University of Southampton

UKRI Gateway to Research · FY 2025 · 2025-12

The gambling landscape has shifted dramatically over recent years. Individuals now encounter gambling opportunities earlier and more frequently than before through online platforms, mobile apps, and gambling features embedded within gaming environments). Rising accessibility, combined with the normalisation of gambling as a social activity, has driven increases in problem gambling, damaging mental health, draining finances, and burdening society. Despite this growing burden, help-seeking rates for traditional face-to-face treatment remain very low, with less than 10% of people experiencing problem gambling engaging with current services. Barriers include shame, stigma, barriers to access and awareness, and competing demands on time. Digital technologies for deployment of interventions offer a promising pathway to overcome these obstacles by providing cost-effective, scalable, and immediate access to evidence-based care. This project will conduct a rigorous synthesis of the evidence relating to the use of digital interventions to reduce problem gambling and gambling disorder in adults, overcoming shortfalls and conflicts of interest in prior reviews. By scientifically reviewing the evidence base, we will identify key information and knowledge gaps to help inform future research, as well as configurations of clinical service and public policy.  

UKRI Gateway to Research · FY 2025 · 2025-12

Harmful gambling is a significant public health issue, affecting more than 500 million adults globally. The burden of harm associated with gambling is substantial – estimated to be two-thirds that of alcohol use disorders and major depressive disorder. Importantly, gambling harm is not only experienced by people who gamble, but also their family members, social networks, and the broader community. In England alone, the societal and economic burden of gambling is estimated at a minimum of £1.27 billion annually, increasing to £1.77 billion when broader impacts on health, welfare, and the criminal justice system are considered. These costs may well be under-estimates, due to the challenge in quantifying diverse types of gambling harms. Although psychological and pharmacological treatments have demonstrated efficacy, harmful gambling is commonly characterised by relapse. The aim of this rapid evidence review is to identify, synthesise, and critically appraise the existing literature on relapse. Specifically, we will examine: definitions of relapse; prevalence of relapse; relapse trajectories; warning signs of relapse; determinants (i.e., risk and protective factors) of relapse; consequences or harms associated with relapse; and, relapse prevention, aftercare, and continuing care interventions explicitly designed to address relapse. By evaluating the evidence scientifically, we will identify what is already known (with implications for policy makers, clinical services, public health, and other stakeholders) as well as identifying crucial knowledge gaps that need to be addressed in future work.

UKRI Gateway to Research · FY 2025 · 2025-11

With the 10 warmest years on record all occurring in the last decade, we are on the brink of exceeding the Paris Agreement’s 1.5°C warming target. In response, the 2023 United Nations Climate Change Conference outlined targets to achieve net-zero emissions. Consequently, the need for projections of high-emission scenarios is waning, instead we need to know what climate recovery looks like. Yet, how climate will respond to a state of net-zero emissions and gradual CO2 removal from the atmosphere remains poorly understood. Hence, investigating the processes and implications of climate recovery becomes critical for informing long-term actions and policies. To date, climate scientists have used complex earth system models that integrate a vast array of processes across the atmosphere, ocean, land, ice, and living organisms to answer this question, but their different representations of climate components and interactions, such as climate feedbacks, ocean circulation, and sea ice, have led to diverging projections at global and regional scales.  This vital knowledge gap in our understanding limits our ability to guide accurate mitigation actions and policies. With a decade of experience developing novel statistical tools and simple physical models to improve historical estimates of climate states, I am now positioned to lead a world-class team and develop new modelling methods that integrate simple models, historical data, and AI to better predict future climate recovery. My novel modelling approach will be more accurate and quicker to run, and hence responsive to the rapidly evolving landscape of climate actions as we strive to achieve net-zero emissions. To achieve these aims, I will form an inter-disciplinary team including climate scientists, computer scientists, and stakeholder engagement experts.  My team and I will first examine the behaviour of temperature, rainfall, humidity, wind, and ice in recovery scenarios simulated by complex earth system models, with a focus on pinning down causes that lead to differences across models, a key challenge for improving projections (Objective 1).  Yet, even with these causes identified, integrating this knowledge into complex models in a timely manner remains challenging. Therefore, we will develop a simpler modelling framework, which first uses simple climate models based on essential principles of climate physics.  Parameters of the simple models will then be restricted by a range of historical instrumental and palaeoclimate records using a Bayesian statistical method.  Finally, we'll use AI techniques to enhance simple model predictions and generate high-resolution climate maps.  This combined approach is novel and will be easier to understand, constrain, quantify uncertainties, and faster to run (Objective 2).  Using projections from my team’s new modelling framework, we will evaluate climate recovery and its societal implications at both global and regional scales (Objective 3). Through workshop engagement and data sharing with key stakeholders, we will also ensure our new projections reflect end-user needs and are accessible and impactful to decision-making (Objective 4). In sum, my fellowship proposal addresses the next big challenge - what climate recovery will look like and why. It will also result in a novel climate modelling framework and more accurate projections that will be directly usable by scholars and decision-makers. Completion of the project will allow me to establish a world-leading research team and extend my expertise from climate and statistics to AI and making a real-world impact, enabling me to become a future leader in climate science and policy.

UKRI Gateway to Research · FY 2025 · 2025-11

The PHOTOMEM 2 research programme aims to transform the field of neuromorphic computing by creating next-generation devices that integrate light detection, memory, and computation within a single unit. These devices are inspired by the efficiency of the human brain, mimicking biological functions to enable real-time data processing with ultra-low power consumption. This work addresses the growing demand for energy-efficient artificial intelligence (AI) systems, particularly in applications requiring rapid decision-making, such as autonomous vehicles, robotics, and wearable technologies. Building on the successes of the initial PHOTOMEM programme, which developed artificial synapses combining optoelectronic and analogue memory characteristics in perovskite and polyoxometalate-based devices, PHOTOMEM 2 focuses on scaling up these single synapses into neural network arrays and integrating them with photonic circuits. The ultimate goal is to create a complete system for in-memory computing and retinomorphic vision, where devices emulate the retina’s ability to process visual information efficiently. By adopting innovative materials like 2D transition metal dichalcogenides (e.g., MoS2), ferroelectric polymers, and molecular metal oxides, the project aims to optimise performance for advanced applications, including in-sensor computing and Edge AI systems. The Key Objectives of this project are to: Develop nanoscale devices with coplanar nanogap electrodes to achieve high density, minimal energy consumption, and compatibility with photonic sources. Tailor materials to specific applications, exploring novel combinations and heterostructures to improve device performance and scalability. Incorporate light sources directly into the neural network to create compact, optogenetics-inspired computing systems with faster signal processing and reduced latency. The project represents a significant step beyond current state-of-the-art systems by addressing the limitations of traditional heterogeneous machine vision technologies, where data sensing and processing occur separately. Instead, PHOTOMEM 2 proposes a homogeneous approach that co-locates sensing and computation within the same unit, enabling faster processing, reduced latency, and improved energy efficiency. This integration is expected to open new possibilities for smarter machine vision systems with widespread applications. More specifically, the outcomes of this research are expected to impact several key areas, such as: Advanced Technologies: Enabling smarter, more efficient AI systems for autonomous vehicles, robotics, healthcare diagnostics, and environmental monitoring. Sustainable Electronics: Offering eco-friendly electronic devices that consume ultra-low power and support global sustainability goals. Scientific Advancement: Providing the research community with novel methodologies, materials, and device architectures that drive innovation in post-Moore’s Law computing. Economic Growth: Supporting the rapidly growing neuromorphic sensor market that is estimated to expand at a compound annual growth rate of 28% and beyond $550M by 2032 and fostering industrial collaborations for technology translation. Beneficiaries of PHOTOMEM 2 include researchers in materials science, optoelectronics, and AI hardware; industries focusing on Edge AI and sustainable technologies; and society at large, which will benefit from safer, smarter, and more energy-efficient innovations. This work is timely and aligns with the urgent need for scalable, low-power, and sustainable electronics in an increasingly AI-driven world.

