Microprocessors chips are in most devices we interact with in our daily lives. From mobile devices, TVs, cars, fridges, petrol station pumps, servers that power the web and social media infrastructure --- the list is endless. Microprocessors have been doubling in power roughly every two years following Moore's law, which has been enabled by making the features of the chips smaller, fitting more transistors per unit area and driving the entire consumer electronics market worth more than £1 trillion per year. In order to continue to satisfy the industrial and societal demand that drives Moore's law, there are some fluid dynamics modelling challenges that we need to overcome. The next-generation of photolithography machines that need to manufacture smaller, faster microprocessor chips and the new devices required to supercool the high-performance chips during operation can be enabled by understanding and predicting accurately how gases behave at the micro/nanoscales, or in vacuum-like conditions. In these multiscale flow problems, the fluid dynamics is often unintuitive and all equations we normally turn to for modelling and designing engineering flow problems, such as flow around aircraft and ships using Navier-Stokes equations, are no longer valid here, because the gas is no longer in local thermodynamic equilibrium, on which these classical equations are formulated. The direct simulation Monte Carlo (DSMC), is the state-of-the-art software for modelling these non-equilibrium gas flows. It is a stochastic particle method with large numerical stability and can resolve the molecular nature of gases in three dimensional geometries. However, because it is a particle method, it requires a voracious computational cost to produce engineering solutions of scales that matter to industry. DSMC also performs poorly if those flows are at low speed, due to the inherent thermal noise in the particles blocking the measurable signals. In this project, we propose developing a new multiscale method, one which combines DSMC with computationally cheaper models such as those used in Computational Fluid Dynamics (CFD). We will produce a step change in simulation efficiency and accuracy by connecting DSMC and CFD solvers using surrogate modelling and Bayesian inference. With strong backing from our industrial partners, we will turn the outcome of this project into a free open-source computational solver released in the UK's OpenFOAM software that is validated with experimental data. The industrial focus of this project will be on processor-chip manufacturing, chip thermal management and electrospray technologies, but the underlying method is general to new directions in other research and industrial areas.

HetSys students will develop and apply computational models for heterogeneous material systems, addressing three distinct but closely connected shortcomings in current modelling paradigms: (i) most material systems of scientific and technological interest are highly heterogeneous in structure, phases, and range of length- and time-scales, whereas the predominant modelling paradigms typically focus on limited scenarios; (ii) coupling of scales is typically ad hoc, thus lacking robust quantification of uncertainty propagation across scales, essential for reliable and applicable models; (iii) research software is often poorly maintained and hard to re-use, further slowing down progress. Overcoming these interdisciplinary challenges to unlock more efficient simulation-for-design capabilities has been hindered by outdated training approaches: the pathway followed by, for example, a theoretical physicist has been distinct from that of a materials engineer, with the resulting lack of a 'common language' preventing synergy across disciplines. HetSys will transform this landscape by being the first CDT explicitly targeting modelling of heterogeneous systems required by industry and academia, with all models to be implemented in robust and reusable software that produces probabilistic error bars on all outputs using uncertainty quantification (UQ). Exemplar research challenges range from novel materials and devices exploiting multiscale physics and chemistry, high performance alloys, direct drive laser fusion, future medicine exploration, smart nanofluidic interfaces, and flow through heterogeneous rocks. HetSys' mission is to train high-quality computational scientists who can develop and implement new methods for modelling complex and heterogeneous systems in collaboration with scientists and end-users. Working in a highly interdisciplinary context is challenging even for experienced researchers but especially for an isolated PhD student. Creating a cohesive, interdisciplinary cohort connected through a joint training programme with an existing vibrant cross-departmental research community will create a culture that significantly lowers the entrance barrier into this style of research. Our multidisciplinary approach aligns with the formation of UKRI and will help to address the productivity gap identified in the industrial strategy by targeting several challenges and national priority areas. As noted by Innovate UK/KTN: "Industry requires new insight into how [materials] behave and uniquely this proposal sets the understanding of how uncertainty propagates across scales as a central theme". These benefits are recognised by industry through HetSys' strong support from 14 industrial project partners. We have also established bilateral links with 12 international partners who have identified the same urgent modelling challenges. The potential impact of the postgraduate training is affirmed by the career destinations of the 70 students who completed their studies with the 33 HetSys supervisors since 2012: 27 have proceeded into academic research (21 postdoctoral and 6 academic posts), 28 into careers in industrial R&D and the engineering industry, 4 into IT, 2 to consultancy, 6 into school teaching and 2 to finance. The strong absorptive capacity for graduates is recognised by project partners, e.g. AWE: "given the ever growing importance that computational modelling is acquiring in the UK and internationally, there will be significant competition for the number of doctoral level scientists and engineers that you are proposing to train". New paradigms in the study of heterogeneous materials are vital for both academic research and industry. Future impact at larger scales will be greatly increased if researchers can be trained to master a wide range of techniques and encapsulate them in well-designed software.

