University of St Andrews

UKRI Gateway to Research · FY 2026 · 2026-09

Solar systems, including our own, form from the collapse of clouds of dust and gas which has been processed by previous generations of stars. This collapsing cloud, the ‘early Solar System’, set the stage for the subsequent formation and evolution of the collection of planets and asteroids we know today. We can examine the sources and processes of the early Solar System, e.g. inner Solar System volatile delivery, by looking at variations in the isotope compositions between different meteorites. These variations result from incomplete mixing of material from different stellar sources. Stars produce elements, and their isotopes, in dramatically different abundances and release them during their last stages of evolution (e.g. supernovae). Meteorites formed in the early Solar System and sampled these different pre-solar signatures to varying degrees. Therefore, by measuring the isotopic compositions of materials from the early Solar System we can trace the mixing of material during the collapse of the cloud of dust and gas.   Over the past 20 years the isotopic variations of a wide range of elements have been measured in meteorites. This has painted a picture of characteristic isotope compositions for the inner and outer Solar System. Using these isotopic variations, the origins of meteorites can be classified and their relationships examined. However, despite the apparent systematic patterns in these isotopic variations their origin remains uncertain. Recently, several models have been proposed to explain how these variations were produced.  In one family of models, the systematic differences between the inner and outer Solar System were inherited from stratification in the parent molecular cloud. In another set of models, the different stellar sources were progressively unmixed (e.g. by thermal processes) from a previously physically homogeneous parent molecular cloud. These two models predict similar isotopic variations through the resulting Solar System but achieve this through fundamentally different mechanisms. Knowledge of the mechanism of isotopic evolution of the early Solar System is vital for our understanding of early Solar System processes and to be able to place our own Solar System in context with other exoplanetary systems.   The proposed work will test the different models of isotopic evolution in the early Solar System by examining chondrules – melt droplets which formed in space during the first few million years of the early Solar System. Chondrules make up 20-80 % of most chondrites, the sedimentary space rocks which survived the major planet forming events. We shall measure the ages and isotope compositions of chondrules to examine the variation of isotope compositions through time. If the variation in isotope composition in the early Solar System was inherited from a stratified parent molecular cloud, we would expected larger variations to be sampled by chondrules which formed earlier, and this variation should decrease in later chondrules as material mixes. However, if the Solar System formed from a homogenous molecular cloud which progressively unmixed, the isotope compositions of chondrules through time would diverge in different regions from a common starting composition. Using chondrules as snapshot samples of the isotopic variability through the first few million years after the Sun formed, we can test the mechanism of the isotopic evolution of the early Solar System. This will allow greater understanding of the formation of solar systems and the processes which are required to form systems like ours with habitable planets.

UKRI Gateway to Research · FY 2026 · 2026-09

Within LCDM the formation and evolution of galaxies is intrinsically linked to the distribution of matter in the Universe. On scales smaller than ~1Mpc, this link is often understood as the connection between a galaxy and its host dark matter halo (the “galaxy-halo connection”) and understanding it has become a fundamental driver of galaxy evolution and observational cosmology studies over the last decade. Nonetheless, it is increasingly clear that the full matter density distribution is necessary to fully predict the growth and properties of halos and galaxies. The cosmic web – the classification of the matter density field into nodes, filaments, walls and voids – is an effective way to capture missing information, as it naturally encodes the multi-scale and anisotropic nature of the full matter density field. The impact of the cosmic web on the growth of dark matter halos is well understood from simulations, but the impact of halo growth on galaxies is not, with important and outstanding tensions between different simulations and observations. This leaves us in a difficult position - without a full understanding of how galaxies form and with uncertainty on how to link galaxy and halo growth. This project will advance the field through a comprehensive study of the impact of large-scale structure on halos and galaxies using the largest redshift survey available of the nearby universe: the complete Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS). Using a combination of new observations, existing simulations, and new modelling, we will answer the following three key questions: What is the impact of large-scale structure on the assembly of dark matter halos? On what timescales does structure formation affect the evolution of galaxies? In what ways, and by which mechanism(s), does the large-scale environment impact the evolution of galaxies?

UKRI Gateway to Research · FY 2026 · 2026-07

The vision of my FLF renewal is to develop efficient processes catalysed by organometallic complexes for creating renewable, recyclable polymers via dehydrogenation and hydrogenation chemistry, while demonstrating their applications in batteries and CO2 capture. This builds on my lab’s outputs from the first phase of my FLF, particularly the dehydrogenative and hydrogen borrowing polymerisation approaches, which enable the syntheses of renewable polymers like polyureas, polyethylenimines, and polyesterethers from bio-based feedstocks. Furthermore, some of these polymers can be depolymerised back to monomers using hydrogenation, supporting circular economy principles. These processes are catalysed by well-defined organometallic complexes, in particular pincer catalysts. Although the outputs from the first phase of FLF are exciting, commercial viability faces two main challenges: low catalyst turnover numbers (TON <500) that make the processes expensive and the need of market or applications of these new polymers. The next phase of my FLF will tackle these challenges by (1) developing new organometallic catalysts and processes to achieve higher turnover numbers (in collaboration with Prof. Michael Buehl), (2) creating polyetherurea-based waterborne binders for batteries to replace toxic PVDF binders in batteries (in collaboration with Dr. Rob Armstrong, University of St. Andrews), and (3) advancing polyethylenimines for CO2 capture (in collaboration with Prof. Paul Wright, University of St. Andrews). This work will drive the transition from lab-scale breakthroughs to commercially viable, sustainable polymer technologies.

