +3yrs FLF will also benefit from the fellow's first-hand experience as the UK's technical representative on various international standards committees, providing further insight and a clear route to deliver impact from the proposed research through the development of international standards and regulations, while also ensuring that the UK becomes a global leader in this area.

UKRI Gateway to Research · FY 2024 · 2024-07

Addressing climate change is humanity's greatest challenge in the 21st century. The European Green Deal has declared that Europe is committed to realizing a climate-neural society by 2050. To reduce carbon dioxide emissions from transport, power, and industry sectors, Europe must urgently change the energy paradigm, shifting to renewables. However, renewables are all intermittent, and facing the storage challenge. Secondary batteries offer highly efficient electrical energy storage capability, and become the key technology to achieve the large-scale application of solar/wind green energy and thus support the deep decarbonization of European energy system. European Commission estimated that the value of battery industry can reach 250 Euros billion by 2025. Existing battery systems still suffer from low energy density and safety issues. There is huge gap between commercial batteries and advanced battery proposed by BATTERY2030+. Employing novel electrode materials are considered as promising strategies to develop next generation high performance batteries. However, these high capacity electrode materials raise significant challenges (dendrite, volume change, and degradation etc.) in practical application, which limit their commercialization prospects. LESIA will develop and construct bio inspired surfaces/interfaces with electrochemical functionalities for the components of batteries using laser-based fabrication and emerging nanoscale characterisation techniques. LESIA will develop new surficial chemistry, and regulate the decisive electrochemical interfacial processes, and thus address the challenges of the high performance anodes and cathodes for next generation advanced batteries. The advanced batteries are designed to deliver 450+ Wh/kg energy density, 5000+ W/kg power density, 5000+ cycles and 85 Euros/kWh target cost. LESIA will create new paradigm of advanced battery development by using cutting edge laser-based surface/interface engineering technologies.

UKRI Gateway to Research · FY 2024 · 2024-07

Much of life on Earth relies on oxygen for aerobic respiration. Indeed, it is thought that mammalian reproductive systems cannot operate at oxygen concentrations much lower than today's 21%. It is therefore vitally important that we understand how oxygen is generated, maintained and consumed. The cycling of oxygen is just one of numerous 'redox-coupled' biogeochemical cycles, whereby the majority of transformations are carried out by biology. For instance, our primordial Earth completely lacked free oxygen, until the evolution of photosynthesis freed it from water more than two billion years ago. The subsequent rise of oxygen concentrations until today has been crucial for the evolution of complex life forms. Yet, this rise has been far from linear. Indeed, for most of Earth's history, oxygen concentration remained at less than one percent of today's value, with geochemical proxies suggesting large and rapid fluctuations in atmospheric oxygen roughly 600 million years ago. It is important that we establish what events catalyse these swings, to predict future habitability. Over geological timescales, oxygen concentration is controlled by three factors: 1) The amount of primary production of the biosphere, 2) The global balance of photosynthesis to aerobic respiration and 3) The rate of burial of carbon-rich organic matter into mostly marine sediments. Roughly 25% of present primary production is carried out by one group of microorganisms, marine cyanobacteria. This group represent the most numerically abundant photosynthetic organisms on Earth. They evolved roughly 650 million years ago, narrowly pre-dating a rapid rise in oxygen concentration, suggesting their distinct physiology could have driven this rise. However, we have no understanding of how this group became so abundant in the marine environment. We recently identified a genetic change that is unique to this group that controls an important aspect of photosynthesis. This genetic change involves cellular machinery, called the carboxysome, which allows carbon fixation to function efficiently. This group of cyanobacteria acquired their carboxysome from distantly related bacteria and it has subsequently been passed to all descendants. Here, we propose that this unique genetic change allows photosynthesis to better operate when nutrients are limiting. We call this the oligotrophy hypothesis. If this genetic change would have allowed these organisms to adapt to oligotrophy, this would have promoted their rapid expansion into the vast Neoproterozoic oceans, which were otherwise devoid of primary producers. The result would have been a large increase in planetary primary productivity and increase in atmospheric oxygen. By combining interdisciplinary approaches, we will test this exciting hypothesis . We will combine 'genetic transplants' of carboxysome genes and cellular modelling to understand their underlying effect on cell physiology. We will use field work to experimentally test selection of trophic status on carboxysome type. We will then integrate this data with evolutionary scenarios of cyanobacteria into geochemical models of the Neoproterozoic oceans to understand if this mechanism could plausibly explain the rise in oxygen supporting complex life. Our findings will have important implications for our understanding of the habitability of life on Earth and the existence of complex life beyond our planet.