UKRI Gateway to Research · FY 2025 · 2025-11

The immune effector functions of IgG antibodies can be fine-tuned by modification of conserved moieties, called N-linked glycans, within their Fc region. Antibody glycoengineering is of considerable biotechnological interest and has been utilised in several clinically approved antibodies, such as the cancer therapeutic Mogamulizumab (generated ~200 million USD revenue in 2023). Current methods of glycoengineering (which involve enzymatic modification of glycans in vitro, or manipulation of the antibody production cell line), are inefficient and yield heterogenous product. To solve this, we propose a structural and computational approach to develop novel enzymatic tools which specifically process IgG N-linked glycans, thereby increasing enzyme activity by proximity-driven effects. This will enable the manufacture of currently inaccessible IgG glycoforms. IgG glycans contain variable levels of fucose, galactose and sialic acid monosaccharide units, all of which influence antibody effector functions. The absence of fucose, and presence of galactose, potentiate activation of cell killing pathways by IgG antibodies, while sialic acid appears to impart anti-inflammatory activity. Conversely, elevated fucosylation has been established to be a desirable feature of antibodies with low cell killing properties (e.g. Simulect; Takeda UK Ltd v. F Hoffmann-La Roche AG [2019], High Court of Justice case no. HP-2018-000008). However, production of antibody glycans highly saturated in these units is impeded by the partial shielding of glycans by the antibody protein surface, which hinders glycan processing enzymes from accessing their glycan substrates. We aim to generate novel enzymatic tools for improved fucosylation, galactosylation and sialylation of IgG antibodies, using an approach divided into two stages: Structural investigations into existing glycosyltransferase enzymes which modify IgG glycans (Aim 1) Structure-guided, computational design of IgG-specific glycosyltransferase enzymes (Aim 2) Within Aim 1, we will investigate the structure and dynamics of enzyme targets catalysing addition of fucose, galactose or sialic acid units to IgG Fc N-linked glycans, using structural biology and computational modelling techniques. The output structural data will inform the computational protein design efforts in Aim 2, to harness the full potential of these natural biological systems. We will subsequently design three new IgG-specific, glycan-active enzymes (a galactosyltransferase, a sialyltransferase and a fucosyltransferase). Our approach to potentiate the activity of natural enzyme targets investigated in Aim 1 exploits bacterial endoglycosidases (EndoS and EndoS2 from Streptococcus pyogenes), which remove N-linked glycans from IgG. These enzymes specifically target IgG as their sole substrate, using a non-catalytic domain which binds the Fc protein surface. A strategy of proximity-driven enzyme enhancement can therefore be achieved by fusing our glycosyltransferase targets with an IgG-specific, non-catalytic Fc binding domain from EndoS/EndoS2. Structural information of enzyme targets from Aim 1 will be combined with our previous EndoS/EndoS2-IgG Fc crystal structures to inform the computational design of chimeric enzymes, using established deep-learning computational tools to generate suitable linker regions between catalytic and Fc-binding domains. The activity of novel enzymes against IgG glycans will subsequently be tested relative to the native enzymes, using established glycan analysis protocols. This project will combine expertise in structural biology, glycobiology and computational protein design to deliver the proposed aims. Our ambition is to provide new tools for research into fundamental biology of IgG glycosylation and translate this knowledge into the generation of novel tools for efficient manufacture of antibody glycoforms, which will find application in modification of existing therapeutics for precise modulation of their immune effector functions.

UKRI Gateway to Research · FY 2025 · 2025-11

Romantic relationships play a fundamental role in emotional well-being and mental health. More than half (58%) of therapists have reported an increase in clients presenting with relationship issues in the past year, according to the British Association for Counselling and Psychotherapy Mindometer survey. Many couples struggle with negative thought patterns that fuel misunderstandings and conflicts. One such pattern is hostile attribution bias (HAB)—the tendency to interpret a partner’s behaviour as intentionally hurtful. HAB can be a silent but powerful disruptor of healthy relationships, linking to aggressive responses and even intimate partner violence. My PhD research demonstrated that HAB plays a key role in the relationship between attachment security (the secure emotional bond with a partner) and relationship outcomes. However, further work is needed to raise public awareness of HAB's harmful effects and develop effective interventions to reduce its negative impact. The primary aim of my fellowship is to maximise the potential of my laboratory-based research to date, develop open-source materials for the field of relational aggression and intimate partner violence, and bridge the gap between laboratory science and clinical practice. Through this fellowship, I will disseminate the impact of my PhD research via several pathways, including: (a) Developing a self-assessment digital Toolkit to identify and reduce HAB. I will collaborate with national relationship-related organisations/platforms (e.g., OnePlusOne) to adapt my recently published scale, Hostile Attribution Bias in Romantic Relationships Test, into a practical self-assessment Toolkit. It will be widely and freely available to both research and clinical communities. Specifically, this digital Toolkit will maximise real-world impact by benefiting the general population, especially couples facing relationship challenges and relationship therapists; (b) Increasing public engagement. I will write at least four public-facing articles and blogs, making psychological research accessible to wider audience and translating research findings into practical advice for couples. These blogs will help individuals recognise and manage dysfunctional thought patterns in their relationships; (c) Publishing my work in leading psychology journals, broadening the academic impact of my research; (d) Open-sourcing the programs I developed based on PsychoPy, via platforms like GitHub, providing a valuable resource for fellow researchers interested in social cognition in romantic contexts; (e) Presenting at major international and national conferences.  To expand my professional network and disseminate my research, I will present at renowned international and national conferences. These conferences will facilitate discussions with leading relationship scientists, social psychologists, statisticians and research methodologies, and external organisations, creating opportunities for interdisciplinary collaborations. In addition, this fellowship will also support me to further develop relevant skills, to (a) undertake advanced statistical training to maintain a competitive edge in modern social psychology research; (b) lecture and supervise undergraduate, Masters, and Doctorate students; (c) complete the two remaining trainings toward full Emotionally Focused Therapy (EFT) certification (I have finished the foundation training), which will help me bridge the gap between academic research and real-world practical solutions.