UKRI Gateway to Research · FY 2026 · 2026-03

Data controllers working with ADR UK to provide access to their data for public benefit research have varied risk appetites.  This means that there are differences in where they will allow a Researcher to access their data from and how it is to be accessed.  While some data controllers demand strict controls over access locations, others are happy with this happening from offices or a person’s home.  However, all insist on having secure and audited networks to this point of access. This has meant many UK Researchers struggle to access some types of data from their workplaces.  Their institutions are unable to resource the significant financial overheads involved, the space needed, and the continuing security assurances required by data controllers.  The only other solution has meant that Researchers having to travel the often-large distance to acceptable points of access or not undertake the research. The role of the SafePod Network (SPN) is to remove these barriers and solve this problem with flexible, dynamic and cost-effective data access solutions, ensuring that ADR UK can support access to all types of administrative data, to all Researchers irrespective of where their place of work is in the UK. Since the SafePod Network (SPN) launched in October 2021, it has transformed the landscape for secure data access solutions and locations.  Prior to launch, there were only a few main locations in the UK which offered access to a limited set of data.  The SPN has since established a network of 24 SafePods (which are small, standardised and prefabricated safe settings) in operation at universities across the UK.  SafePods provide approved Researchers with secure access to multiple different Data Centre’s data.  This includes data from the Office for National Statistics, UK Data Service, SAIL Databank and the Scottish Government.  In the next investment period, the SPN will launch SafePack, the most flexible and cost-effective secure data access solution.  SafePack will make it possible for individual Researchers to afford their own low cost highly secure point of access, sitting in their workplace and perhaps their home. This means, at no new cost to the ESRC, the SPN will be able significantly scale up the number of highly secure points of data access as Researchers will be able to justify this cost to their institutions or funders. The SPN has achieved the critical success factors, as set out in the 2022-2026 case for support.  These were: To be recognised and trusted across the UK as the main provider of safe settings for secure data access for research. To maintain security for SafePods and supporting services.  To implement agreements with Data Centres for access to their data through the SPN. To help improve the quantity and diversity of public benefit research. To continue to innovate to provide secure data access solutions for research. Furthermore, the new SafePoint and SafePack developments will build on the success of the SafePod Network to provide scalable, standardised secure data access services for use from Researchers institutions, offices and home.  This will effectively enable any approved Researcher in the UK to have a secure data access solution for their research, and help meet ADR UK’s long term objectives to facilitate better access to administrative data across the UK, and support the demand for existing and newly created flagship datasets.

UKRI Gateway to Research · FY 2026 · 2026-03

The BOSOMTWE project is a UK-Ghana collaboration that aims to build scientific capacity in Ghana by developing and deploying advanced but affordable optical imaging and spectroscopy tools. The project is centred at the Ghana Photonics and Optics Laboratory (GPOL) at Kwame Nkrumah University of Science and Technology (KNUST), and brings together a multidisciplinary team of researchers from Ghana and the UK with expertise in photonics, biomedical imaging, spectroscopy, and public health. In many low-resource settings, researchers face significant barriers to accessing high-end scientific equipment and training. This limits their ability to investigate local health, environmental, and technological challenges using modern scientific methods. Ghana has a growing community of talented scientists and students, but limited access to advanced imaging and diagnostic tools. BOSOMTWE addresses this gap by delivering low-cost, high-performance optical systems and the training needed to use and maintain them effectively, enabling researchers to conduct world-class science in their own institutions. The project is structured around three main areas of work. First, it will deliver a compact, bench-top super-resolution microscope capable of imaging biological structures at the nanoscale. This system is designed to be robust, affordable, and easy to use, making it ideal for laboratories without access to expensive infrastructure. Second, the project will develop a portable Raman spectrometer that can be used in the field to analyse complex samples such as traditional medicines, pharmaceuticals, and food products. This tool will support research into public health and food safety. Third, the project includes a strong training component. This includes hands-on workshops in the UK and Ghana for technical knowledge of advanced biophotonics techniques, as well as the establishment of the first laser safety policies and training programmes for the region. Training will be delivered to students, technicians, and researchers, with a focus on sustainability, local leadership and impacting a broad African research community. By combining technical innovation with training and collaboration, BOSOMTWE will create a lasting research infrastructure that empowers local scientists to address challenges that matter most to their communities. The project has the potential to impact a wide range of sectors, including healthcare, agriculture, food safety, and education. It will also strengthen international partnerships and contribute to a more equitable global research landscape by ensuring that cutting-edge science is accessible and relevant to researchers in low-resource settings. Through BOSOMTWE, Ghanaian researchers will be better equipped to lead scientific discovery, contribute to global knowledge, and drive innovation that benefits society.

UKRI Gateway to Research · FY 2026 · 2026-03

Organic light-emitting diodes (OLEDs) are a remarkable light-emitting and display technology, found throughout our lives in smartphones, watches, fitness monitors and some televisions.  The purpose of this proposal is to explore their use for high speed optical communication.  This would enable display to display communication and light sources to send information to smart devices.   OLEDs are attractive for this emerging field of “LiFi” because they are simple to make, can emit a range of colours, are already present in many displays, and can readily be integrated into everyday objects.  Optical communication is fast and secure, and can complement existing mobile communications and Wi-Fi which use radio waves, particularly within rooms. We will adjust the design of OLEDs to enhance their emission rate, and so enable them to send data faster.   We will then develop red, green and blue OLEDs side by side and use each colour to send a data stream – enabling data to be transmitted approximately three times faster than for a single colour OLED, with the aim of setting a world record data rate for OLED data transmission of 30 gigabits per second (over a distance of 1 metre), ten times faster than the current record.  This will be achieved by a combination of advances in OLED design, and improvements in how data is encoded to be sent by OLEDs.  In addition we will make larger arrays of OLEDs so as to be able to send information in multiple directions. The research is important because of the ever-growing need for data communication as more and more devices are connected to the internet.   We will demonstrate the potential of OLEDs for optical communication and provide proof of principle for subsequent use of displays for communications.  Our work will expand the range of uses of OLEDs, provide a new platform for LiFi and set a new world record for OLED based data rates.  

