Since the 2011 Fukushima disaster, a major priority for the nuclear sector has been to develop accident tolerant fuels (ATFs). A very promising ATF is uranium-nitride (UN). UN has a high thermal conductivity, enabling heat to be transferred efficiently so the fuel is meltdown-resistant. UN has a high fissile content, so more power can be generated than with existing oxide fuels for the same enrichment level. Mixed UN/PuN is a fuel option for Generation IV reactors breeding fissile material and producing less long-lived radioactive waste. So, UN is a safer, more environmentally friendly, and sustainable nuclear fuel. For similar reasons uranium-carbides are also attractive ATFs. However, preparing uranium-nitrides and -carbides by traditional routes presents challenges. An attractive approach is to use molecular uranium-nitride and -carbyne precursors and decompose them to binary nitrides and carbides. Sadly, for decades there were few molecular uranium-nitrides so a molecules-to-materials approach was not realistic. The situation for uranium-carbynes is worse; there are only two spectroscopic reports of uranium-carbynes at ~10 Kelvin. Recently, we prepared the first molecular uranium-nitride triple bonds (Science, 2012, 337, 717; Nature Chemistry, 2013, 5, 482). Metal-ligand multiple-bonding is fundamentally important in chemistry and we have made a number of contributions in this area (e.g. J. Am. Chem. Soc. 2014, 136, 5619; Angew. Chem. Int .Ed. 2014, 53, 4484) and preliminary results show that our molecular nitrides can be controllably decomposed to binary nitrides which opens up a molecules-to-materials approach. This Proposal aims to apply our recent coordination chemistry to the preparation of materials for energy in Grand Challenge and Priority Areas. We will develop a new range of uranium precursors to generate a platform to expand the range of nitrides. This exploits a blend of steric and electronic properties uniquely suited to stabilising uranium-ligand multiple bonds. Using these precursors we have identified four routes to maximise our chance of success to prepare high-value uranium-carbynes which have no precedent. With an expanded range of molecular uranium-nitrides and new uranium-carbynes we will build on preliminary results and investigate their decomposition to binary materials. The availability of new precursors leads to the possibility of exploring high pressure phase transitions to give new polymorphs. This is directly relevant to understanding fuels under extreme conditions in nuclear reactors and these metallic polymorphs are interesting to study as their itinerant vs localised 5f electron behaviour is magnetically fascinating and crucial to designing better ATFs. We will combine synthetic, structural, and materials studies with interdisciplinary magnetometric, computational, and spectroscopic studies with collaborators to give a comprehensive understanding of uranium-nitrogen and -carbon bonding, reactivity, and materials applications. A Fellowship will provide the best opportunity to oversee this complex programme of research, manage an intensive array of collaborations, and make the time to engage with the nuclear industry and translate academic advances on to the next level into industrially relevant applications. The researchers on this project will develop a range of skills in a recognised strategic skills shortage area. Our molecules provide unique opportunities to probe the nature and extent of covalency in uranium bonding; this issue is long-running, still hotly debated, and important because of the nuclear waste legacy in the UK. Spent nuclear fuel is ~96% uranium and the official Nuclear Decommissioning Authority figure for nuclear waste clean-up bill is 70 billion pounds. If we can better understand the chemistry of uranium this may in the future contribute to ameliorating the UK's nuclear waste legacy and provide new routes to ATFs to be developed with the Nuclear Industry.