UKRI Gateway to Research · FY 2025 · 2025-10

Infectious diseases were once the leading cause of death amongst men and women in almost all age demographics in the UK. However, the discovery of antibiotics revolutionised our ability to treat bacterial infections and, as a result, saved millions of lives. Bacteria inhabit almost every corner of our planet due to their incredible ability to adapt to different environmental niches. This capacity to evolve and survive even in the most inhospitable environments means that, following the introduction of a new antibiotic to our healthcare systems, resistant bacterial strains rapidly appear. This cycle has kept repeating until the emergence, in some instances, of infections that cannot be effectively treated with any currently available antibiotics. This is creating a dangerous situation where a "post-antibiotic" era is now becoming a reality, threatening all aspects of healthcare from cancer treatment to dental work. At the forefront of pathogens that can evolve multidrug resistance is Acinetobacter baumannii. This pathogen can infect individuals who are already sick or have a supressed immune system, leading to a variety of life-threatening clinical complications and, potentially, death. This creates a problem particularly in hospitals where most A. baumannii outbreaks occur. Prior to the 2000s, A. baumannii infections were relatively infrequent and, typically, very treatable. However, there has been a rapid increase in the number of these infections, such that this bacterium now accounts for 20% of all infections seen in Intensive Care Units (ICUs) worldwide. These infections are incredibly difficult to treat, with up to 75% of A. baumannii isolated from these patients being resistant to more than 3 types of antibiotic. Previously, we have shown that the artificial sweetener acesulfame K (ace-K), a compound is consumed by millions of people around the world every day in "sugar free" or "calorie free" food and drinks, has a remarkable ability to tackle this pathogen. We demonstrated that not only can ace-K inhibit this pathogens growth. It can also inhibit a range of virulent processes that it uses to establish infection, including the ability to move from the initial site of infection and the capacity of this bacteria to form communities called biofilms which help it overcome antibiotic therapy. Remarkably, we also demonstrated that this compound will make A. baumannii vulnerable to antibiotics that it has previously evolved resistance to. We now want to explore what exactly ace-K is doing to the cell to stop it growing and to increase its sensitivity to antibiotics. We will use a range of cutting-edge fluorescent microscopy, proteomics and molecular biology techniques to uncover exactly how ace-k effects the bacterial cell and resensitises it to antibiotics. We will develop, characterise and assess novel ace-K loaded wound dressings to tackle acute and long-term, difficult to treat infections and test them in a porcine ex vivo wound model. We will also test these loaded wound dressings in a mouse wound model to determine their capacity to treat infection. As ace-k is approved for consumption by every international regulatory body including the Food and Drug Administration, it means it has been extensively tested for safety. Therefore, there is significant potential that the use of ace-K as a therapeutic to tackle infection could be fast tracked to clinical trials and into hospitals. This would overcome one of the main barriers delaying the introduction of new antimicrobials drugs which is that all the safety testing and trials required before final approval can take over 15 years on average to complete.

UKRI Gateway to Research · FY 2025 · 2025-09

Although the volume and quality of experimental data from physical sciences is rising exponentially, methods for analysis and interpretation of resulting data are not keeping pace with this growth. At the UK’s major analytical science facilities, the National Research Facilities and for strategic and core equipment, high-throughput synthesis demands timely characterisation and analysis of samples. Particularly important is the ability to rapidly identify those samples that are most likely to give rise to useful data in an experiment. AI can play a key role in such ‘pre-experiment’ screening and subsequent experiment steering. A brief and low-cost initial data collection can be used to plan and steer the more resource consuming workflow of the main experiment that follows. Such high throughput screening can also enable autonomous laboratories by providing the feedback loop that drives an experiment towards a particular goal. This project brings together the Physical Sciences Data Infrastructure (PSDI), UCL, the Ada Lovelace Centre (ALC), central facilities and NRFs. A PSDI goal is to develop and support whole lifecycle data pipelines that are ready for AI, while the ALC is concerned with providing tools and services to enable more efficient use of (experimental) central facilities and their data products.     We will leverage the work of both PSDI and ALC by pairing this project with a related project led by ALC in the same call. This PSDI project will construct example data pipelines and a prototype ‘AI ready’ data repository, whereas the ALC project will work on specific applications in central facilities and in home laboratories that use the PSDI developed infrastructure. The approach will be driven and validated across a range of use cases producing well curated datasets with well-defined outcomes from diffraction and microscopy experiments/facilities. The use cases for building pipelines and the repository will be centred on: Serial small molecule crystallography (Diamond Light Source beamline I19) Materials powder diffraction (Diamond Light Source beamline I11)    Project M crystallisation and diffraction outcomes dataset (https://www.diamond.ac.uk/ProjectM/) Single crystal electron diffraction (National Electron Diffraction Facility) Autonomous TEM control to enable automated imaging, driving image segmentation and classification (UCL TEM facility) Furthermore, with the view of testing the AI ready nature of the repository contents, a service will be deployed for the AI-driven (CrystaLLM) prediction of crystal structure from composition and experimental X-ray diffraction data (UCL). This project draws together domain experts necessary for the categorisation and collection of highly curated and trustworthy datasets, with data engineers and research software engineers, to build data pipelines that feed the repositories and associated services hosted by PSDI. The project therefore addresses a problem that is common across many sciences: what does it mean to generate trusted ‘AI ready’ data, and how can data be assembled into collections that are useful as training data for AI tools and systems that accelerate how science is done?