UKRI Gateway to Research · FY 2024 · 2024-06

SuperAIRE aims to establish a world-leading network connecting academia, industries, and policymakers across the spectrum of artificial intelligence (AI) for renewable energy (RE), particularly wind, solar, marine, and bio energy. This includes generation, storage, transmission/distribution and demand side management. These represent most of the research areas in the UKRI's Energy and Decarbonisation theme. With SuperAIRE, we aim to create the conditions in which AI for RE can be promoted much more rapidly than at present to boost the development and deployment of RE. We will not only exploit the transformative power of AI in different RE subsectors but also address common challenges and optimise performance across the RE ecosystem. Supported by a broad partnership currently with 30 partners across industry (23), leading R&I organisations (5), and policymakers (2), we will incubate a Supergen AI+RE research community seizing the opportunity to enhance the UK's role as a global leader in the intelligent and digital transformation of the RE sector. Despite the recent growth in all subsectors, progress in essential technologies supporting the lifecycles of RE systems lags behind. AI offers strategic advantages in overcoming the limitations of traditional methods which struggle to process the increasing complexity and big data in RE systems. It will enable decision-supporting digitalisation, operational efficiency optimisation, cost-effective integration, multi-scenario adaptability, and technological cross-applicability. Though there are some current critical masses in AI for RE, the communities are facing many challenges, e.g., the fragmented nature of the landscape, subsystem isolation, and limited scope. SuperAIRE will address these challenges by enabling shared learning on common research challenges in different RE subsectors through promoting novel generic approaches complemented with refinements tailored to subsector's unique needs; forging a holistic view to facilitate system-wide AI applications; and fostering comprehensive solutions that go beyond single-task focuses to exploit the full potential of AI in enhancing the RE ecosystem. SuperAIRE will carry out diverse activities to engage with stakeholders, facilitate knowledge exchanges, catalyse community coherence, identify cross-sector opportunities, address skill gaps, support nurturing high-skill professionals with multidisciplinary expertise, and disseminate project outcomes. These activities include four key challenge workshops, bimonthly seminars, flexible funds, outreach activities, an international conference, etc. SuperAIRE will support early career researchers (ECRs) from both academia and industry via a dedicated ECR Forum, a mentoring scheme, secondment opportunities, and ECR grants. We will emphasise Equality, Diversity and Inclusion in all activities. Based on the current critical mass and emerging gaps and opportunities, we have also proposed six pre-defined research themes (RTs) to steer our Network+ activities, especially in guiding discussions, identifying challenges and opportunities, streamlining research coordination efforts, shaping a research landscape report, and developing a whitepaper. This includes RT1 Robust and trustworthy AI; RT2 Prediction and forecasting across scales; RT3 AI-powered digital twins; RT4 Intelligent control and management; RT5 Smart integration; and RT6 Intelligent robotics and autonomous systems in resource assessments, operations, and maintenance. Bolstered by strong support from project partners, we will consolidate core achievements and pursue the establishment of a new Supergen Hub in AI for RE at the end of SuperAIRE. Through these endeavours, we aim to enhance the efficiency, resilience, and affordability of RE, ultimately transforming the RE sector and addressing environmental challenges via AI.