When linguists are trying to determine how different languages are related or neuroscientists wish to know how one part of the brain is associated with another, how to analyse data which is both complex and massive is a fundamental question. However, an area of Statistics, namely Functional Data Analysis, where the data is described as mathematical functions rather than numbers or vectors, has recently been shown to be very powerful in these situations. This fellowship aims to take functional data analysis and advance it so that much more complex data can be investigated. This will require establishing a careful statistical framework for the analysis of such functions even in situations where the functions have strict relationships. By considering the underlying mathematical spaces which the functions lie in, it is possible to construct valid statistical procedures, which preserve these relationships, such as the functions needing to be positive definite or the functions needing to be related by a graph or network. As an example, comparison between different languages (for example, how is French quantitatively different from Italian) can be carried out in the framework of functional data but not without considering specifically how the data should be analysed to take into account its particular properties. For example in trying to find a path from one language to another, it would be sensible to try to only go via other feasible acoustic sounds. This turns out to be mathematically related to shape analysis, a simple example of which might be how to describe going from London to Sydney. The shortest path is through the centre of the Earth, but this is not sensible, so you have to go round the world. Establishing links between shape analysis and functional data is a major aim of this fellowship. In addition, most brain analysis currently splits the brain up into lots of elements know as voxels, and then analyses these voxels one by one. However, the brain is really one object (or complex 3-D object) which should be analysed together. This is another example of functional data and the methods developed in this fellowship will enable the analysis of the brain as a single object. This will be done by examining the types of dependence between observations in brain imaging data, and using these to build such an object. Of particular interest will be the analysis of brain connections resulting from particular tasks which will require a mixture of functional data analysis and graphical or network analysis. However, before this can be done and the resulting insights into the brain found, the statistical methods required to do this need to be developed.

Laying eggs or giving birth to live young are two fundamentally different ways for females to produce their offspring. All birds, crocodilians, turtles, monotreme mammals (such as duck-billed platypus), and many lizards and snakes are egg-laying, as were most dinosaurs. In contrast, all placental mammals (like humans), marsupials, and some lizards and snakes are live-bearing. From studying embryos we know that many molecular and developmental aspects of these reproductive modes arose deep within the tree of life. For example, ancient egg-making structures are still retained within mammalian placenta, and the genes activated by pregnancy in lizards are the same as those activated by pregnancy in mammals and seahorses. Yet, clearly, substantial reproductive differences evolved between species; though it is not known how or why because the core genetic controls of these reproductive modes remain unknown. This major and obvious gap in our biological knowledge has persisted into the genomic era - where we can now study the entire DNA sequence of an organism - because we lacked an informative experimental model. Simply put, to test the genetic basis of traits that differ, the definitive experiment is to make a cross between the two different types. In the case of reproductive mode this is usual not possible, because species are too divergent to successfully breed. For example, no one can make a genetic cross of a platypus and a snake to test if the 'egg making DNA' is the same in both species. Our proposal seeks to shed light on the genetic basis of these fundamental reproductive traits using an exceptional species: the humbly-named 'common lizard'. Native to all of Eurasia, including the British Isles, this species harbours a secret underneath its simple brown scales: some populations are egg-laying and others are live-bearing. Like all reptiles, egg-laying is the original, or ancestral, mode. This means that many millions of years ago all common lizard females laid eggs. Then, about three million years ago, some females discarded the egg-laying tactic; no longer encircling their embryos in eggshells, the females retained their babies inside their bodies until fully developed. Why and how this happened is not known, but is presumed to be an adaptation that allowed mothers to better protect their embryos from cold and challenging environments. Amazingly, evolutionary reconstructions suggest that another million years later, some common lizards abandoned the live-bearing strategy and reversed back to egg-laying. Today we have populations with the original egg-laying strategy (mostly in the Alps), the live-bearers (across most of Eurasia), and those few that reversed back to egg-laying from live-bearing (found in the Pyrenees). Importantly, because they are closely related, individuals from all of these populations can interbreed. To test long-standing ideas about the genetic basis of fundamental reproductive traits, we plan to do controlled functional studies of the different types found within these lizards and make experimental crosses between them. By comparing the two lineages of egg-laying lizards we will be able to identify the genes necessary for egg-laying. This is due to the fact that the core genes should be found in the genomes of both and, if they are shared, these genes should be expressed in similar places and times. Then, using all the information we gain about how and where genes are active, we will use computational approaches to retrace the evolution of 'egg-laying' and 'live-bearing' genes across the history of the entire species. This will reveal how changes in a species' DNA give rise to changes in reproductive mode. Because of the ancient origins and sharing of reproductive genes across species, the lessons learned from these lizards will provide new and valuable insights into the biology, reproductive health, and evolution of all vertebrates.