UKRI Gateway to Research · FY 2025 · 2025-09

Ocean crust is produced during submarine volcanism along mid-ocean ridges, repaving two-thirds of Earth's surface every 200 million years. Yet it remains relatively unexplored, accessible only using submersibles or scientific ocean drilling. Such exploration revealed that seawater circulates through the cooling crust and reacts with the rocks, transporting heat and chemicals to the oceans. This “hydrothermal circulation” makes important contributions to Earth’s long-term biogeochemical cycles. During submarine volcanism carbon dioxide (CO2) is released from the magma to the oceans and atmosphere, but during subsequent hydrothermal circulation, calcium carbonate minerals form storing CO2 from seawater in the rock. Consequently, the formation and evolution of ocean crust affects atmospheric CO2 levels and hence climate. The role of ocean crust in the planetary carbon cycle depends on the balance between the CO2 released during formation of new crust and the CO2 sequestered during hydrothermal reactions throughout the crust's lifetime. Global variations in the extent and timing of hydrothermal calcium carbonate formation therefore have the potential to drive significant changes in the Earth system. Along mid-ocean ridges hydrothermal circulation occurs through spectacular “black smoker” hot springs, but it can occur wherever heat drives fluid flow through the ocean crust. Consequently, gaining a complete understanding of the full complement of hydrothermal exchanges between the crust and overlying oceans across all tectonic settings is key to determining past hydrothermal contributions to global biogeochemical cycles and their role in driving global change. Until recently volcanism was thought to occur in three geodynamic settings: divergent plate boundaries (including mid-ocean ridges), convergent plate boundaries (including subduction zones) and hotspots. However, a new type of volcanism that occurs due to flexure and fracturing of oceanic plates before they subduct, termed ‘petit-spot volcanism’, was discovered in the Japan Trench in 2006. Petit-spot volcanism, now known to be ubiquitous where ocean plates flex, is predicted to make important contributions to Earth’s CO2 emissions because the magmas are enriched in CO2 relative to elsewhere in the oceans. However, the overall role of petit-spot volcanism in the global carbon cycle depends on the extent to which these emissions are balanced by subsequent hydrothermal reactions. International Ocean Drilling Programme Expedition 502 will recover the first in-situ section through petit-spot lavas, allowing their role in Earth’s long-term carbon cycle to be quantified. This research will use these unique cores to: -Quantify the exchanges between petit-spot lavas and the oceans, including the extent of carbon-uptake, due to different styles of hydrothermal alteration. -Determine the ages of hydrothermal minerals and hence the timing and duration of these exchanges.   These results will allow us to achieve our overall objective of evaluating the role of petit-spot volcanism in long-term global biogeochemical cycles, including the carbon cycle. The resultant more complete understanding of Earth’s past carbon cycle will benefit efforts to model past climate change due to elevated atmospheric CO2, and hence our ability to predict potential future climate change due to anthropogenic CO2 emissions. The knowledge of how petit-spot lavas and their reactions with seawater affect the characteristics of crust entering subduction zones will also aid studies of these plate boundaries where major earthquakes and their associated natural hazards (e.g., tsunamis) occur.

UKRI Gateway to Research · FY 2025 · 2025-09

The magnitude of future anthropogenic warming is uncertain and will depend upon the strength of different carbon cycle feedback mechanisms. These are processes in the Earth system that alter the concentration of atmospheric CO2 and can either amplify warming (a positive feedback) or reduce warming (a negative feedback). Future climate change projections suggest that the combined effect of known climate feedback mechanisms is to amplify CO2-driven global warming. However, climate models are blind to the ‘unknown unknowns’ - these are the things we know little about but have the potential to take future climate into unimagined directions. The geological record captures the response of the climate system to all feedbacks in operation, including those we don’t know about. Earth’s history includes several short-lived warming events (‘hyperthermals’) that occurred tens of millions of years ago and can provide unique insights into the unknown feedbacks that may operate in the future. Exposure of rock organic carbon at the Earth’s surface can release carbon dioxide (CO2) and may have been an important carbon cycle feedback during hyperthermals, potentially enhancing and prolonging global warming. However, this feedback is not included in state-of-the-art Earth system models. We hypothesise that rock organic carbon oxidation is a universal positive feedback mechanism associated with rapid warming events and is capable of prolonging global warming for thousands of years. However, the lack of empirical data means that our knowledge of how this feedback operates during past warming events remains a major gap in our understanding, with potentially important consequences for the magnitude of future global warmth. Crucially, the techniques that have been developed to measure rock organic carbon oxidation in the modern environment (radiocarbon) cannot be applied beyond the last 60,000 years. We will address this knowledge gap using a novel tool based on lipid analysis. Lipids are organic molecules that are essential to life and produced by all biological organisms. During burial, lipids undergo structural transformations and are transformed into more stable compounds. These so-called ‘fossil’ lipids have been used to trace input of old, reworked organic carbon into aquatic environments. However, we lack a mechanistic understanding of how ‘fossil’ lipids translate into oxidative weathering fluxes and ultimately CO2 release. To make this crucial step forward, we will (i) measure ‘fossil’ lipids in contemporary environments and (ii) develop new metrics to quantify CO2 release via rock organic oxidation. This knowledge will be applied to several hyperthermal events to quantify rock organic oxidation and CO2 release during global warming events for the first time. To develop a proxy for oxidative weathering, we will measure fossil lipids in modern shale weathering profiles and calibrate this against in-situ contemporary measurements of oxidative weathering (WP1). To enable successful application in the geological record, we will explore how the ‘fossil’ lipid signature is modified along the land-to-sea continuum by measuring lipids in modern rivers (WP2) and marine sediments (WP3). To determine whether rock organic carbon oxidation is an intrinsic feedback associated with rapid warming events, we will apply our proxies to three past warming events associated with different magnitudes of warming (WP4), helping to constrain the temperature sensitivity of this positive climate feedback mechanism. Our data-driven approach will reveal how rock OC oxidation operates during past warming events and will evaluate whether Earth system models currently underestimate CO2-driven warming in past warm climates.

UKRI Gateway to Research · FY 2025 · 2025-09

The figure of the “migrant” is a deeply politicised one. Some mobilities are problematised and increasingly criminalised, whilst others are seen as unremarkable, even celebrated, and not framed as migrations. Migratisation, or the construction of some people – and not others – as migrant outsiders, is a social process. In other words, migrants are not born, but made. Scholarship on migratisation has come to recognise the significant role played by racialisation in this process. At the same time, there is still a tendency to assume that those who are racially minoritised are equally disadvantaged in economic terms, or that racially minoritised individuals of relative class privilege are free from discrimination. My PhD research shows that the effects of class privilege do not cancel out those of racial minoritisation, and that race and class are co-constitutive in processes of migratisation. My PhD thesis shows that cultural capitals such as Western educational qualifications, ability in Western languages, professional experience and other competencies are often contested when they are held by those who are racially minoritised. Based on analysis of longitudinal biographical narrative interviews with racially minoritised privileged migrants incorporating music elicitation, I show that refusals to recognise the legitimacy of such capitals can trigger migratisation, or the framing of the capitals’ owners as out of place and belonging elsewhere. Crucially, the intersections of race and class in processes of migratisation mean that a person can be treated as a migrant whether or not they have actually moved. This extends to racially minoritised and mixed-race citizens of Western states, where they may have lived all their lives. My PhD thus draws out the shared struggles between "migrants" and "citizens" alike, underscoring the urgent need for collective commitments to antiracism and social justice across civil society. In this fellowship, I will disseminate the contributions of my PhD thesis widely, to both academic and non-academic audiences. I will produce high-quality articles for reputable academic journals, present my findings at key sociological conferences internationally, develop a book proposal based on my PhD research and work towards a draft of the monograph. I will engage policymakers and non-academic users of my research by partnering with PublicPolicy@Southampton, a centre which specialises in connecting academics with policymakers and non-academic stakeholders. I will conduct stakeholder analysis, produce a policy brief and organise a workshop to communicate my findings to practitioners with a remit for social mobility, equality, diversity and inclusion. This fellowship will also build my research capacity. I will pursue training in research leadership, project management and grant writing. Based on this training, I will develop funding proposals for my next research project on the retention and progression of racially minoritised and mixed-race individuals in accredited professions such as education, law and medicine. I will conduct limited further research as part of a pilot study for this project. Lastly, I will broaden my teaching experience by engaging in teaching activities within the department. Through this fellowship programme of work, I will develop myself as an academic researcher.