UKRI Gateway to Research · FY 2026 · 2026-03

The integration of Darwinian evolution and Mendelian genetics in the early 20th century provided the conceptual bases for the study of how specific genetic differences, known as genotypes, are linked to observable traits or characteristics, known as phenotypes. However, advances in our understanding of this relationship were limited by genotyping techniques that could only examine a small subset of known genetic markers. The emergence of next generation sequencing in the early 2000's led to so-called genome-wide studies focused on identifying individual variants associated with specific phenotypes. Such studies helped identify several variants associated with important phenotypic traits in plant and animal  breeds. It also uncovered many variants linked to disease in humans.  However much of the variation underlying these traits remains unexplained. Moreover, the increase in size of genomic datasets and complexity of traits being studied represent important challenges to the statistical frameworks in use. It is now clear that complex phenotypic traits may be determined not only by many genes of small effect but also by so-called epistatic interactions among them. Some progress has been made in detecting interactions among a small number of variants but the role of high-order epistatic interactions still needs to be addressed. Thus, the challenge today is to develop new methods of analysis that can scale up to modern population genomics databases and uncover interactions between many genetic variants. Our project addresses these challenges by harnessing the power of deep learning (DL) methods and complex network analysis (CNA) to develop an end-to-end computational tool to associate causal genetic variants to a phenotype of interest and also detect underlying epistatic interactions. Our approach will go beyond pairwise gene-to-gene interactions and study higher-order interactions. We will implement DL models that scale up to high-dimensional input and learn complex nonlinear interaction patterns, which can then be unveiled using the latest advances in explainable and interpretable machine learning approaches. Once important variants and potential low dimensional interactions are identified, CNA techniques will allow us to explore higher-order interactions using an enormous range of new analysis methods that are unavailable in lower-order settings. Our approach will help identify essential genes (as network hubs), gene clusters with similar functionalities, and genes with suppressing and augmenting effects for a specific phenotype. Our proposed framework can reveal how genes drive biological functions and contribute to diversity, health, and disease and will be applicable in a wide range of domains. In evolutionary biology, it will provide new insights into how certain traits evolved and adapted in response to environmental pressures. This new knowledge is crucial for the design of efficient animal and plant breeding programs aimed at increasing disease resistance and adaptation to global change; as well as for conservation efforts and for predicting how populations may respond to changing environments. It will also help to uncover the genetic basis of complex human diseases, which may lead to new diagnostic tools, personalised medicine, and targeted therapies. We aim to develop proof-of-concept and identify the right techniques. This, in turn, will allow us in the near future to develop an open-sourced library for geneticists and evolutionary biologists interested in understanding the genetic architecture of complex traits, which will facilitate new genetic discoveries.

UKRI Gateway to Research · FY 2025 · 2025-12

Control of non-equilibrium phases of matter promises stabilisation of new and unconventional ground states as well as new routes for new and ultra-fast functionality for new device concepts. Experimental studies of non-equilibrium states of matter are challenging due to the short lifetime of the ground states, and the technical difficulties in implementing efficient pumping without simply heating the sample. Imaging and local spectroscopy of non-equilibrium states has remained difficult and often resulted in inconclusive results. This proposal aims to lay the foundations for building such an instrument, by given the project lead the opportunity to explore the approaches that have been pursued so far through a number of visits and to learn from the cases where pump-probe spectroscopy combined with local measurements has been achieved, to then build a pump-probe scanning probe microscope that can image electrons in non-equilibrium phases. This builds on a strong track record of the applicant in developing instrumentation for studying the electronic states in quantum materials through quasi-particle imaging, and operating a suite of such instruments.

UKRI Gateway to Research · FY 2025 · 2025-12

The innovations of videographic criticism have the potential to expand the field of digital humanities and to create new opportunities and structures for how research is made, published and accessed. At a critical moment when videographic scholarship is becoming an established practice within film, television and screen studies, how can we preserve and expand this innovative and radical potential to avoid recapitulating entrenched academic models and hierarchies? In answer to this central question, ‘Ways of Undoing’ turns to systems of knowledge and modes of making that have been overlooked and marginalised in filmic and academic environments. Filmmaking is one of many creative practices that have followed the hierarchical formation in which ‘art’ is understood as of greater value than ‘craft’ and whereby the achievements of the few (directors, actors, screenwriters) are privileged over the contributions of the many (such as costume, hair, make-up, and sound designers). The video essay has likewise been conceptualised as a singular intellectual and creative endeavour in which the scholar-maker has been prioritised over collaborative possibilities. And yet, it is the very form of the video essay itself, with its many layers of process and production, that presents the possibilities of collective research. In recognising that the videographic essay shares the medium of its subject - moving images and sounds - the proposed project is designed as an intervention in which the focus of videographic scholarship is redirected to methodologies that prioritise craft, community, and collaboration. Most pressingly, the project seeks to recognise the value of collaboration and practice-as-process in order to develop new forms and practices of research, posing the question: How can collaborative craft practices intervene in institutionalised hierarchies which govern both filmmaking and academia? The proposed project thus has two main aims: 1) to counter the widely established lack of recognition for the creativity and collaborative labour of design craft in cinema; and 2) to create sustainable models of research, community and circulation which prioritise methods emphasising process and embodied thinking, and which generate knowledge through collective action. In order to undo persistent hierarchical power structures prioritising art over craft that are prevalent in filmmaking and videographic criticism, ‘Ways of Undoing’ is designed to create ways to produce, circulate, and teach collective research that counters the devaluing of craft practices, recognising their significance as material and embodied ways of knowing. These pursuits will result in the following outputs: An open-access peer-reviewed videographic monograph, which invents aesthetic and conceptual strategies to embody the material practices that are its subject; Three week-long in-residence workshops which develop community practice and collaboration with local partners in Scotland, Canada and Japan, through practice-based methodologies drawing on material thinking and process-driven craft techniques and traditions; One peer-reviewed special issue of [in]Transition: Journal of Videographic Film & Moving Image Studies edited by participants under the mentorship of the project team; Nine videographic exercises published open-access online and translated into four languages (Spanish, Japanese, Mandarin, and Arabic) to encourage global use;  Physical and online curations exhibiting work produced at the workshops, including a guaranteed curated screening at the Locarno Film Festival in 2028; Three episodes for The Video Essay Podcast.