UKRI Gateway to Research · FY 2024 · 2024-06

Human capital is a central ingredient of the development process. While the literature has made progress in measuring the variation of human skills across countries and over time, we still have a limited understanding of the channels through which they shape the organisation of production and economic development. This is complicated by the growing realization that human capital is a multidimensional object, given the variety of skills embodied in workers on one hand, and the heterogeneity across firms, occupations, sectors, and countries in their utilization on the other. HUMANDEV will leverage micro-level data from multiple countries and novel theoretical frameworks to shed light on the role of human capital for the past and future of economic development. The project is structured around three Work Packages, studying how the accumulation and utilization of different types of skills is shaped by and can facilitate the adaptation to some of the most pressing challenges faced by the global economy: population ageing (Work Package 1), climate change (Work Package 2), and the reallocation of workers across economic activities (Work Package 3). Each Work Package will involve three complementary contributions: 1. Collecting and harmonizing micro-level data from countries at different levels of development to construct novel facts on the accumulation and utilization of human skills in a variety of contexts. 2. Developing new theoretical frameworks to provide a structural interpretation of the empirical facts. 3. Estimating the key parameters of these models and implementing counterfactual exercises to assess the effects of different economic scenarios and policy proposals. The findings of HUMANDEV will shed light on the present and future contribution of human capital to economic development, and on how policy can help equip labour forces in developing countries for the impending socio-economic transformations.

UKRI Gateway to Research · FY 2024 · 2024-06

Everyday, we are surrounded by situations that depend on large-scale computations, from Artificial Intelligence, trained on enormous datasets with parallel processing, to data storage, such as Dropbox. Performing these massive, multi-core computations introduces many challenges of its own. > Imagine an old computer with a handful (8, say) of processing cores. It was feasible for the central controller to track how many tasks are assigned to each cores in real time. A new task can be allocated to the core with the smallest current load. > Now imagine a modern set-up, with thousands of individual cores---the Met Office has one with ~500,000, as of 2019. This is far too many for the central controller to track in real time; tasks must be allocated without complete information. This is where the *balanced allocation* (BA) framework comes in. A popular protocol chooses two cores randomly, inspects their load and assign the task to the least-loaded. This is computationally efficient, only requiring inspection of two cores. It works very well, both in theory and in practice. Unfortunately, classic BA is *static*: tasks are assigned to processors, but never removed. This is appropriate for certain scenarios: eg, Dropbox data storage uses a variant of this 'two-choice' protocol. However, it is less applicable in the dynamic computing set-up above: once a core completes a computational task, it moves onto the next task and the completed task is removed from the system. Also, if the core does not have another task ready, it will be idle, wasting resources. Minimising the likelihood of this is an important aspect not covered in the classical BA framework. Enter *queueing theory* (QT). Classically, this is used to model the behaviour of customers, such as at supermarket checkout lines or telephone call centres. Customers *enter* the system, then *exit* (are *removed*) after they have been served. The set-ups are similar: customers/tasks arrive and are assigned to a line/core. The key difference is that customers are removed in QT. The traditional BA and QT viewpoints are somewhat different, even opposing. > QT research *models* customer behaviour. Properties and characteristics are learnt via analysis of the resulting probabilistic system. > The purpose of BA is to *design* a smart protocol for assigning jobs. The analysis is performed to determine how well the protocol works. This is, of course, a simplification: there is some QT research into configuring systems, but it is more the exception, rather than the rule. The overarching aim of this proposal is to take the design-based viewpoint of BA to the QT set-up, allowing analysis of "job allocation with removals". - Tasks arrive at rate r < 1 (r per second, say; the scaling is unimportant). - Upon arrival, they are assigned to a core according to some protocol, and they join its queue. - The processor completes each task in its queue at rate 1 (1 per second on average). These dynamics provide a more realistic and applicable framework in which to design, test and analyse protocols for balanced allocation of tasks. We have three primary objectives. Current BA protocols can easily be ported to the 'dynamic' framework. > O1: Analyse popular BA protocols ported to this dynamic framework, obtaining rigorous bounds on their performance; currently, these only exist in the static framework. These BA protocols were designed and optimised for the static set-up. So, whilst they can be ported, there is there is surely much to be gained by designing protocols directly in the dynamic framework. > O2: Design new, bespoke protocols directly in the dynamic framework, using the richness of QT to exploit the dynamics. Our framework has assumed that each processor knows how many jobs are queueing at it perfectly, and can communicate this to the central controller. We relax this. > O3: Analyse the effect of noisy and/or delayed measurements on protocols.