UKRI Gateway to Research · FY 2025 · 2025-09

This proposal contains the main research goals of the Southampton LIGO-Virgo-KAGRA (LVK) Gravitational Waves group for the period 20025-2028.  It consists of two Themes, both central to the LVK science remit. Theme 1 concerns searches for continuous gravitational waves signals (CGWs) from spinning neutron stars (NSs).  No such signal has been detected yet, but the first detection could come at any time.  CGW searches typically assume a signal template, which is then compared against the detector data.  The template’s phase needs to match the signal over the course of the observation.  For known NSs this is not a problem, but for unknown NSs, or know ones with unknown spin frequency, this requires a search in the very large space of the NSs spin-down parameters and (if relevant) sky location.  This makes the searches computationally very expensive.  It also renders the searches vulnerable to sudden step changes known as glitches in the signal, a phenomenon known to be common in the electromagnetically observed NS population. The Project Lead has previously led a study confirming that this is a real issue for CGW searches, with the NSs that spin-down most rapidly, and are therefore potentially the strongest CGW emitters, glitching the most often and the most strongly. In Theme 1 we will devise modifications to the hierarchical search pipelines commonly used in CGW searches to see where the effects of unmodelled glitches first degrade detection efficiency, and how to then make the pipelines robust against such glitches, while being mindful of the computational cost. Theme 2 concerns systematics in waveform models for compact binary coalescence events.  With nearly one hundred such events now reported, a statistically meaningful array of source parameters has now been assembled.  However, the parameter estimation itself makes use of phenomenological waveforms that approximate accurate waveforms produced by full numerical relativity simulations.  These approximations introduce systematic errors into the parameter estimation, on top of the random errors that the finite signal-to-noise introduces.  As the sensitivity of the detectors improves for O5, the random errors due to noise will shrink, exposing systematic biases and potentially degrading all parameter estimation in future Observing Runs, and limiting our ability to carry out our science goals such as testing General Relativity and probing the high-density equation of state.  Indeed, there is evidence that this was already a problem for a handful of detections in observing run O3.  We plan to build on our existing expertise in investigating systematics to extend an in-preparation procedure for identifying systematics in waveform models to fully generic signals. At the moment, this procedure is prototyped for simple aligned-spin, quadrupolar signals, and the work outlined for this grant will extend the method to work with fully precessing models with higher multipoles. Another goal of this project is to increase the efficiency of the method, allowing for on-the-fly systematics estimation in Bayesian model selection schemes. We are asking for staff time for both Themes, and a PhD student for Theme 1, and a RIA (i.e. post-doc) for Theme 2.  

UKRI Gateway to Research · FY 2025 · 2025-09

Black holes and the Big Bang are extreme events of our Universe that are not yet properly explained so far. One reason for this is a lack of a consistent theory that merges two pillars of theoretical physics, quantum field theory and general relativity. This theory, named quantum gravity, remains elusive despite decades of attempts at formulating it. Understanding the nature and the properties of quantum gravity is one of the most challenging problems in fundamental sciences, and doing so would open up new directions in quantum theory and help to unlock the technologies of the future. The goal of this research proposal is to understand the structure of quantum gravity theories and black holes at a deeper level, through the framework of a conformal field theory (CFT). A CFT is a physical theory which is invariant under changes in its length or energy scale. CFTs appear to play an important role in our universe - they describe microscopic properties of quantum gravity theories and black holes, yet we are far from understanding why this is the case. My goal is to advance our understanding of quantum gravity via probing its unexplored CFT foundations. I aim to understand how CFTs give rise to consistent theories of quantum gravity that are suited to describe our present-day Universe. I propose a new framework which merges three areas of research in theoretical physics, namely CFT spaces, holography, and string theory, and makes it possible to explore new features of these directions in parallel. Within the proposed framework, I aim to address the key research questions: What are the quantum building blocks of black holes? Where are these building blocks located? What do they look like? How do they radiate their energy? What are the discrete symmetries of black hole quanta? The results of the proposed research project will advance our understanding of quantum gravity theory and black holes of the universe.

UKRI Gateway to Research · FY 2025 · 2025-09

CD8+ ‘killer’ T-cells (T-cells) are fundamental in immune surveillance for recognition and destruction of tumour cells, by detecting tumour-specific proteins (antigens) displayed at the cell surface on Major Histocompatibility Complex class I (MHC-I). Effective T-cell targeting of tumours relies on a tightly regulated and effective antigen processing and presentation (APP) pathway, a system present in all mammals however is highly complex in humans due to the variation in MHC-I expressed in individuals. Therefore, mouse models are unlikely to fully recapitulate human APP and may not be effective in understanding the mechanism and effect of this complex system. During tumour evolution, several mechanisms are adopted to escape detection by T-cells, including changes to the function and expression of APP components resulting in a reduction/loss of MHC-I at the cell surface, a common feature observed in many cancers. The loss of MHC-I influences levels of infiltrating T-cells and response to checkpoint inhibitor immunotherapy. Whilst studies have investigated the functionality of T-cells in resistance to immunotherapy, few have characterised the role of APP on T-cell responses and treatment success/failure. This project aims to establish a patient-derived tumour organoid (PDO) T-cell co-culture system from HPV+ oropharyngeal squamous cell carcinoma to replace the use of mice in characterising the impact of APP on anti-tumour T-cell responses. Our objectives are to 1) establish a robust methodology for the PDO co-culture system and functional assessment of T-cell responses, 2) characterise APP mechanism in each PDO by determining the expression and mutation profile of key components, the cell surface expression of MHC-I and anti-tumour T-cell function, 3) modulation of APP with specific inhibitors/activators, and how this impacts on T-cell responses and immunotherapy efficacy. This model will be essential for replacing the current use of mice and provide a more relevant/better understanding of the contribution of APP alterations on effective T-cell responses in cancer. It will provide key knowledge on how to improve MHC-I antigen presentation in a patient-specific manner, how this influences the response to immunotherapy, as well as the potential to identify patients who are likely to benefit from immunotherapy with the addition of APP modulation. Furthermore, once established, this model system will provide a key tool for researchers investigating specific APP components in disease (cancer, viral infection and autoimmunity), as well as being adopted for other cancer systems, giving rise to patient specific understanding on how antigen processing and presentation influences T-cell responses in these systems.

