The functional electroceramics market is multibillion pounds in value and growing year by year. Electroceramic components are vital to the operation of a wide variety of home electronics, mobile communications, computer, automotive and aerospace systems. The UK ceramics industry tends to focus on a number of specialist markets and there are new opportunities in sensors, communications, imaging and related systems as new materials are developed. To enable the UK ceramics community to benefit from the new and emerging techniques for the processing and characterisation of functional electroceramics a series of collaborative exchanges will be undertaken between the three UK universities (Manchester, Sheffield and Imperial College) and universities and industry in Europe (Austria, Germany, Russia, Czech Republic), the USA and Asia (Japan, Taiwan and Singapore). These exchanges will enable the UK researchers (particularly those at an early stage of their careers) to learn new experimental and theoretical techniques. This knowledge and expertise will be utilised in the first instance in the new bilateral collaborative projects, and transferred to the UK user communities (UK universities and UK industry). A number of seminars and a two day Workshop will be held to help the dissemination of knowledge.

As we approach the theoretical limit of 3 nm transistor channel lengths, manufacturing challenges of CMOS architectures become exponentially more difficult and more expensive to overcome. Simultaneously, a seismic shift is occurring in the computational workload, away from offline processing to real-time big-data applications driven by the Internet of Things (IoT), robotics and autonomous agents. This combination of factors has led to an intensified exploration of alternative computing methodologies that span the entire Boolean computational stack from physical effects, to materials, devices, architectures, and data representations. It also includes novel, non-Boolean methods of computing such as quantum, wave and neuromorphic computation, Boltzmann machines and others. Exactly which combination of computational elements will evolve from this plethora of options is far from clear. However, it is possible to state general requirements future computing platforms must meet. First, any new computing methodology must be compatible with the existing multi-trillion-pound infrastructure associated with current CMOS based computing. Second, it must be scalable through multiple generations of incremental hardware and software improvements. Third, the performance/cost metric must greatly exceed that of Boolean CMOS processors, and, fourth, the new technology must provide a much more energy-efficient alternative to existing technology. Reservoir Computing (RC) leverages fast nonlinear dynamics in analogue physical systems to map a system's spontaneous transient response to solutions of traditionally hard problems such as classification tasks and signal prediction. This technique effectively ties memory and processing tasks to the intrinsic materials properties. The specific details of the physical system in which RC is implemented, however, are not relevant so long the following key criteria are met: dynamical non-linearity, high phase space dimensionality, uniquely reproducible initial state, easy out-of-equilibrium perturbation, and readability of dynamical state. The main quest is to identify a system suitable for the task, which is not plagued by real world-incompatible requirements. Our proposed solution is based on driven spin-wave excitations which guarantee both sufficiently complex transient responses, controlled chaoticity, as well as providing a natural spintronic platform for straightforward driving and reading of dynamical magnetic states. Our proposed work aims at demonstrating the versatility of spin-wave interference as the key candidate for the implementation of RC in a real-world device. We believe that spin-waves in magnetic nanostructures are ideal candidates for developing drop-in substitutes for circuit components, as well as stand-alone devices. Success in this endeavour would prove groundbreaking for the development of real-time pattern detection technologies with the potential for high-impact deployment in areas ranging from medical monitoring to climate modelling. Complex pattern recognition tasks could be performed on RC hardware with square-micrometre surface area, 100 micro-W power consumption and 10 ns inference time. Compared to the server stacks currently used by industry leaders (Google, Apple, Facebook, etc.) to satisfy global demand, success in this action will pave the way for massively more resource efficient big-data solutions.

Aerosol particles are key drivers of reduced air quality and provide significant offsetting of warming by greenhouse gases. The organic fraction is frequently observed to dominate mass of fine particulate matter (PM) and secondary organic aerosol (SOA) is the major contributor. With air pollution responsible for 11 % of global deaths annually and air temperature rise within 0.5 degree C of the target pursued by Paris Agreement signatories, accurate forecasts of organic aerosol particle mass loadings are required to inform policy decisions. We will interrogate experimental results presented in our recent landmark study to investigate the mechanisms determining SOA formation in atmospheric mixtures. We will include new mechanistic chemical understanding developed from this work into a coupled model of gaseous photochemistry and aerosol formation. Detailed comparison of the model with measured gaseous and aerosol composition will enable unprecedented confidence in our understanding of the interactions that can occur in the real atmosphere. We will use the model to demonstrate the magnitude of interactions to be expected in airmasses containing natural and manmade pollutants that promises to enable reasonable mechanistic interpretation of SOA formation in the real atmosphere for the first time. What... We will develop a mechanistic quantitative representation of oxidative chemistry leading to SOA formation in realistic atmospheric mixtures including interactions between biogenic and anthropogenic precursors. We will demonstrate its predictive capability by comparison with existing and emerging experimental data and use it to evaluate the potential for SOA formation and uncertainty ranges across VOC mixtures at VOC:NOx regimes applicable to the real atmosphere. Why... Our recent study (McFiggans et al., 2019) was transformative in that it showed that the formation of particulate mass in mixtures of gaseous precursors cannot be assumed to be the sum of that formed independently from the components of the mixture. We demonstrated that this resulted from two effects: i) oxidant scavenging; competition of the precursor molecules for the available oxidant and ii) product scavenging; vapour phase interactions between oxidation products that would have otherwise reacted to form condensed particulate mass. These two effects lead to the requirement for a realistic treatment of SOA formation in mixtures in order to predict atmospheric PM loading and its effect on human health and climate. How... We have data from a large number of published and (as yet) unpublished laboratory and chamber experiments, investigating SOA formation from the oxidation of individual VOC and their mixtures. In each, we quantify the formation of highly-oxygenated organic molecules (HOM) found to be major contributors to the condensed SOA mass. The VOC include key species from the major biogenic and anthropogenic classes of SOA precursors. We will extend the benchmark mechanism for atmospheric VOC oxidation to incorporate the most recent mechanistic understanding of HOM into our chamber model of coupled photochemistry and aerosol microphysics. We will optimise simulations using this model by comparison with the experimental data and conduct further simulations to establish the critical dependencies of SOA formation in the atmosphere. Large scale air quality and climate models will need to capture these relationships to enable confidence to be placed in their predictions. We will include a simplified mechanism based on the same framework as our more detailed scheme into the EMEP regional pollution model to demonstrate the impact of interactions in atmospheric mixtures of VOC on regional PM.