UKRI Gateway to Research · FY 2024 · 2024-06

We propose an exciting research project that aims to uncover the mysteries behind a parasite, known as the African trypanosome, which causes diseases in both humans and livestock. These parasites can 'swim' through their host to avoid the immune system and spread throughout the body. This movement is powered by a 'tail' or flagellum, which beats like a tiny oar and is controlled by various proteins and complex structures within the parasite. Not only will our research unveil trypanosome biology, it will also tell us about human biology. This is because the movement mechanism within these parasites shares similarities with specific structures in human cells, such as our in our airways. Problems in the same tiny structures that control movement in these parasites can cause a genetic disease in humans called primary ciliary dyskinesia, affecting 1 in 10,000 people. Despite its importance, there's still a lot we don't understand about this complex process of movement. For instance, we know some proteins (called CPAPs) play a crucial role in assembly of the machinery that drives movement, but we don't understand how all the pieces fit together. Our research aims to address this by setting out with three big goals. Firstly, we're going hunting for new proteins involved in the process. We want to understand their roles and where they fit in the complex 3D puzzle. Secondly, we're going to study the intricate biochemical relationships between these proteins, using high-tech methods to reveal how they interact. Lastly, we're going to recreate the process in the lab, which will allow us to observe how these proteins bind and work together in real-time. Through this ambitious research, we hope to develop a detailed model of how these proteins assemble and work together. Our findings could not only shed light on the biology of these harmful parasites but could also provide broader insights into similar processes in a wide variety of organisms, including humans. In doing so, we hope to take a significant step forward in our understanding of these fundamental biological processes. This might even pave the way for new treatments for diseases caused by these parasites and further our understanding of some human genetic diseases.

UKRI Gateway to Research · FY 2024 · 2024-06

Long linear infrastructure (LLIs) earthworks (e.g. road & railway slopes, pipeline bedding, flood protection structures) are more vulnerable to cascading and escalating failures, due to their topographically designed spanning length and long operational lives. With increasingly frequent severe weather conditions caused by climate change, maintaining a high level of safety performance, especially for the aged LLIs, remains a constant challenge, leading to an ever-increasing amount of investment in maintenance. Current knowledge about how these assets deteriorate over time and how deterioration affects risk and performance is patchy. The conventional engineering-oriented approach alone became insufficient to provide a solution to the complex problem like this. As we accelerate into the 21st century, the latest advances in technology, through digitalisation by integrating new revolutionary data technologies of Internet-of-Things (IoT) and artificial intelligence (AI), offer opportunities to UPGRADE our LLIs and achieve new heights in safety and performance. Highly-skilled researchers and practitioners, capable of dealing with such problems, are scarce and in high demand by both academia and industry. Therefore, formed with 11 world-leading research organisations and 6 companies across Europe, Asia and Oceania with expertise and facilities in Earth Observation, geomaterial testing, constitutive modelling, data mining, machine learning, uncertainty quantification, data-driven design and optic communication, UPGRADE aims to ensure comprehensive, robust and implementable solutions are obtained for LLIs resilience built and sustainable development. The network is carefully designed to enable research and innovation staff exchange across all aspects. UPGRADE secondees will enjoy a highly integrated, interdisciplinary and intersectoral staff exchange, sharing know-how and skills development environment through the planned secondments, networkwide events and local trainings.

