This proposal seeks funding to create a Centre for Doctoral Training (CDT) in Connected Electronic and Photonic Systems (CEPS). Photonics has moved from a niche industry to being embedded in the majority of deployed systems, ranging from sensing, biophotonics and advanced manufacturing, through communications from the chip-to-chip to transcontinental scale, to display technologies, bringing higher resolution, lower power operation and enabling new ways of human-machine interaction. These advances have set the scene for a major change in commercialisation activity where electronics photonics and wireless converge in a wide range of information, sensing, communications, manufacturing and personal healthcare systems. Currently manufactured systems are realised by combining separately developed photonics, electronic and wireless components. This approach is labour intensive and requires many electrical interconnects as well as optical alignment on the micron scale. Devices are optimised separately and then brought together to meet systems specifications. Such an approach, although it has delivered remarkable results, not least the communications systems upon which the internet depends, limits the benefits that could come from systems-led design and the development of technologies for seamless integration of electronic photonics and wireless systems. To realise such connected systems requires researchers who have not only deep understanding of their specialist area, but also an excellent understanding across the fields of electronic photonics and wireless hardware and software. This proposal seeks to meet this important need, building upon the uniqueness and extent of the UCL and Cambridge research, where research activities are already focussing on higher levels of electronic, photonic and wireless integration; the convergence of wireless and optical communication systems; combined quantum and classical communication systems; the application of THz and optical low-latency connections in data centres; techniques for the low-cost roll-out of optical fibre to replace the copper network; the substitution of many conventional lighting products with photonic light sources and extensive application of photonics in medical diagnostics and personalised medicine. Many of these activities will increasingly rely on more advanced systems integration, and so the proposed CDT includes experts in electronic circuits, wireless systems and software. By drawing these complementary activities together, and building upon initial work towards this goal carried out within our previously funded CDT in Integrated Photonic and Electronic Systems, it is proposed to develop an advanced training programme to equip the next generation of very high calibre doctoral students with the required technical expertise, responsible innovation (RI), commercial and business skills to enable the £90 billion annual turnover UK electronics and photonics industry to create the closely integrated systems of the future. The CEPS CDT will provide a wide range of methods for learning for research students, well beyond that conventionally available, so that they can gain the required skills. In addition to conventional lectures and seminars, for example, there will be bespoke experimental coursework activities, reading clubs, roadmapping activities, responsible innovation (RI) studies, secondments to companies and other research laboratories and business planning courses. Connecting electronic and photonic systems is likely to expand the range of applications into which these technologies are deployed in other key sectors of the economy, such as industrial manufacturing, consumer electronics, data processing, defence, energy, engineering, security and medicine. As a result, a key feature of the CDT will be a developed awareness in its student cohorts of the breadth of opportunity available and the confidence that they can make strong impact thereon.

This proposal brings together a group of leading multidisciplinary teams in medical, chemical, metabolic, statistical and computational sciences from across Imperial College London (ICL, lead institution) and its partners. These include the Institute of Cancer Research, the European Molecular Biology Laboratory-European Bioinformatics Institute, the Universities of Oxford, Swansea and Nottingham, and the MRC Clinical Sciences Centre and MRC Human Nutrition Research Centre, supported by strong partnerships and collaborative links with industry, the NHS and the National Institute for Health Research funded Biomedical Research Centres and Units. The proposal seeks support to build a DEDICATED INFRASTRUCTURE in data storage, aggregation, analysis and visualisation of diverse types of biomedical data. These come from standard clinical sources through to different types of information including from genetic analysis, and metabolic information, that help us to define patients or people studied in the general population using a holistic "systems medicine" framework. The GLOBAL AIM is to make major advances in understanding the causes and reasons for disease progression of common human diseases such as cancer, cardiovascular disease, respiratory disease and metabolic disorders such as type 2 diabetes and obesity. In this way we aim to create new disease diagnostics and prognostics aimed at the individual patient ("stratified medicine") through innovations in medical bioinformatics with powerful computing capability. The programme will create unprecedented capacity to i) DEVELOP powerful new approaches for computation and analysis of large-scale, complex, multi-source medical data; ii) INTEGRATE information linking multiple different types of biological information from analysis of blood and urine samples (e.g., metabolic, genomic, analysis of the microbial genome) to different diseases, disease progression and outcomes; hence to iii) help UNDERSTAND the causes and mechanisms of disease and improve individual disease classification for better patient treatments and safety; also to iv) TRANSFORM the training of the biomedical researchers of the future through creation of a seamless interdisciplinary environment spanning biomedicine, physical sciences, computing and engineering. In particular we will capitalise on computational expertise that has led to the development of a partnership in medical information infrastructure and service between universities and the pharmaceutical industry called eTRIKS, and related software platforms such as tranSMART, an "open source" solution for managing data and research knowledge in clinical studies. We also have world-leading expertise in metabolic "fingerprinting" and systems medicine approaches manifested in the MRC-NIHR National Phenome Centre located at ICL, and underpinned by excellence in genomics, computational sciences and advanced data modelling and visualisation. This project has a very broad collaboration with industrial sectors including major pharmaceutical companies, instrument vendors, IT and informatics companies. Our project covers the complete healthcare envelope of data generating activity and analysis from the level of basic measurement sciences through to the understanding of gene-environment interactions and disease mechanisms to the creation of knowledge systems for better clinical decision making based on detailed knowledge of individual patient biology. This application is strengthened by the decision of ICL to establish a major interdisciplinary centre for 'big data' at the new Imperial West campus, ensuring sustainability over the longer term. The project aims to deliver top class science, a robust informatics platform and in-depth scientific data and knowledge to contribute to the state of the art of UK and international medical research.