Given the unprecedented demand for mobile capacity beyond that available from the RF spectrum, it is natural to consider the infrared and visible light spectrum for future terrestrial wireless systems. Wireless systems using these parts of the electromagnetic spectrum could be classified as nmWave wireless communications system in relation to mmWave radio systems and both are being standardised in current 5G systems. TOWS, therefore, will provide a technically logical pathway to ensure that wireless systems are future-proof and that they can deliver the capacities that future data intensive services such as high definition (HD) video streaming, augmented reality, virtual reality and mixed reality will demand. Light based wireless communication systems will not be in competition with RF communications, but instead these systems follow a trend that has been witnessed in cellular communications over the last 30 years. Light based wireless communications simply adds new capacity - the available spectrum is 2600 times the RF spectrum. 6G and beyond promise increased wireless capacity to accommodate this growth in traffic in an increasingly congested spectrum, however action is required now to ensure UK leadership of the fast moving 6G field. Optical wireless (OW) opens new spectral bands with a bandwidth exceeding 540 THz using simple sources and detectors and can be simpler than cellular and WiFi with a significantly larger spectrum. It is the best choice of spectrum beyond millimetre waves, where unlike the THz spectrum (the other possible choice), OW avoids complex sources and detectors and has good indoor channel conditions. Optical signals, when used indoors, are confined to the environment in which they originate, which offers added security at the physical layer and the ability to re-use wavelengths in adjacent rooms, thus radically increasing capacity. Our vision is to develop and experimentally demonstrate multiuser Terabit/s optical wireless systems that offer capacities at least two orders of magnitude higher than the current planned 5G optical and radio wireless systems, with a roadmap to wireless systems that can offer up to four orders of magnitude higher capacity. There are four features of the proposed system which make possible such unprecedented capacities to enable this disruptive advance. Firstly, unlike visible light communications (VLC), we will exploit the infrared spectrum, this providing a solution to the light dimming problem associated with VLC, eliminating uplink VLC glare and thus supporting bidirectional communications. Secondly, to make possible much greater transmission capacities and multi-user, multi-cell operation, we will introduce a new type of LED-like steerable laser diode array, which does not suffer from the speckle impairments of conventional laser diodes while ensuring ultrahigh speed performance. Thirdly, with the added capacity, we will develop native OW multi-user systems to share the resources, these being adaptively directional to allow full coverage with reduced user and inter-cell interference and finally incorporate RF systems to allow seamless transition and facilitate overall network control, in essence to introduce software defined radio to optical wireless. This means that OW multi-user systems can readily be designed to allow very high aggregate capacities as beams can be controlled in a compact manner. We will develop advanced inter-cell coding and handover for our optical multi-user systems, this also allowing seamless handover with radio systems when required such as for resilience. We believe that this work, though challenging, is feasible as it will leverage existing skills and research within the consortium, which includes excellence in OW link design, advanced coding and modulation, optimised algorithms for front-haul and back-haul networking, expertise in surface emitting laser design and single photon avalanche detectors for ultra-sensitive detection.

We propose to build the EPSRC Centre for Doctoral Training in Sensor Technologies for a Healthy and Sustainable Future (Sensor CDT) on the foundations we have established with our current CDT (EPSRC CDT for Sensor Technologies and Applications, see http://cdt.sensors.cam.ac.uk). The bid falls squarely into EPSRC's strategic priority theme of New Science and Technology for Sensing, Imaging and Analysis. The sensor market already contributes an annual £6bn in exports to the UK economy, underpinning 73000 jobs and markets estimated at £120bn (source: KTN UK). Major growth is expected in this sector but at the same time there is a growing problem in recruiting suitably qualified candidates with the necessary breadth of skills and leadership qualities to address identified needs from UK industry and to drive sustainable innovation. We have created an integrated programme for high quality research students that treats sensing as an academic discipline in its own right and provides comprehensive training in sensor technologies all the way from the fundamental science of sensing, the networking and interpretation of sensory data, to end user application. In the new, evolved CDT, we will provide training for our CDT students on themes that are of direct relevance to a sustainable and healthy future society, whilst retaining a focus that delivers value to the UK economy and academia. The 4-year programme is strongly cross disciplinary and focuses on sustainable development goals and emphasises training in Responsible Innovation. One example of the latter is our objective to 'democratise sensor technologies': Our students will learn how to engage with the public during research, how to play a valuable part in public debate, and how to innovate technology that benefits society. Technical aspects will be taught in a bespoke training programme for the course, that includes lectures, practicals, lab rotations, industry secondments, and skills training on key underpinning technologies. To support this effort, we have created dedicated, state-of-the-art infrastructure for the CDT that includes laboratory, office, teaching, and social spaces, and we connect to the world leading infrastructure available in the participating departments and partner industries. The programme is designed to create strong identities both within and across CDT cohorts (horizontal and vertical integration) to maximise opportunities for peer-to-peer learning and leadership training through activities such as our unique sensor team challenges and the monthly Sensor Cafés, attended by representatives from academia, industry, government agencies, and the public. We will create a diverse and inclusive atmosphere where students feel confident and empowered to offer different opinions and experiences and which maximises creativity and innovation. We have attracted substantial interest and support (>£2.5M) from established industrial partners, but our new programme emphasises engagement also with UK start-ups and SMEs, who are particularly vulnerable in the current economic climate and who have expressed a need for researchers with the breadth and depth of skills the CDT provides (see letters of support). We recruit outstanding, prizewinning students from a diverse range of disciplines and the training programme connects more than 90 PIs across 15 departments and 40 industrial partners working together to address future societal needs with novel sensor technologies. Technology developers will benefit through connection with experts in middleware (e.g. sensor distribution and networking, data processing) and applications experts (e.g. life scientists, atmospheric scientists, etc.) and vice versa. This integrative character of the CDT will inspire innovations that transform capability in many disciplines of science and industries.