The traditional view of the ordering of polarisation or magnetisation in both ferroelectrics and ferromagnets is that local dipoles or magnetic moments are arranged into neat rows and columns, and that boundaries between neatly arranged groups must strictly conform to the crystallography of the host material (conventional stripe domains). However, recent experimental research in three-dimensionally size-constrained soft ferromagnets has revealed the existence of completely different domain states which form into vortices. As with many aspects of behaviour in ferromagnetism, analogous properties in the behaviour of the electrical polarisation in ferroelectrics is often seen, and recent modelling strongly suggests that such vortex domain states should also exist in ferroelectrics. Differences in the energetics between ferromagnets and ferroelectrics means that such unusual behaviour is only expected to dominate whenever ferroelectric dimensions are reduced to the order of ~10 nm. The creation of such small structures and the characterisation of their domain states represents a serious challenge to experimentalists involved in ferroelectric research and yet the potential for new discovery is immense. Further, simple vortex structures may only be the tip of the ice-berg, as much more exotic domain patterns have been postulated: for example some theorists have suggested the possibility of an electrostatic solenoid-analogue. Given the research performed to date, and the postulations made by theorists, the creation of three-dimensionally constrained nanostructures in ferroelectrics, and the subsequent analysis of their domain characteristics, clearly represents an exciting and challenging problem. This project will address this area of research by combining expertise in nanoscale ferroelectric fabrication with specialist characterisation techniques such as electron holography, second-harmonic near field optics, nano-Raman spectroscopy and scanning probe microscopy. The programme builds on an already established successful collaboration between ferroelectric activities in Queen's University Belfast and Cambridge, and this is augmented by international experts in specifically chosen characterisation techniques.

Biomass burning (BB) and wildfires release huge quantities of particulates and trace gases into the atmosphere in amounts highly variable in space and time. Plume rise means these that under certain conditions these emissions can be injected into the atmosphere at heights far above the Earth surface, enhancing their long-range transport and altering their atmospheric chemistry, radiative budget, and air quality effects. Results from past project show that UK air quality can be signficantly affected by long-range transport of smoke from European and Russian wildires, and smoke from fires in Canada can be detected in air samples at DEFRA monitoring stations in e.g. Mace Head. Near real-time (NRT) atmospheric modelling and forecasting schemes aiming to realistically represent these aspects of the Earth system must include a high temporal resolution, non-retrospective source of BB emissions information - which generally comes from satellite Earth Obervation data. However, as discussed above, a fires smoke plumes buoyancy characteristics can strongly influence its atmospheric impact, and this is increasingly realised to be an important term to represent when modelling the long-range effects of wildfire smoke emissions. However, a lack of a priori information and, until recently, a directly-related EO observable, has meant that parameterisation of smoke plume injection height has received far less attention than has estimating the magnitude and variability of the smoke emissions. This KE Project will exploit the findings from two successful NERC research projects to provide major improvements to the current (ad hoc) prescription of wildfire smoke plume injection height in the prototype GMES UK/European atmospheric monitoring and forecasting scheme (the 'GMES Atmospheric Core Service', which is based on the world-leading integrated forecast system (IFS) of ECMWF in the UK and which is being desiged to provide the public, policy makers and downstream organisations with access to state-of-the-art atmospheric chemistry monitoring and forecasting data. The GACS serves a broad community of users, for example those involved in environmental policy development and policing, those delivering downstream services related to the health community (warning of increased asthma incidence during air pollution episodes), and those aiming to reduce public exposure to air pollution. We will work with Project Partners developing the GACS to exploit the research on plume height rise developed in NE/E016863/1 and the EO data processing procedures developed in NE/H00419X/1 to provide a much more realistic representation of smoke injection height in the GACS system; one that takes account of both fire and atmospheric characteristics such that the atmospheric transport of these emissions, including to the UK, can be better represented. The Project Partners are ECMWF, who lead GACS development in the UK and who operate the global model within which the plume rise scheme will be embedded, and Jülich Research Centre who are experts in the chemistry and transport of smoke emissions and who are a main partner in the GACS development. The KCL Environmental Research Group (KCL-ERG) are a 'down-stream' user of global atmospheric model output, funded by UK Government to provide regional air quality (AQ) monitoring and modelling, and this KE project will support them in starting to use the enhanced GACS outputs in their UK regional and London-wide AQ modelling schemes, in particular to take better take account of smoke-polluted air that is known to move into the UK from e.g. eastern Europe or western Russia, and which at present causes enhanced discrepancies between the AQ models and measurements (see DEFRA letter of support). All model outputs incorporating the new scheme will be made available freely through the GMES GACS system interface http://www.gmes-atmosphere.eu/ and for the UK region throught the online public interface www.londonair.org.uk/