UKRI Gateway to Research · FY 2024 · 2024-06

The news media industry has recently been disrupted by the rise of social media. The traditional news media played a dominant role in political debate. Social media now offers new opportunities for public participation in political debate, and it has the potential to support a much more socially inclusive public sphere. The disruption in the news media industry presents a formidable challenge. Is it possible to guarantee a future for high-quality, informative news in the digital age? There is much at stake here because a well-functioning democracy is only possible if it is supported by informed political debate. Our project addresses this challenge. It will deliver innovations in the news media industry that secure high-quality news combined with enhanced audience participation. As such, it has the potential to strengthen the positive democratic role of the news media. Journalists and media studies professionals have been grappling with the question of whether and how to involve the public in their work. Following Rosen (1991), media studies have explored models such as 'participatory journalism' (Singer et al. 2011), 'collaborative journalism' (Sambrook 2018), and 'engaged journalism' (Schmidt and Lawrence 2020). The debate has also questioned commitments to journalistic objectivity and impartiality. Some argue that objectivity and impartiality remain essential for good journalistic practice. Others reject objectivity and embrace partisanship, where the role of journalist blurs into that of activist (https://www.project-syndicate.org/commentary/news-reporting-and-advocacy-can-both-be-objective-by-jan-werner-mueller-2023-04). The research underpinning our project rejects the binary nature of the existing debate and shows that it is possible to reconcile a commitment to high epistemic standards with a commitment to audience participation in journalism. Our research led us to outline a new model for the news media industry. This model - which we call the co-creational model (Heawood and Peter 2023) - enables audience involvement in the creation and dissemination of news and in accountability-related processes while producing high-quality news. The model offers an important and timely tool to contain the pernicious political effects of lies and misinformation. The model is also informed by previous work with industry leaders, and by research on co-creation and co-production (Brandsen and Honing 2018). It incorporates insights from diverse sectors such as business (Prahalad, 2004), healthcare (Peng 2022), education (Bovill, 2020), and public policy. In this project, we will continue to work with industry leaders to further develop and embed the co-creational model for the news media. Our project has two specific objectives. The first is to identify best practices for the co-creational model for the news media. The second objective is to promote professional standards innovation in the news media through the adoption of co-creational best practices in the news media industry. We take a modular approach to the co-creational model, which is designed to allow a broad range of news media organisations, including the traditional media, to benefit from this project by adopting elements of this model. Key outputs of our project include an online best practices toolkit and a co-creational pledge scheme that allows news media organisations to signal commitment to co-creational best practices.

UKRI Gateway to Research · FY 2024 · 2024-06

The transition to clean renewable energy requires cheaper and more efficient means of both harnessing and storing energy. This is limited by the functional properties of the materials used in devices such as solar cells and batteries. To design new materials with better performance, we must understand the structure of the material and how they work in a given application. In particular, the atomic-level structure and chemistry uniquely determine the material attributes and how well they perform. In this project, I will use solid-state nuclear magnetic resonance (NMR) spectroscopy to identify the mechanisms and structure of functional materials. NMR measures the magnetism of atomic nuclei, which is highly sensitive to the local arrangement of atoms, as well as to motion of the atoms over a wide range of timescales, from picoseconds to minutes. Correlation experiments further measure the interaction between the magnetic moments of different nuclei, enabling spatial proximities of different species to be determined. NMR is particularly well-suited to complex, multicomponent, and/or nanoscale materials, which are challenging to study with other techniques. I will focus on two important classes of materials, hybrid perovskites and MXenes. Hybrid perovskites offer the promise of next-generation solar cells with higher efficiency and lower production costs than current silicon-based photovoltaics. However, their commercialisation is held back by their propensity to degrade under environmental conditions, particularly exposure to light. I will study the effects of light illumination on the structure and dynamics of perovskite materials, to understand how they degrade and, therefore, how to protect against degradation. This will require new experiments to measure the NMR spectra of device-relevant thin-film samples on exposure to light. MXenes are a class of layered 2D materials, reminiscent of graphene, that can be used as batteries or gas sensors and separators. The surfaces of the MXene layers are covered in a disordered array of functional groups which are hard to characterise, but which critically determine the functional properties such as the battery capacity and charging rate, or the gas separation selectivity and sensing limits. To optimise the performance of MXenes in these applications, I will investigate how ions and gas molecules fit between the layers and how this is affected by the surface groups. Advanced NMR methodologies will be used to perform these experiments while charging/discharging the material in-situ, and with in-situ introduction of gas molecules. These ambitious experiments will reveal the structural factors that limit the performance of both sets of materials in real-world applications, thereby guiding the design of improved materials via new formulations, processing methods, and treatment strategies. Overall, this will push the materials towards commercialisation. Moreover, the methodological development and expertise can subsequently be applied to other novel materials with new functional challenges.