UKRI Gateway to Research · FY 2025 · 2025-12

Sleep and gambling are important issues affecting the lives of young people. During adolescence and young adulthood, sleep patterns change as body clocks shift, responsibilities increase, and screen use becomes more common. These are also the years when many first encounter gambling, including lotteries, scratch cards, esports betting, online casino-style games, and in-game gambling such as loot boxes and other chance-based purchases. Although sleep problems and gambling behaviours often appear at the same stage of life, no previous review has examined the relationship over time or explored whether one may contribute to the development of the other. This project addresses that gap by focusing specifically on longitudinal and potentially causal pathways. Poor sleep affects judgement, emotional control, and impulsivity, creating conditions that may increase the likelihood of engaging in risky behaviours, including gambling. Digital gambling forms, which are accessible at any hour, may disrupt sleep further by encouraging late-night involvement or generating stress and financial strain. Understanding which occurs first, and whether one behaviour increases vulnerability to the other, is crucial. If sleep difficulties arise earlier in adolescence and contribute to gambling initiation or harms in young adulthood, this suggests a possible causal route. If gambling disrupts sleep, this may reinforce harmful cycles that intensify over time. Clarifying these sequences is essential for practical prevention efforts. Both sleep and gambling harms are shaped by inequality. Young people from deprived backgrounds, those with care experience, neurodivergent young people, and those living in rural areas face higher risks of sleep problems and gambling-related harms. The review will therefore examine whether the relationship between sleep and gambling differs for groups who already experience significant disadvantage. This will help identify where early support may be most effective. The SAGE project will bring together evidence on how sleep and gambling are associated across ages 10 to 24, with particular focus on studies that track young people over time. It will examine whether poor sleep predicts later gambling, whether gambling affects subsequent sleep, or whether both develop together in a bidirectional cycle. It will also assess whether studies account for factors such as deprivation, gender, neurodivergence, and care experience, which can shape both sleep health and gambling vulnerability. This work will be carried out through a systematic review following PRISMA 2020 guidelines. Evidence will be sourced from scientific databases, grey literature, policy reports, and materials relevant to digital and youth gambling. Studies will be screened using clear criteria, with priority placed on longitudinal designs, repeated measures, and research that allows assessment of timing or direction of associations. Where possible, statistical techniques will be used to summarise the strength and direction of these relationships. The findings will directly support prevention, public health planning, and clinical practice. If poor sleep is identified as an early-life risk factor, this would support school-based sleep education, healthier start times, and targeted interventions for vulnerable young people. If gambling is shown to harm sleep, gambling support services could integrate sleep screening and structured guidance. Policymakers will gain clearer insight into where investment in sleep health may reduce gambling harms across the population. The review will produce a technical report, policy brief, evidence map, and a plain-English summary co-designed with young people and caregivers. All outputs will be openly accessible and designed to support decision-making across research, policy, education, regulation, and healthcare.

UKRI Gateway to Research · FY 2025 · 2025-12

Context: Many bacterial pathogens have become resistant to multiple antibiotics, making infections increasingly difficult to treat. This raises serious concerns that routine surgeries, cancer treatments, and organ transplants could again become high-risk due to untreatable bacterial infections. Bacteria can share instructions for antimicrobial resistance (AMR) through a process called horizontal gene transfer (HGT). This is often facilitated by mobile genetic elements (MGEs), such as bacteriophages (phages) - viruses that infect bacteria - and a related group known as phage-inducible chromosomal islands (PICIs). PICIs act as molecular parasites, hijacking phage machinery to spread their own DNA. These elements, often found together in Staphylococcus aureus and other bacteria, are known to facilitate the transfer of AMR genes, toxins, and immune evasion factors, contributing to the spread of disease. Challenge: Although MGEs are individually well studied, how they interact with each other is still poorly understood. Yet, these interactions may profoundly influence the evolution, virulence, and resistance capabilities of bacterial pathogens. A newly discovered interaction - whereby PICIs actively induce prophages - could be a key mechanism driving the spread of AMR and virulence traits. Aims and Objectives: This research will investigate how this newly identified PICI–phage interaction affects bacterial evolution, gene transfer, and disease potential. The project will pursue three major aims: Characterise the molecular basis and conservation of PICI-mediated prophage induction: How do PICIs trigger prophage activation, and how widespread is this mechanism? Define the impact on HGT and bacterial evolution: How does this interaction influence the mobilisation of DNA and the spread of AMR? Determine the impact on virulence and pathogenicity: How do PICI-phage interactions shape the expression of virulence genes and the ability of bacteria to damage host cells? Staphylococcus aureus is used as the model organism because it is genetically tractable, clinically relevant, and a major contributor to AMR infections globally. Potential Applications and Benefits: The project will improve our understanding of fundamental bacterial biology, offering insights applicable to clinical, industrial, and environmental microbiology. It will provide high-level training in advanced molecular microbiology techniques, transcriptomics, and host–pathogen interaction models. While this is a discovery-driven project, the findings could help shape future strategies to limit the spread of AMR. For example, interfering with MGE interactions could prevent bacteria from acquiring resistance or becoming more virulent. In the long term, this could inform the development of new anti-virulence therapies, phage-based treatments, or targeted antimicrobials that disarm bacteria without promoting resistance. This research is strongly aligned with the MRC’s strategic priorities in AMR, infection biology, and bacterial evolution.

UKRI Gateway to Research · FY 2025 · 2025-12

With the growing success of AI in modern society, exponential energy consumption and the limitations of classical computing are becoming serious challenges. To keep up with this growing global demand requires revolutionary new approaches beyond conventional Silicon-based technologies. One of the most promising routes here is to utilise correlated quantum materials. These materials exhibit strong electron-electron interactions that give rise to remarkable low-energy phenomena, such as high-temperature superconductivity and unconventional magnetism, which offer immense potential not only for energy-efficient technology, but also for advancements in frictionless transportation, industrial magnets, spintronic devices, and next-generation quantum computers. However, as it stands, most correlated quantum materials only exhibit these technologically relevant properties at extremely low temperatures, or in equally impractical conditions, and we usually lack insight into how to optimize these properties for specific applications. While dramatically improving the practical application of correlated quantum materials is in principle possible, our lack of theoretical understanding of the complex interactions has held back progress in real-life material development. Theoretical methods to describe the fundamental interactions and predict the properties of correlated materials have been developed, using a technique known as functional renormalisation group theory (FRG), yet for decades they have been so computationally demanding that they have only been applicable to the simplest of toy systems, limiting their utility for understanding real materials. A recent breakthrough in FRG theory in 2022 however has broken through this computational complexity barrier, unlocking the modelling of systems with realistic and complex electronic structures. This has enabled a route to combine our advanced fundamental understanding of the underpinning theories with material specificity to allow for a direct comparison with experimental data and to understand how electron correlations influences materials that host multiple atomic, orbital and spin degrees of freedom. The aim of this fellowship is to harness this new material specificity within FRG and apply it to a wide range of known correlated material systems using realistic materials parameters as input. From this large-scale analysis, I will be able to theoretically identify, and experimentally verify, the key chemical and structural handles required to enhance and control quantum interactions in real materials, leading to the development of new correlated electron materials with enhanced properties, such as superconductors with higher transition temperatures. The objectives of this project will be achieved through a uniquely transformative, high-throughput approach to correlated quantum material research, identifying routes to maximise the correlated ground state transition temperatures of quantum materials. Through the process, I will develop an open-access database consisting of open-source correlated quantum material models and simulations, leading to a standardisation of correlated quantum materials computations and enabling myself, and other scientists, to design next-generation correlated quantum materials with record-breaking properties. This research will act as a bridge connecting theoretical predictions to practical application and pave the way for a new era of designer correlated quantum technologies.