UKRI Gateway to Research · FY 2025 · 2025-09

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 2025 · 2025-09

The SPICA project brings together experts from the UK, Germany and Indonesia to create new ways of making electronic devices secure, especially those that need to work in extremely cold environments—like those found in quantum computers, satellites, and cryogenic sensors. Most security features in electronics we have today, such as those that generate random numbers or create unique digital fingerprints, rely on conventional transistor technology. However, these technologies don’t work well at very low temperatures, which can make them unreliable and easier to hack. To solve this, our team is exploring the use of a new type of electronic component called a memristor. Memristors are tiny, fast, and use very little power. They work in a way that is similar to how connections in the human brain operate, changing their properties based on the movement of atoms inside them. SPICA will exploit this unpredictable atomic movement to generate truly random numbers and create unique digital fingerprints encoded in atomic scale that are impossible to replicate—even in freezing conditions. Our project brings together specialists in materials, device engineering, and circuit design from three leading institutions. By combining our skills, we aim to develop new, energy-efficient and deployable security primitives that are reliable even at extremely low temperatures. Our work will help protect cutting-edge technologies from hacking and tampering, paving the way for next-generation semiconductor security. Ultimately, this collaboration will help us build long-term partnerships and open up new research opportunities in the field of secure, tamper-resistant electronics.

UKRI Gateway to Research · FY 2025 · 2025-09

We seek to improve the efficacy, efficiency and reproducibility of focused ion beam (FIB) nanofabrication processes for advanced photonic materials and devices, and in turn their optical performance and energy efficiency, through the application of deep learning. Our methods will enable rapid optimization of nanostructures for optical function informed by real process and material characteristics, rather than analytical/numerical approximations or wasteful trial-and-error. Deep learning offers a novel, systematic, data-driven approach to modelling the FIB milling process that is applicable to arbitrary nano/microstructural geometries in any target medium, whereby milling outcomes can be accurately predicted without the need for knowledge or understanding of (often unavailable/inaccessible) material parameters, the fundamental physics of ion-atom interactions, or the mathematical description of time-dependent 3D structural geometry. We will show how neural networks can: rapidly accrue understanding of the complex relationships among numerous sample and system parameters that affect process outcomes for a variety of metal, semiconductor and dielectric target materials commonly used in nanophotonic devices, to expedite or negate the need for conventional 'dose testing'; be configured to solve challenging inverse problems, answering the question "what input design will generate a desired output structure?"; optimize (rather than just simulate) milling processes, to answer the question "what input design and process parameters will best deliver a structure with prescribed optical and/or nanomechanical properties?". Alongside these trained functionalities we expect emergent capabilities, such as the ability to make accurate predictions for unseen target media, and inherent compensation for systematic artefacts. The project aligns to the EPSRC strategic priority on "Frontiers in Engineering and Technology": it will leverage novel capabilities and ideas in deep learning and nanophotonics to facilitate "breakthroughs in ... tools and techniques enabling researchers and businesses to make, measure and model more efficiently and effectively," and to "accelerate design to manufacture of the new materials needed for a more resilient, sustainable UK". FIB milling is a key enabling technology in many areas of fundamental and applied research, and high-tech (electronics and photonics) industrial applications of importance to the UK's position at the forefront of physical and bio sciences research and advanced technology development - for micro/nanoscale rapid prototyping, materials/device characterisation and cross-sectional/tomographic imaging (including in support of other high-throughput, e.g. lithographic, nanofabrication processes), and transmission electron microscopy sample preparation. Our initial focus will be on applications in nanophotonics (e.g. to the optimized fabrication of metasurface optics and energy-efficient optomechanical time crystals), but the techniques developed will be transferrable to beneficiaries in other domains of engineering, physical science and technology, deployable on any FIB platform, and indeed adaptable to other direct-write micro/nanofabrication processes.

UKRI Gateway to Research · FY 2025 · 2025-09

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 2025 · 2025-09

This project aims to pioneer an integrated, high-throughput approach for accelerating the design and qualification of new austenitic steels for creep-fatigue environments. The key objectives are: Design new alloy compositions with improved phase stability by combining combinatorial experiments and computational thermodynamics modelling. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Address the low-throughput limitation of creep-fatigue testing by leveraging full-field strain measurement techniques to analyse a single sample containing multiple compositions. It is fully aligned with the vision, and now requires the capital investment underpinning the “Materials 4.0” Big Idea, put forward by the Royce to the EPSRC, emphasising the need for integrated tools, protocols, and methods to accelerate materials discovery, testing, and characterisation. By working with the Royce my aim is to shorten the development cycle for new materials, which typically spans 10-20 years for safety-critical applications at present. This lengthy timeline poses a significant barrier to meeting our 2050 net-zero commitment. This project proposes a ground-breaking solution: an integrated, high-throughput framework designed to accelerate materials innovation. The UK’s next-generation high-temperature nuclear reactor (HTGR) offers an ideal environment to showcase this novel approach due to its far-reaching impacts, and unique regulatory conditions compared to other sectors. Specifically, the HTGR design requires a safe and efficient heat transfer system with a 60-year lifespan, making the long-term integrity of heat exchangers and boiler components critical. The principal degradation mechanism is creep-fatigue, a significant material challenge that must be addressed during the design phase. The PI, a newly appointed Professor at Southampton, currently lacks the full range of facilities and resources required to realise the project aim. By utilising the Advanced Metals Processing (AMP) facilities at Royce and collaborating with the AMP Area Leads, this project will enable the manufacturing of samples with tailored compositional gradients. Further, Southampton's expertise in combinatorial approach for thin-film material synthesis and screening will be leveraged to intelligently bypass its intrinsic scale-up limitations. Additionally, Southampton’s full-field measurement capabilities will be fully utilised to enable the simultaneous verification of creep-fatigue behaviour in multiple compositions on a single sample, significantly overcoming the constraints of conventional low-throughput testing methods. This collaborative effort not only unites complementary expertise and resources of different institutions but also creates synergies that amplify the impact of each contribution. Our vision is a step-change in development time and cost savings associated with materials innovation. While this project focuses on advanced nuclear fission, the high-throughput methodology developed will benefit a broader community, including those working on fusion, ultra-supercritical power, conventional power plants requiring fuel flexibility, long-term operation of advanced gas-turbines, and petrochemical plants. As a result, this project will also benefit the Royce in its mission to accelerate the introduction of new materials into industrial applications. This project is inherently interdisciplinary and directly addresses the challenges facing next-generation nuclear, which is essential for enhancing the environmental and economic benefits. By successfully overcoming the creep-fatigue material challenge, this project will unlock the full potential of HTGR technology, enabling the elevated nuclear heat to decarbonise the hard-to-abate sectors, which currently generate 25% of global energy-related CO2 emissions. In terms of applications, our accelerated materials discovery framework is ultimately linked to both national and international drivers, such as the transition to zero carbon, sustainable materials and manufacturing, and the circular economy.

