The acoustics industry contributes £4.6 billion to the UK's economy annually, employing more than 16,000 people, each generating over £65,000 in gross value added across over 750 companies nationwide. The productivity of acoustics industry is similar to that of other enabling technologies, for example the UK photonics industry (£62k per employee in 2014). Innovation through research in acoustics is a key to its industry success. The UK's acoustics industry and research feeds into many major global markets, including the $10 billion market for sound insulation materials in construction, $7.6 billion ultrasound equipment market and $31 billion market for voice recognition. This is before the vital role of acoustics in automotive, aerospace, marine and defence is taken into consideration, or that of the major UK industries that leverage acoustics expertise, or the indirect environmental and societal value of acoustics is considered. All the four Grand Challenges identified in the 2017 UK Industrial Strategy require acoustics innovation. The Industrial Strategy Challenge Fund (ISCF, https://www.ukri.org/innovation/industrial-strategychallenge-fund/) focuses on areas all of which need support from acoustics as an enabling technology. The future of acoustics research in the UK depends on its ability to contribute to the Four Grand Challenges. Numerous examples are emerging to demonstrate the central role of acoustics in addressing the four Grand Challenges and particularly through more focused research. The acoustics-related research base in the UK is internationally competitive, but it is important to continue to link this research directly to the four Grand Challenges. In this process, the role of UK Acoustics Network (UKAN) is very important. The Network unites over 870 members organised in 15 Special Interest Groups (www.acoustics.ac.uk) who represent industry, academia and various non-academic organisations which success relies on the quality of acoustics related research in the UK. UKAN was funded by the EPSRC as a standard Network grant with the explicit aim of pulling together the formerly disparate and disjoint acoustics community in the UK, across both industry and academia. UKAN has been remarkably successful. Its success is manifested in the large number of its members, numerous network events it has run since its inception in November 2017 and contribution it has made to the acoustics research community. Unfortunately, UKAN has not been in the position to fund new, pilot adventurous or translational projects nor has it any funding support for on-going research or knowledge transfer (KT) activities. The purpose of UKAN+ is to move beyond UKAN, create strategic connections between acoustics challenges and the Grand Challenges and to tackle these challenges through pilot studies leading in turn to full-scale grant proposals and systematic research and KT projects involving a wider acoustics community. There is a great opportunity for the future of the UK's acoustics related research to move on beyond this point, build upon the assembled critical mass and explore the trans-disciplinary work initiated by UKAN. Therefore, this proposal is for UKAN+ to take this community to the next stage, connect this Network more widely in the UK and internationally to contribute through coordinated research to the solution of Grand Challenges set by the government. UKAN+ will develop a new roadmap for acoustics research in the UK related to Grand Challenges, award exploratory (pilot) cross-disciplinary research projects to the wider community to support adventure research and knowledge transfer activities agreed in the roadmap and support the development of develop full-scale bids to the government research funding bodies which are aligned with the Grand Challenges. UKAN+ will also set up a National Centre or Coordination of Acoustics Research, achieve full sustainability and support best Equality, Diversity and Inclusion practices.

Computer models have played a central role in assessing the behaviour of nuclear power facilities for decades, they have ensured nuclear operations remain safe to both the public and the environment. The aim of the project is to develop a new and highly advanced modelling capability that is accurate, robust and validated. A new multi-physics, predictive modelling framework will be formed for simulating neutron transport, fluid flows and structural interaction problems. It aims to combine novel and world leading technologies in numerical methods and high performance computing to form a simulation tool for geometrically complex, nuclear engineering problems. This will surpass current computational capabilities, by providing modelling accuracy through the use of efficient adaptive resolution, and will tackle grand challenge problems such as full core reactor modelling. This model will be developed within a predictive framework that combines modelling with uncertainty and experimental data. This is a vital component as inherent uncertainties in data, geometry, parameterisations and measurement will place uncertainties in the modelled predictions. By integrating these uncertainties within the calculations we can quantify the uncertainty they place on the final result. The combination of all these technologies will result in the first modelling framework of its kind, offering unprecedented detail through optimised resolution with combined uncertainty quantification and data assimilation. It will provide substantially improved analysis of nuclear facilities, improve operational efficiency and, ultimately, help ensure its safety. The project will work closely with world leading academics and industry, both within the UK and overseas. This collaboration will result in the technologies being used to analyse future reactor designs, including those reactors due to be built in the UK over the coming years.