UKRI Gateway to Research · FY 2025 · 2025-11

Context Language is at the core of what makes us human, underpinning our unbounded capacity to exchange thoughts, ideas, and culture. Speech and language rely on complex biological mechanisms shaped by evolution. Studying the biology and evolution of the capacity for language poses unique challenges. Invasive experimentation in humans is unethical, and the lack of fossil evidence for language limits evolutionary insights. For these reasons, despite its importance, the biological basis and evolutionary origins of speech and language remain poorly understood. While no other animal has a full language system, some animals display ‘language-relevant traits’. A key language-relevant trait is vocal learning - the ability to imitate and modify sounds. A comparative approach, exploring vocal learning in animal systems, provides invaluable opportunities to gain insights into biology and evolution of language. However, few tractable animal models for language-relevant traits exist, and those that have dominated the field are either evolutionarily distant from humans, such as birds, or are impractical for experimentation, like whales and seals. This highlights the need for a tractable mammalian model to investigate the genetic and neurobiological foundations of vocal learning. Addressing The Challenge Bats offer an unparalleled opportunity to address these challenges. Bats are small, social mammals that demonstrate robust vocal learning abilities. They are experimentally tractable and can be bred and housed in laboratory facilities. Bats also provide a much closer evolutionary comparison than the dominant model species, birds, which are separated from humans by over 300 million years of evolution. Despite their potential, prior research into bat vocal learning, particularly regarding the genetic and neurobiological mechanisms involved has been limited. Aims and Objectives This project consolidates bats, specifically the pale spear-nosed bat (Phyllostomus discolor), as a groundbreaking mammalian model for vocal learning. The primary aims are to investigate the molecular and neural encoding of vocal learning, and to provide insights into the evolutionary pathways that enable this trait. Key objectives include: Developing genomic and molecular tools in bats. Identifying genes and neural pathways associated with vocal learning. Establishing causative links between genes, brains, and vocal behaviour using transgenic bats. Expanding research on bats to explore new applications and build interdisciplinary networks to exploit this emerging model. Potential Applications and Benefits This research seeks to unravel fundamental biological principles underlying vocal learning, shedding light on how complex behaviours like speech evolved and are encoded in mammals. By comparing bats to other vocal learners, the project aims to uncover convergent and divergent evolutionary mechanisms, offering a deeper understanding of vocal learning across species. This work will also reveal how specific molecular and neural systems interact to enable complex vocal behaviours. The findings may have far-reaching implications for understanding how communication systems evolve and function, providing a broader context for studying the origins of human speech and language. These findings may also provide insight into human language-related disorders which affect >11% of the population. This research provides a unique opportunity to investigate a currently understudied area that represents a major and urgent scientific challenge. By solidifying bats as a key model system, this project opens new avenues for research into neurogenetics, behaviour, and evolution. The integration of diverse disciplines positions bats at the forefront of vocal learning studies and contributes to our understanding of this rare and complex trait.

UKRI Gateway to Research · FY 2025 · 2025-10

Characterising and quantifying random and deterministic behaviours in data, which can be as diverse as rainfall data or the distribution of prime numbers, is a fundamentally important topic.  This proposal is based in Ergodic Theory and Dynamical Systems, but motivated by these problems as well as questions around quantifying energy spectra, questions in sequences seen in Number Theory, and by matching sequences of symbols in DNA.  Such quantifications can be understood in terms of the average long-term random-type signatures in the data, along with possible rigid clustering behaviour (for example a day of heavy rainfall is more likely if the previous day had heavy rainfall, so we would expect clustering here alongside more random phenomena). In this proposal we focus on the sizes of gaps between data points, which can generally be called gap statistics.  We will use state-of-the-art mathematical tools, and to develop new ones, to more fully understand gap statistics, capturing the locations and structure of clusters of gaps of a given type (large, medium or small) for the first time.  In problems in energy spectra and number theory the gaps in the data has been previously looked at on the average scale, while in the setting of sequences of symbols (which has applications for DNA), where the size of gaps correspond to how similar two sequences are to each other, gap statistics has previously been looked at on the extreme scale (long strings of symbols matching each other).  The location of these gaps and their clustering has not been considered previously. Recently tools from probability, used in a dynamical systems context have become better suited to capturing both of these scales in a random measure, a tool which can incorporate detailed asymptotic behaviour if convergence can be proved, i.e., taking the number of data points to be larger and larger and rescaling the expected average or extreme gap accordingly and seeing if there is a limiting measure.  Proving such convergence and fully characterising these measures will be a significant challenge, but developments in both the dynamical and number theoretic setting mean that now is the time to create and benefit from synergies in theories across these different areas of mathematics and lay the groundwork for a significant multifaceted research programme.