UKRI Gateway to Research · FY 2025 · 2025-09

Organic synthesis is the engine that powers the advance of science and technology. Millions of scientists around the world rely on innovations in organic synthesis to tackle the challenges we face in the 21st century – from energy and the environment, to medicines and materials. This project will provide efficient and sustainable methods for the discovery and production of the molecules that society relies on, in particular medicines and agrochemicals. This will be achieved by delivering new reagents that will lower costs and minimize hazardous waste streams, whilst remaining practical and easy-to-apply in both an academic and industrial setting. This project revolves around the development of a new class of compound called Dual-Function Reagents (DFRs). These reagents are unique as they will perform multiple roles during a reaction. This will change current mindsets around reaction development within the field and lead to safer, practical and more efficient ways to make molecules. The project will initially focus on the development of DFRs for carboxylation. Advancing the state-of-the-art in carboxylation has been chosen as these reactions provide carboxylic acids which are versatile building blocks and important products in many sectors. Carboxylation is also a powerful method for adding isotope labels onto a molecule. Isotope labels are vital in scientific discovery and the development of drugs and agrochemicals as they allow scientists to follow the progress of a molecule, for example to check that it is reaching the correct location within a patient, or to check that it is not polluting the environment. Unfortunately, labelled compounds are difficult to produce as they are prohibitively expensive to make and often rely on the use of reagents that are radioactive and sourced from regions with political tensions with the UK. The DFRs developed through this project will significantly impact the field as they will greatly improve efficiency around the preparation of labelled compounds, thus minimizing costs, waste and reliance on unstable trade routes. DFRs will also provide practical and safety benefits by avoiding hazardous and difficult-to-handle chemicals, such as organometallics and gaseous reagents. DFRs will be applied in a range of transformations that are important to academia and industry, such as the incorporation of sulfur groups and amides. This will lead to DFRs showing a variety of applications within the pharma-/agrochemical industries and beyond. Overall, my DFR concept will provide safer, cleaner, and more sustainable ways to make a range of important molecules that society depends upon.

UKRI Gateway to Research · FY 2025 · 2025-09

By conducting this international fellowship at the Research Institute for Humanity and Nature in Japan, I aim to create an immersive and interactive artwork that blends art, film and technology. This exhibit will help us discover more about the complex nature of the self, understand the present, and explore the interaction with the technology. By adopting a multidisciplinary approach combined with AI technology, it invites audiences to step into the cinematic world and interact with a shadowy, ghost-like humanoid figure. It will offer a creative reflection space where horror and technology intersect, and the eerie, supernatural presence becomes an expression that explains our complex, indescribable emotions and hidden anxieties while exploring our relationship with technology, as well as how we see and understand ourselves and our place in the world in the era of digital advancement. Inspired by the Japanese horror film Kairo (2001) and as a further development of my PhD project on the representation of the female ghost in Chinese cinema, I intend to expand my research into an immersive and participatory experience which people can feel, hear and interact with. Through this approach, this project offers a playful way for audiences outside academia to experience East Asian supernatural traditions, contributes to the broader landscape of horror and cultural studies, and fosters cross-cultural appreciation and dialogue. This project also encourages a multidisciplinary discussion on the interrelations between the fields of art, the humanities, and technology beyond theoretical contributions.

UKRI Gateway to Research · FY 2025 · 2025-08

The prevalence of camera technology has undoubtedly reshaped our lives, offering enhanced communication, security, and innovative possibilities. However, this widespread integration has raised serious concerns regarding personal privacy and security. Many individuals are under constant surveillance, leading to altered behaviour and emotional distress. This concern extends to sign language users relying heavily on camera-based Sign Language Recognition Technology (SLRT). These users encounter the same privacy issues, which can lead to self-censorship, fear of judgment, and emotional strain. Moreover, the increasing proliferation of smart technology, particularly those designed for spoken language recognition and communication, excludes sign language users from accessing and utilizing these tools, further deepening the digital divide. Addressing these pressing concerns and provide sign language users with the freedom to communicate without compromising their privacy requires a technology that adapts to sign languages while safeguarding personal privacy. This project seeks to bridge this gap by introducing radar technology as an innovative alternative, primarily focusing on British Sign Language (BSL) users. Radar technology offers a distinct advantage – it can recognise sign language gestures without capturing visual images, ensuring signers' privacy. However, the key challenge lies in the limited research on radar-based sign language recognition and the absence of publicly available radar databases essential for developing and testing algorithms. This project addresses these challenges through a well-thought-out approach. Central to this effort is the development of LinguaRadar, an advanced Sign Language Radar Simulator specifically designed to capture the intricate nuances of BSL (Objective 1). LinguaRadar goes beyond the basics, incorporating the complexities of facial expressions, detailed finger movements, and the subtleties of body posture. It achieves this by extracting animation data directly from monochrome videos, presenting a game-changing opportunity to use publicly available video databases to generate substantial data. Leveraging this unique capability, the project also focuses on creating a comprehensive radar dataset (Objective 2). This dataset will form the foundation for refining and validating our Language and Learning Models (LLMs), which are crucial for recognising patterns and correlations within radar data and facilitating accurate BSL sign recognition (Objective 3). Ultimately, the project aims to develop a hardware prototype (Objective 4) to translate BSL radar data into spoken commands, enabling a signing interface for widely used virtual assistants like Alexa. This project holds substantial promise with far-reaching impacts. Firstly, developing a simulator capable of utilising existing videos saves data collection efforts and aligns with sustainability goals by reducing the digital carbon footprint. This contribution aligns with the UK's mission of achieving NetZero by 2050. Secondly, creating extensive radar synthetic datasets addresses a significant data shortage issue within the radar community. Most notably, the potential societal benefits extend beyond British Sign Language (BSL) to encompass other sign and non-sign language gestures, broadening the reach and impact of this research. This project transcends academic boundaries, actively seeking to translate its findings into practical applications through workshops and industry demonstrations. This approach ensures that our research delivers tangible solutions, benefiting BSL users and a wider audience. Principal Investigator's unique expertise in radar technology and machine learning, combined with the diverse and skilled research team, including linguistic experts at the Centre for Speech Technology Research (CSTR) at the University of Edinburgh and the Deafness Cognition and Language Research Centre (DCAL) at University College London, positions us ideally to execute this interdisciplinary project successfully.  