The UKRI Centre for Doctoral Training in Machine Intelligence for Nano-electronic Devices and Systems (MINDS-CDT) will operate as a centre of training excellence in the next generation of systems that employ Artificial Intelligence (AI) algorithms in low-cost/low-power device technologies: hardware-enabled AI. The use of AI in real-world applications through systems of interconnected devices (so-called Internet of Things) is increasingly important across the global economy. Various market surveys estimate the sector to be valued in the hundreds of billions, and project levels of compound annual growth of 25-30%. Applications of these technologies include smart cities, industrial IoT and robotics, connected health and smart homes. It is widely agreed that new advances in artificial intelligence and machine learning are key to unlocking the potential of these systems. Significant challenges remain, however, in the development of robust algorithms and coordinated systems that are efficient, secure, and work in concert with modern devices. Advances in electronics will soon hit atomic scales, requiring new approaches if we are to continue to improve hardware speed and power consumption. Novel nanotechnologies such as memristors have the potential to play a key role in addressing these challenges, but critical to their employment in real-world applications is how algorithms work in the context of device physics. Further, there are significant challenges around how resources available to devices (energy, memory, etc.) can more effectively adapt to the computational tasks at hand, again requiring us to think about how hardware and software work together. The MINDS CDT is unique in its cross-disciplinary research programme crossing emerging AI algorithms and models with advances in device technologies that underpin and enable their potential. To quote from one of our industry partners, "innovation is to come from software and hardware co-development" and that "this joined-up thinking as a potential game changer". The MINDS-CDT will train a substantial number of experts with the knowledge and skills to lead the development of this next generation of intelligent, embedded systems. The training programme will draw from both computer science and electronics expertise at the University of Southampton, and a substantial network of stakeholders from across industry, government and the broader economy. Core to our training ethos is the up-front investigation of the potential impacts of technological innovation on society, security and safety, and in the engagement of interest groups and the public in understanding the benefits as well as the risks of the use of these new developments in AI and technology for our society and economy. The processes we will use here include that all projects and research activities will be informed by in-depth impact assessment, and we will instigate an ambassadors programme for public engagement and, in particular, the engagement of underrepresented groups in AI and engineering.

Plutonium dioxide is a very dynamic material. Radioactive decay damages the lattice and also forms other elements in the material. Helium, an inert gas, may be localised or trapped in the lattice, or maybe released. Uranium isotopes (formed from the decay of plutonium-238, 239, 240) and americium-241 (formed from decay of plutonium-241) are formed atom-by-atom within the plutonium dioxide lattice. The UK has 140 tonnes of separated plutonium in the form of plutonium dioxide, the World's largest civil stockpile. This has been separated over the last half century and will need to be stored for several decades into the future before its end use. Currently, Government intends most of this material to be made into nuclear reactor fuel ('mixed oxide fuel'), with a small proportion, which cannot be made into fuel, being disposed of as waste, although policy changes could lead to more of it being designated as waste. Whatever the final fate of the plutonium, the material will need to be processed into a suitable form for its end use, and its evolution while it is being stored will affect its suitability for processing. We therefore need to be able to predict how plutonium dioxide will change in storage, so we know whether it will be suitable for its final use. The purpose of this project is to understand how plutonium dioxide changes so we can make these predictions. We will make experimental measurements with plutonium dioxide to define the effects of radiation damage, helium formation and decay product formation on the material over timescales up to several decades. The evolution of plutonium dioxide will be explored using both a series of model samples and materials drawn from the UK stockpile. Behaviour of decay products will be determined using the stockpile materials. We will use synchrotron techniques (X-ray absorption spectroscopy, diffraction and tomography), electron microscopy and specific surface area measurements to characterise the materials. The results of these experiments will be used to develop computational models of plutonium dioxide evolution. Because decay products form atom-by-atom, and decay processes affect the electronic structure of the material, we need to model all these processes at the scale of individual atoms and small aggregates of atoms, but because the properties we are interested in are manifest at the lattice scale, we also need to understand how the atomic-scale effects carry across to this larger scale, and we will also develop models which we can use at this larger scale.