UKRI Gateway to Research · FY 2025 · 2025-09

There are few challenges with more pressing urgency than climate change, land and ecosystem degradation, and biodiversity loss. The need to formalise practices for improving nature amidst essential land management activities for housing, infrastructure, and food, now dominates the global discourse on restoring the planet’s terrestrial and marine habitats (collectively: “net gain”). We are entering a time of unprecedented public and private investment in climate and nature-related restoration activities, driven by the integration of the net gain concept into local, national, and international targets and emerging nature markets. Yet, the science and practice of net gain and nature markets remain underdeveloped, lacking a robust evidence base and theoretical framework to ensure these sweeping changes in land use management truly secure nature-positive and climate-positive outcomes in a socially equitable way. Addressing this urgent challenge requires bridging knowledge gaps across scientific disciplines, industry, and government sectors. There is, therefore, an acute need for training that produces a new type of net gain scientist-practitioner, one who can seamlessly navigate and integrate these diverse fields to effectively drive and deliver progress. NETGAIN will directly address this challenge. We have assembled a far-reaching network of academic and non-academic partners invested in supporting the initiative through evidence-driven training and research, and propose a novel and innovative doctoral training programme co-developed with this network of partners. This programme will serve as a template to equip future scientist-practitioners with the translational skills and experience necessary to develop scientifically rigorous, trusted, sustainable, and fit-for-purpose nature markets that contribute to reversing biodiversity loss in the UK, and globally. Using proposed NERC and University funding as a seedcorn, NETGAIN aims to become a self-sustaining programme positioning the UK as a leader in ecologically, economically, and socially effective nature markets. Our vision is of an inclusive, equality-driven, and collaborative doctoral training programme that integrates diverse disciplinary and sectoral perspectives to directly address critical training needs and knowledge gaps associated with the design and implementation of nature markets and delivering biodiversity net gain more broadly. We will achieve this through a multidisciplinary culture of co-creation. Our unique training programme, supported by four HEIs and 36 external partners and which has generated close to £3M in financial support (>100% matched funding), will address critical skills gaps across quantitative eco/geosciences, socioeconomic disciplines, regulators, and industry.  This initiative will prevent disciplinary siloing and establish a robust evidence base for nature markets, ensuring students emerge as multidisciplinary leaders. Our pioneering training programme, spanning a wide range of net gain-related topics, will expose collegiate cohorts of students (and supervisors, and partners) to cross-sector training delivered through three core modes: the NETGAIN Student Development Programme (SDP, monthly ‘little-and-often’ learning), a community-building annual conference including Skills Development Masterclasses (SDMs), and support for bespoke Individual Training Programme (ITP, continuous and self-paced). At the heart of this programme is the NETGAIN open-access e-book, with contributions from leading experts and student case studies that will adaptively define net gain theory and practice, providing a standard-defining resource for ongoing learning and progress tracking. Cultivating a new generation of multidisciplinary scientist-practitioners, NETGAIN will transform the landscape of nature markets, ensuring effective, evidence-based solutions to the world's most urgent environmental challenges.

UKRI Gateway to Research · FY 2025 · 2025-09

"Histories of Hope?" is a 26-month project (July 2025-September 2027) that brings together researchers from the University of St Andrews alongside public historians and heritage staff at the Camp Nelson National Monument, a major site of African American Civil War history in Nicholasville, Kentucky. Our aim is to co-develop an innovative, community-engaged museum exhibit that will inspire visitors to think critically and creatively about processes of commemoration and better understand Camp Nelson’s role in contemporary and historical Black freedom struggles. Originally established as a supply depot for the Union Army, Camp Nelson became the country's third largest recruitment centre for African American troops (USCT). It also became a critical destination for refugees as hundreds of Black women and children travelled to the site in pursuit of their freedom but were violently cast out. Designated a National Monument in 2018 and managed by the U.S. National Park Service (NPS), the former encampment is now a place of commemorative activity, interpretation, and education. It is a non-traditional monument to freedom, contrasting starkly with the Confederate monuments erected during Reconstruction and beyond in Kentucky, which currently dominate debates surrounding commemoration, racism, and the Civil War. Against this backdrop, this project chooses to emphasize collaboration and co-creation while confronting the challenges of who should tell Camp Nelson’s story and define its modern-day legacy. Using traditionally overlooked databases, primary and secondary resources, and archaeological research, our goals are to uncover previously untold stories of Camp Nelson and seek creative and effective ways to share them with the broadest possible audience. Through community engagement efforts, we aim to center the voices of those who have been historically marginalised in interpretations and establish Camp Nelson as a model for inclusive and equitable design. The project will have a direct influence on the current rehabilitation of the Camp Nelson Museum and advance the mission of Commemorative Cultures, a digital humanities project led by Treen at St Andrews that seeks to map and interpret Civil War monuments from around the world. The NPS are working on the redevelopment of on-site exhibits and the creation of digital content to make the stories and relevance of Camp Nelson more accessible to physical and virtual visitors to the park. This project will provide the research for this work as well as creating significant professional opportunities for early career researchers and a convenor in project management, museum studies and the public humanities. Working in conjunction with Camp Nelson staff and NPS contractors, the project will lead a comprehensive re-evaluation of the site's commemorative and interpretative legacy, ensuring the integration of previously neglected perspectives. This will significantly contribute to the academic discourse surrounding Civil War heritage, commemoration, and curatorial best practice. Further, by enhancing the museum’s interpretive strategies, the project will establish Camp Nelson as a critical case study for inclusive engagement with the potential to inform heritage policy and curatorial practices within the NPS and other heritage organizations more widely, thus addressing the need for more inclusive and representative narratives in public history.

UKRI Gateway to Research · FY 2025 · 2025-09

Developing more energy-efficient technologies is a key component of sustainable economic growth. Superconductors can make a key contribution to such technologies, however their ground state is typically only reached at very low temperatures. Only one group of materials, the cuprate high-temperature superconductors, so far exhibits superconductivity at temperatures above the boiling point of liquid nitrogen and at ambient pressure, which has made it challenging to develop a universal understanding of the pairing mechanism in these materials. Recently, superconductivity at similarly high temperatures has been reported in a second class of transition metal oxides, the lanthanum nickelates, albeit so far only under pressure. Discovery of a second class of transition metal oxides that exhibits high temperature superconductivity promises new opportunities to establish an understanding of the pairing mechanism in these materials and vastly better possibilities their properties in applications. The lanthanum nickelates are structurally very similar to the cuprates: they are both perovskite oxides, and superconductivity is observed in layered compounds of the Ruddlesden-Popper (RP) series – suggesting that similar physics might be at play. The primary objective of this research proposal is to systematically investigate the ground states of RP type phases derived from lanthanum nickelates in a quest to stabilise the superconductivity at ambient pressure as well as establish their correlated phases and understand their origin. To be able to harvest this potential high temperature superconductivity, but also improve our understanding of and ability to design correlated phases in transition metal oxides, we propose here an approach that combines thin film growth with characterisation by spectroscopies and electronic transport and ab-initio modelling to identify the key physics, enable identification of the superconducting phase, and unravel the mystery of high-temperature superconductivity in lanthanum nickelates. To achieve this objective, we will Use advanced spectroscopic methods to understand the electronic structure and correlated phases of single crystals of lanthanum nickelates Establish growth of electronic designer metamaterials, consisting of layered structures of different members of the Ruddlesden-Popper series of the lanthanum nickelates Employ a range of methods to identify the superconducting phase and stabilise it in thin films at ambient pressure