UKRI Gateway to Research · FY 2024 · 2024-06

This application for a BBSRC Flexible Talent Mobility Account (FTMA) represents a strategic partnership between the University of Warwick and the University of Birmingham. Our aim is to build on our productive regional collaborations, world-class facilities, and complementary strengths in biosciences research to deliver an FTMA that enhances knowledge exchange (KE) between sectors, promotes early career development, and is open and inclusive to diverse beneficiaries. In line with these aims, our proposed programme includes flexible secondments to and from external organisations, an early career researcher (ECR) and technician fellowship scheme, and support for new and existing international collaborations. To accompany these opportunities, we will support challenge-focused networking events with collaborators and technical network meetings open to both institutions. The contribution of our research culture practitioners to design of this programme has ensured that equality, diversity and inclusion (EDI) principles are appropriately embedded and that opportunities for cross-sector professional exchanges are flexible and inclusive. Our application is focused on the priority area of tackling infections reflecting the breadth and diversity of our combined thematic strengths that span antimicrobial resistance (AMR), plant pathogens, genomic surveillance, vaccine development, and mathematical modelling of infections. The outstanding recent impact of our talented researchers and support staff on the frontlines of infectious disease outbreaks including the Ebola epidemic, avian influenza, and the COVID-19 pandemic, has highlighted the necessity of cross-sectoral collaborative partnerships to combat these emerging threats. The current crisis of AMR is also a major priority for scientists at both Universities and our dedicated interdisciplinary research centres would benefit greatly from enhanced external connectivity. Our present collaborations span academia, business, government, and the third sector and are vital to ensure our research is relevant to today's societal challenges and generates wide reaching impacts. The FTMA will allow us to deepen existing links and develop exciting new alliances that will last beyond the lifetime of this programme. We will place particular emphasis on opportunities to engage with policymakers in recognition of the role excellent research plays in shaping tomorrow's policy solutions. By allocating FTMA funding competitively and transparently through managed calls, we will be able to select projects that have potential for excellent KE, provide opportunities for professional development and are aligned with our EDI framework. This FTMA would represent a significant asset to our ECR and technical communities who reap numerous benefits from experiencing new working environments. Opportunities to drive externally facing projects will complement our existing investments in technical career development and ECR skills training. Emphasising the potential impact of the FTMA on early career trajectory are our previous beneficiaries who have used their external placements as crucial stepping stones on the path to becoming today's academic group leaders and spin out entrepreneurs. As well as supporting programme delivery, we are committed to ensuring mobility opportunities are extended to our research support staff which, in turn, will deliver valuable KE and additional external connections to our academic communities. Through the FTMA, we will provide vital opportunities for our staff to gain awareness of societal challenges, understand routes to policy impact, and appreciate the needs of industry. In this way we will support our researchers and support staff to become future drivers of positive change and champions of interconnectivity between all sectors that contribute to excellent research and its resulting impacts.

Other NSERC · FY 2024

Stellar astrophysics, White dwarf stars, Evolutionary models, Core crystallization, Stellar age dating, Galactic evolution

Other NSERC · FY 2024

theoretical computer science, computational complexity theory, lower bounds, algorithms, circuit complexity, randomness in computation, pseudorandomness, information theory, Kolmogorov complexity, compression