The goal of Laser Inertial Confinement Fusion (ICF) is to create and ignite a minute star. The energy liberated through thermonuclear fusion can be harnessed, providing mankind with an essentially limitless source of safe, sustainable, secure, carbon-free, electricity. If realised, laser-fusion would not only provide a solution to global warming, but enable the UK to become a net energy exporter, and also create a new market in ultra-high-tech technology exports in areas where the UK is currently world-leading, such as laser and targetry manufacture. The multi-billion dollar National Ignition Facility (NIF) is currently the only laser which, in principal, has sufficient energy to achieve ignition (where the 'star' burns), although to-date NIF has not achieved ignition. The base-line 'indirect-drive' NIF design uses an array of laser beams to create x-rays in a metallic cylinder (hohlraum), these x-rays in turn ablate the spherical ICF target, driving a convergent implosion. This causes the target to be compressed, creating density and temperature conditions similar to those within the centre of the Sun, thereby igniting the 'star'. While there are some advantages to the indirect-drive approach to ICF, it is extremely inefficient, and it is currently unclear whether it will be possible to achieve indirect drive ignition with the laser energy available on NIF. Alternative ICF schemes exist including 'direct drive' and 'shock ignition'. Here, the lasers directly illuminate the target improving efficiency by a factor of ~5, meaning it should be possible to achieve ignition with NIF's energy. Shock ignition is a recently invented variant of direct drive. Here the implosion velocity can be lower than the minimum required for ignition, instead ignition is initiated by a strong shock launched towards the end of the implosion. Shock ignition has many potential advantages over other ICF schemes; the laser energy requirements for ignition are well within those possible on NIF, as the implosion velocity can be lower, the susceptibility to deleterious fluid instabilities (Rayleigh-Taylor) is also reduced. Importantly, the energy gain (fusion energy out/electrical energy in) should be sufficient for power generation. Laser-plasma interaction instabilities (LPI) such as Stimulated Raman Scatter, Two Plasmon Decay and Stimulated Brillouin Scatter occur in all ICF schemes. These LPIs alter the temporospatial characteristics of laser absorption and can create significant populations of energetic (or hot) electrons. Determining the characteristics of the LPIs and the associated hot electrons is of critical importance for ICF as they dictate whether the fusion fuel will be heated prior to the fuel being compressed (pre-heat) - potentially precluding ignition - or whether the hot electrons' energy can be harnessed, enhancing shock generation in the shock ignition scheme, potentially leading to fusion energy gains sufficient for energy applications on today's lasers. This crucial area of ICF physics is the focus of this proposal. New experiments on the Omega laser facility will measure the LPI and hot electron characteristics in the parameter spaces of ignition-scale direct drive and shock ignition. A key outcome will be the encapsulation of the experimental data in innovative new laser-plasma interaction and hot electron simulation models, which will run in-line with the UK's radiation-hydrodynamics code framework: Odin. These will significantly improve our predictive simulation capabilities, providing benchmarked, high-fidelity simulation tools which will be made openly available to the UK academic laser-plasma physics community. This work, with direct involvement and leadership of ICF experiments on large scale facilities, provides a clear route by which the UK community can attain the skills, expertise, and tools to develop next-generation ICF designs for, and execute experiments on, the world's largest largest lasers into the 2020s.