UKRI Gateway to Research · FY 2025 · 2025-09

The advent of multicellularity was a critical evolutionary step that occurred several times independently, leading to the evolution of animals, plants, fungi, and some algae. The ability of cells to discriminate ‘self’ from ‘non-self’ (and, particularly, the ability to detect ‘self’ from conspecific ‘non-self’ - allorecognition) is thought to have been fundamental for this evolution, ensuring genetic stability by preventing the formation of chimeras. Self/non-self recognition is also important for embryonic development, wound-healing, and immune responses, and is therefore thought to be an essential property of multicellular organisms. Our proposed project stems from observations by our team and others that, surprisingly, capacity for allorecognition may be limited in bivalve molluscs. For example, cultured pearl formation involves tissue grafts between two individuals of the same species, and we regularly observe graft success rates that exceed 90%. Another line of evidence for poor allorecognition in bivalves is the recent discovery of eight distinct transmissible neoplasia (cancer) lineages in a range of bivalve species. Transmissible cancers are incredibly rare; besides bivalves, detection has been limited to two cancer lineages within Tasmanian devils, and one in canines. In both these vertebrate systems the cancers have been linked to a dampened allorecognition system, suggesting a link between suppression of allorecognition and evolution of transmissible cancer. We hypothesise that allorecognition is impaired in bivalve molluscs, and that this impairment may explain the repeated evolution of transmissible neoplasia in this group of animals. We aim to test this hypothesis by conducting nested experiments using tissues from the same individual, different individuals from the same species, and individuals of different species (using combinations of both closely and distantly-related species) to determine when tissue rejection occurs. These experiments will be conducted both in-vitro and in-vivo, and will be coupled with analysis of gene expression to identify the molecular components involved in self/non-self recognition. Finally, we will analyse the genomes of bivalve transmissible neoplasia cells to explore whether a lack of allorecognition may explain their repeated independent evolution. This study directly aligns with the BBSRC’s research priority ‘advancing the frontiers of bioscience: understanding the rules of life’. It aims to reveal the fundamental nature of the mechanisms for recognition of non-self in a major group of marine animals, providing a better understanding of bivalve immunity and potentially initiating a major re-evaluation of our understanding of the ubiquity of allorecognition in animals. Knowledge gained in this project will benefit bivalve aquaculture and restoration programmes, facilitating further research on the role of genetic diversity of populations in resilience to transmissible cancer outbreaks. The project will also reveal fundamental principles governing the evolution of transmissible cancers.

UKRI Gateway to Research · FY 2025 · 2025-08

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 · 2025-08

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

UKRI Gateway to Research · FY 2025 · 2025-08

Neurodegenerative diseases, such as Alzheimer’s and Parkinson’s, are closely connected with the buildup of amyloids—proteins that misfold and clump together into fibrils. Recent advances using cryo-electron microscopy (CryoEM) have provided detailed views of these amyloid fibrils, showing how different shapes of these proteins are linked to different disease outcomes. These findings highlight the importance of identifying amyloid fibrils with varying shapes to diagnose and treat neurodegenerative disorders effectively. However, while CryoEM has been invaluable in revealing the shapes of amyloids, it cannot examine fibrils within complex environments, such as human blood or cerebrospinal fluid. This limitation makes it difficult to turn these structural insights into practical diagnostic tools that can be used for early disease detection in clinical settings. My research aims to overcome this challenge by developing a new optical technique that can analyse the shape of individual amyloid fibrils directly from biofluids like blood or cerebrospinal fluid. This method will be designed to “fingerprint” the specific shapes of amyloids with high precision, without the need for complex sample preparation. By doing so, I aim to enable earlier and more accurate diagnosis of neurodegenerative diseases, building on the structural variations in amyloids that CryoEM has helped uncover. Beyond its use in neurodegenerative diseases, this approach could become a powerful tool in broader protein research. It could serve as an experimental counterpart to computational tools like AlphaFold, offering real-world structural data from biological samples on demand. In summary, my research will connect the dots between structural biology and clinical diagnostics, to understand and diagnose neurodegenerative diseases with unprecedented detail. This work aims to advance both scientific knowledge and practical applications, quickly contributing to better disease management and healthier aging.

UKRI Gateway to Research · FY 2025 · 2025-08

In a recent piece of work, PL and VR have developed a structure theory for filtered Boolean powers of finite simple non-abelian Malcev algebras and their automorphism groups. Boolean powers are certain kinds of subdirect powers, and play a significant role at the interface of algebra and model theory, as well as in infinite group theory. Malcev algebras are a broad class of algebraic structures, which includes groups, rings, associative algebras, Lie algebras, and loops. Thus they provide a convenient conceptual umbrella within which to prove powerful theorems which then specialise to each of these specific cases. The power of our theory has been demonstrated by showing that when the filtered Boolean power is taken over the countable atomless Boolean algebra, the automorphism group of the resulting structure has some strong desirable combinatorial/model-theoretic properties, namely the Bergman Property and the Small Index Property. In this project we want to deploy the theory further and investigate two even more advanced (and stronger) properties, namely the existence of ample generics and extreme amenability. In doing so, we will need to intertwine our work, with the theories linking these two properties with Fraisse and Ramsey theories (Kechris-Pestov-Todorcevic), as well as the projective Fraisse theory (Irwin-Solecki), and Kwiatkowska's result that the group of autohomemorphisms of the Cantor space has ample generics. A positive outcome in this project would yield new sources of examples of groups possessing these strong properties. These examples would have a hight degree of novelty, because they arise as automorphism groups of algebraic structures (including groups and rings), as opposed to relational structures or autohomeomorphisms of topological spaces, as is overwhelmingly the case in the existing literature. This would include automorphism groups of groups, rings and (classical) algebras. In this way, the proposed research would initiate novel interactions between different mathematical fields and exciting avenues for future research, creating a lasting impact.