The UK and global research and development communities have made tremendous strides in electronic device prototyping. Platforms that support conventional electronics have become well established, and the emerging potential of printed electronics and related additive technologies is clear. Together these support fast and versatile prototyping of the form and function of digital devices that underpin novel interactive data-driven experiences, including the Internet of Things (IoT), wearable technologies and more. However, challenges remain to realise their full potential. Interactive devices prototyped in labs and makerspaces implement novel capabilities and materials which require holistic manufacturing capability beyond simulation of conventional electronics. Even for conventional bench designs, to make the transition from prototype to product they need to be suitably robust, safe, long-lived, performant and cost-effective to deliver value as products - whether as a series of one-off mass customised devices, low-volume batches, or mass-produced artefacts. Unfortunately, the transition from prototype to production is not a natural one for end users; many ideas with potential don't progress beyond the first few designs. Democratising access to device production is the key next step in underpinning scalability and entrepreneurship in digital systems. We propose a Network+ of universities, research organisations and commercial enterprises who share the common goal of improving the transition from prototyping to production of digital devices. The Pro2 community will build upon the design and fabrication expertise of its researchers and practitioners to facilitate a deep synthesis of established principles, techniques and technologies and develop new concepts that span computer science, engineering and manufacturing. We will complement the on-going global investment into a variety of 'digital manufacturing' topics - including the UK's Made Smarter initiative - by tackling the challenge of progressively and cost-effectively transitioning from unconventional and single digital device prototypes, through tens of copies that can verify a design and validate utility, to batch production of hundreds to thousands of units. In prototyping, as additive manufacture and printed electronics converge further, in unconventional fields such as soft robotics and 4D printing, we need to identify how to integrate and optimise tools into workflows that support digital behaviour across materials, scales and functionalities. In production, smoothing the path from one-off microcontroller prototypes to scale-up is a significant challenge, and requires new processes and tools as well as reconfiguration of business models and services. Our vision for 'organic scaling' from prototype to production will allow faster exploration and exploitation of these digital device concepts and applications. This will accelerate the adoption of IoT, the growth of new consumer electronics markets, and more generally underpin the data-driven digital transformation of many industries. It will enable new research directions, create new business opportunities and drive economic growth.

Generally speaking, modern domestic species are actively prevented from interbreeding with wild populations. The few exceptions to this rule involve the deliberate generation of novel hybrid pets such as those involving domestic and wild cat species. This practice of incorporating wild species in breeding lines is strongly discouraged amongst livestock species since the introduction of genes from wild populations reduces productivity and the degree of tameness in the hybrids. In the recent past, however, husbandry practices were far less restrictive. Recent ethnographic and genetic analyses have revealed that interbreeding between numerous species of domestic and wild species was, in fact, the rule and not a rare exception. While gene flow from wild populations can be detrimental, it can also have a positive impact on livestock populations. For example, by decreasing the risks associated with inbreeding and by introducing genetic variation that allowed for rapid adaptation to novel environments. Adaptive gene flow therefore potentially played an important role during the spread of domestic animals across the world. This is especially true of pigs since geographically and genetically differentiated populations of wild boar are present across Eurasia and adapted to a wide variety of climates and environments; thus providing raw material that could have been absorbed by arriving domestic pigs. In fact, we demonstrated that gene flow between wild and domestic pigs was common and that it began immediately following the introduction of pigs to Europe from the Near East where they were initially domesticated. Despite this gene flow, pigs in Europe maintained their integrity as domestic animals by retaining their morphological and behavioural distinctiveness, suggesting that though some wild boar genomic variation was incorporated into domestic stocks, many wild boar genetic variants were actively expunged. Here, we will determine whether some wild genetic variants were preferentially expunged and whether some were preferentially incorporated into domestic populations. Ultimately, this project will reveal not only the genomic basis for domestication, but also how domestic pigs adapted to novel environments, by identifying specific genomic regions that were rapidly incorporated, and which ones were resisted during gene flow. To do so, we will assess the DNA preservation of more than 1,000 ancient pigs and wild boar from Eastern and Western Eurasia over the past 10,000 years, and then sequence the entire genomes of the best preserved specimens. Armed with this data, we will establish the spatial and temporal differences in the proportion and genomic location of the incorporation of wild boar genes into domestic stocks. The results will allow not only an unprecedented understanding of the origins of domestic animals, they will also have important ramifications for the conservation of endangered wild boar populations and for pig breeders and consumers of pork for whom the authenticity of domestic and wild meat is crucial.