UKRI Gateway to Research · FY 2025 · 2025-08

Skeletons are widespread across animals on planet earth. Within our skeletons, but also the skeletons of most animals, there are hundreds of differently-shaped and -sized elements. A femur, for instance, is distinct from a pelvis and a skull. In vertebrates, skeletons are made out of bones, but other animals across the tree of life have different, but equally vital hard, crystalline structures providing support and protection. These skeletal structures, as well as human bones, are called biominerals, because they are produced by biological processes. Biomineralised skeletons are built by the activity of specialised cells which exhibit precise control over the size, shape, and orientation of the crystals they build. How these cells can produce hundreds of different skeletal elements with diverse shapes and sizes, all within a single organism, remains unclear. Animal growth and development relies on signalling pathways, a group of molecules which help cells to send and receive information from their surrounding environment.  We aim to test the hypothesis that the different activity of signalling molecules around skeletal cells regulates the shape, size, and ultimately the diversity and complexity of skeletal elements during development. Understanding how biomineralising cells build different skeletal elements is crucially important, as these processes occur as a part of normal development in every human, and billions of other animals on planet earth. The World Health Organisation lists musculoskeletal conditions as the leading cause of disability worldwide, effecting 1.71 billion people. Specifically, skeletal dysplasias, where bones form abnormally, can result from dysregulation of signalling pathways during development. Thus, while our proposed work is basic science, it has the potential to inform on fundamental biological mechanisms relevant to human health. During skeletal development, a low number of cell types is able to construct highly complex and diverse tissues. An extreme case of this phenomenon is exemplified by the sea urchin, our model system for the proposed research. The sea urchin skeleton includes hundreds of differently-shaped skeletal elements, all of which are built by a single type of cell, called the sclerocytes. This makes the sea urchin an ideal model species in which to understand how signalling pathways interact with a single cell type to build a vast array of skeletal shapes and sizes. We will address three primary hypotheses with our proposed work: (1) differential signalling regulates sclerocyte position in specific skeletal elements; (2) signalling mediates differences in gene expression in sclerocytes across the skeleton; and (3) variation in shape, size, and complexity of elements is the result of different signalling pathways. We will test our first two hypotheses by analysing developmental gene expression during development in high resolution, and experiments on signalling pathway function. To test the third, we will use micro-CT scanning and harness artificial intelligence by using deep learning-assisted image processing to produce and analyse a massive dataset of skeletal anatomy. All together, our approach will span from genes and cells, up to biomineralised anatomy, providing a holistic, whole-organism understanding of development. Specifically, our work will answer a crucial question at the heart of skeletal biology: how do molecular and cellular processes shape different parts of the skeleton. In doing so, we will produce novel comparative resources for skeletal and developmental biologists and clarify the general mechanisms of how skeletons grow and develop across the tree of life.

UKRI Gateway to Research · FY 2025 · 2025-08

Textiles date back to over 8,000 years and are the most pervasive and closest interface to humans. Unlike existing wearable technologies, electronic textiles (e-textiles or smart textiles) can become fully imperceptible and have the potential to revolutionise sensing, healthcare, and digital human interfaces. However, integrating electronics in textiles and withstanding the rigours of use is far from trivial, and published work remains impractical. The vision of this programme grant (PG), SUSTAIN, is to address the fundamental research challenges that currently limit the application of e-textile technology enabling it to become highly functional, practical, sustainable, convenient, and truly imperceptible to the user. The programme enables cross-disciplinary challenges in electronics, materials and manufacturing, circular economy (CE), textile engineering, and garment design to be jointly tackled through cross-linked work packages (WPs). Our overarching goals are to: Create an array of novel heterogeneous e-textile components and sub-systems. To develop a range of Life Cycle Assessment (LCA)- and design-driven electronic integration flows for responsible e-textiles. Co-create demonstrators fusing our design and manufacturing approaches spanning exemplar applications in health and fitness monitoring, smart workwear, and sports performance. Our research crosses disciplinary boundaries to deliver these goals through novel topologies for heterogeneous electronic devices that address the fundamental limitations of state-of-the-art e-textiles. Split into three technical WPs, we will develop novel sensing modalities and interfaces (WP1), wireless and RF technologies for connectivity power, and sensing (WP2), and energy harvesting and storage devices (WP3). These technical WPs are guided by 3 cross-cutting WPs addressing holistic garment design and co-creation challenges (WP4), sustainable manufacturing and life-cycle assessments (WP5), and bi-directional user- and stakeholder engagement (WP6). A programme grant approach is required to bring these elements together and ensure practical, sustainable, user-centric e-textile developments. The technical challenges addressed across WPs 1-3 are highly interlinked. For example, direct wireless RF interfaces will be co-designed with electrochemical biomarker sensors, multiplexed using flexible and organic semiconductors. In energy harvesting and wireless power, large-area devices such as textile rectennas and supercapacitors or batteries will be co-designed in self-storing energy modules. Moreover, triboelectric sensors and power harvesters will be co-designed with garment considerations and interface electronics to overcome their fundamental performance limitations. The enabling semiconductor devices will comprise bespoke and off-the-shelf heterogeneous devices across device technologies, driven by life-cycle assessments to minimise their environmental footprint while maximising reliability, creating garment-scale "chiplets".

UKRI Gateway to Research · FY 2025 · 2025-08

As data-driven governance gains prominence, fostering spaces for public engagement with data is crucial. This project focuses on creating data publics where citizens interact with data through creative and cultural methods to explore societal impacts. Our objectives are to: 1. Identify the data and the creative and cultural methods used in government and third-sector governance systems and decision-making. 2. Examine the platforms and processes enabling effective interactions between creating data publics and government and third-sector decision-making. 3. Recommend how government and third-sector decision-makers can engage with creating data publics to enable equitable and effective governance systems. In an era of increasing datafication, many citizens remain unaware of how data are collected and used to influence decisions. While mainstream solutions emphasize open data or data literacy, these approaches alone fail to ensure meaningful public engagement. Instead, creating data publics empowers citizens to participate in data generation and deliberation through creative and cultural methods. These interventions position data as relational, highlighting its cultural, political, and economic significance. Efforts to create data publics encompass diverse methods across various contexts. While this heterogeneity strengthens the approach, it challenges understanding how these projects can best support governance and address concerns about their effectiveness. This project will compare UK and Canadian cases and engage expert practitioners working on such projects to better understand how creating data publics applies to governance. This comparison will provide a framework for international best practices in community consultations and policy interventions. The work plan and timeline consist of three phases. Phase 1 is a scoping review of UK and Canadian cases focused on data, methods, and governance. Phase 2 involves a Futures Forum gathering stakeholders from both countries to discuss interaction mechanisms. We will share results from both phases via public reports, blogs, and an evidence brief. Finally, Phase 3 will disseminate findings through multi-modal outputs targeted to specific audiences, aiming to provide actionable insights for future data public initiatives. The project team will also participate in a virtual knowledge mobilization forum to share findings with community practitioners and stakeholders. The project emphasizes governance through cultural openness rather than just open data. By investigating creating data publics, we aim to advance sustainable, inclusive governance models, transforming public engagement and decision-making through creative and cultural data practices. Outcomes will assist policy researchers and makers in Canada and the UK in fostering equitable governance through community engagement. Insights from research institutes and their local government and third-sector partners will be shared via blogs, offering frameworks, toolkits, and methodologies to enhance decision-making platforms. These contributions will support an emerging transatlantic community of practice for creating data publics. Targeted outputs will provide actionable recommendations, reshape policy conversations, and promote innovative, inclusive approaches to data governance, benefiting academia, local governments, and third sectors.