UKRI Gateway to Research · FY 2025 · 2025-07

Buildings are the largest consumers of primary energy; consuming ~30% of it and also the building sector accounts for ~28% of total CO2 emissions globally. Recent studies have shown that by incorporating smart technologies such as the Internet of Things (IoT) into the buildings' energy system, energy savings of up to ~45 % are possible. IoT refers to a smart network of internet-connected everyday electrical and electronic devices which can communicate with each other and respond rapidly in real time. IoT-incorporated smart buildings have the promising potential to save our limited energy supply and reduce the waste of resources, money and time by continuously monitoring the different processes in buildings and optimising energy use. A smart building will utilise innumerable wireless sensors such as occupancy, humidity, temperature, proximity etc to monitor different processes and energy consumption. The latest market analysis (McKinsey & Company 2021) has shown that by 2030, the economic potential of IoT would range from $5.5 to 12.6 trillion and there would be more than 1 trillion connected devices. More than half of these devices and one-third of the economic value potential are expected to come from 'indoor' settings. How are we going to power these billions of connected devices? Connecting these sensor devices to the electrical grid is unfeasible as it requires extensive and complex installation and wiring, restructuring of the buildings, and limits the sensors' portable deployability across the buildings. The use of batteries is not sustainable as the limited lifespan of the batteries brings service interruptions during a battery replacement, increases maintenance costs, and poses severe environmental issues at their disposal. Moreover, once IoT has reached its projected wireless sensor nodes of one trillion, millions of battery replacements would be required per day which is unsustainable and impractical. My proposed research will bring a practical solution to this by developing inexpensive and environmentally friendly power sources by harvesting the freely available energy inside the buildings such as light from artificial light sources, heat energy and mechanical energy from electrical appliances which are otherwise lost as a wasted form of energy. For this, I will tune the properties of a family of electronic materials called 'hybrid perovskites'. The two physical properties that I envisage exploiting for this 'multiple' energy harvesting are (a) photovoltaic - converting light to electricity and (b) piezoelectricity - converting mechanical vibrations to electricity. The hybrid energy harvesters that I develop will make the IoT technology more sustainable by reducing their sole dependence on batteries, and accelerate the wide acceptance of IoT in other applications such as in complete digitisation of manufacturing (industry 4.0), health care, agriculture, precision farming, smart city and transportation settings. In addition to the IoT, the hybrid harvesters that I develop will make other emerging technologies such as Wearables more sustainable and the associated data collection, especially related to health monitoring, more reliable.

UKRI Gateway to Research · FY 2025 · 2025-06

A central task in data science is to fit a large multivariate normal model from fewer datapoints than variables.  The reason is that, in many applications such as neuroscience, structural biology or archaeology, data is either expensive or even impossible to obtain. A widely-used approach is to assume sparsity from some known conditional independences among pairs of variables and then use maximum likelihood estimation. This project will establish new geometric and combinatorial approaches to the question of which independences allow for maximum-likelihood estimation from a fixed sized sample.  More generally, the project will study which linear constraints on the inverse covariance imply the existence of a maximum likelihood estimator for a fixed size sample—a question that involves a subtle interplay between geometry and structural graph theory. The project will exploit recently-discovered links between such data complexity problems and rigidity theory, a field of discrete geometry at the intersection of combinatorics, algebra, and geometry. Consider a scaffold-like structure composed of stiff bars linked at universal joints, with the connectivity of the bars modelled by a graph. Spectral properties of a weighted Laplacian of the structure’s graph control whether the structure can be “lifted” to another structure with maximal affine span and the same bar lengths.  Whether a typical structure in a given dimension can be lifted determines whether the maximum likelihood estimator for an associated Gaussian graphical model exists, providing a geometric avatar for the original statistical problem. A key feature of the project is to initiate an in-depth and sustained exploration of the interplay between linear concentration models and the geometry of rigid structures. The main goals are to: (1) characterise the linear concentration models that have a maximum likelihood estimator for each number of samples; and (2) develop geometric and combinatorial rigidity of linear measurement processes on squared edge lengths and characterise the associated algebraic matroids.

UKRI Gateway to Research · FY 2025 · 2025-06

Circe: Co-rotating Interaction regions colliding with exoplanets On the present-day Earth, geomagnetic storms occur when fast and slow streams of the solar wind collide, generating shocks and producing showers of fast particles that penetrate into, and interact with, the Earth’s atmosphere. These corotating interaction regions permeate the solar wind and their cumulative effect on planetary atmospheres can exceed that of the more powerful, but less frequent, flare-related coronal mass ejections. Although these interaction regions are known to be important in the solar wind, and are well-studied in massive stars, there have been no large-scale studies of their frequency and power in solar-type stars. This project will extend our understanding of these features to the many other types of stars now known to host a range of exoplanets whose upper atmospheres may be vulnerable to the heating induced by this geomagnetic activity. We will develop semi-analytical models in a broad-based study that will characterise these corotating interaction regions as a function of stellar mass and age. We will build on the recent growth in space-based in-situ studies of the solar wind that provide a wealth of data on these interaction regions and the impact of their accelerated particles on the Earth, Mars and Venus. For other stars, we will use spectropolarimetric studies that provide magnetic maps of the surfaces of > 100 stars, many of which are known planet hosts. These maps show the locations from which fast and slow wind streams emerge and hence determine where they collide. Young, rapidly-rotating stars are likely to produce the most powerful interactions. Indeed, using one of these maps as an input, a proof-of-concept MHD simulation of the young Sun kappa Ceti predicted corotating interaction regions whose pressure pulses are 1300 times greater than the background stellar wind. We will also use rotational evolution models to evolve a solar-mass star in time from its pre-main sequence phase to the present day. This will allow us to determine at what point in its history the solar wind hosted the most powerful corotating interaction regions. We will compare this with the known stages in the evolution of the Earth’s atmosphere, and estimate the distribution of energies of the particles accelerated by these interaction regions.