Soft image sensors are expected to take vital roles in our future daily life. They can monitor the physiological information of our body to provide real-time, noninvasive medical diagnostics, as well as capture and share photos, videos via wireless communications. However, current image sensing electronics cannot be integrated easily into humans, because they are made of rigid semiconductor photodetectors and integrated with optical filters for colour discrimination. In addition, the use of filter creates additional requirements on the optical path difference, which confines the foldability and limits the resolution of the detector array. To overcome these technological limitations, filterless foldable photodetectors which only detect light within a specific wavelength have emerged as critical elements for building soft image sensors. Colloidal quantum dots, metal halide perovskite and organic photodetectors have shown excellent flexibility and detectivity. However, their broad light absorption means filters need to be added to make them specific to a certain colour of light. So far, the most successful filterless model is based on charge collection narrowing (CCN) photodiodes, which are semiconductor devices that convert the specific colour of light into an electrical current. However, since the narrowband response is delivered by controlling photogenerated charge collection efficiency, micrometres thickness junction is often required, which results in an array with a greater likelihood of interpixel cross-talk and frequency bandwidth limitations. It has been demonstrated that the junction thickness can be reduced by using high reflectivity cavities, but a number of challenges still remain. In this research, we aim to tackle these challenges to help find suitable semiconductors that use non-toxic elements and are able to efficiently detect light within a specific wavelength of interest at thicknesses as little as few hundred nanometres. If successful, we would be moving a step closer to an eco-friendly soft image sensor with the potential for many applications. Among all incarnations of solution-processed semiconductors, the recently discovered two-dimensionally (2D) Colloidal Quantum Wells (CQWs) are highly promising for soft image sensor applications, not only do they offer high colour purity with ultranarrow full-width at half-maximum (FWHM) but they also exhibit excellent compatibility with flexible electronics, such as unique stretching enhanced optical polarisation. Unlike colloidal quantum dots, CQW ensembles have no inhomogeneous broadening due to an atomically-precise definition of the short axis and is the reason why CQWs exhibit the narrowest ensemble absorption and emission spectrum of any solution-processed material reported to date. However, looming over much of this success is the fact that all the reported CQWs include toxic heavy metals (e.g., cadmium and lead), and little progress has been made on the fabrication of non-toxic CQWs or CQW narrowband photodetectors. This proposal is therefore designed to substantially address this challenge by using non-toxic mechanically stretchable 2D solution-processed CQWs for the fabrication of soft image sensors. This proposal starts from the growth and surface functionalisation of non-toxic CQWs followed by predictions of the new cavity and charge transport layers for fast CCN. The proposed work will consider the key factors limiting frequency bandwidth, and will demonstrate the inkjet printing of multi-coloured CCN-based photodiodes in a soft image sensor scenario. The high impact objective of this project is the demonstration of a CQWs image sensor which is stretchable and mechanically conformable. This proposal will be underpinned from the established compound semiconductor research expertise at Cardiff University, in close collaboration with Oxford, Cambridge and Bristol University, TCL Corporate Research, Huawei UK, Glaia, 99P Recycling and Hamamatsu UK.

This is a proposal for advanced crystal growth equipment to enable the UK to take a lead in important areas of Quantum Technologies. It will enable the growth of nanometre-scale semiconductor quantum dots with world-leading properties. These properties include emission limited only by fundamental properties of the dots unaffected by the surrounding environment, and ordered arrays of dots, critical to enable scale-up and to translate the much excellent science of quantum dots to highly competitive Quantum Technologies. The Quantum Technology applications rely on purely quantum mechanical principles such as superposition, where a system can be in two states at the same time, and entanglement where an operation at one spatial location influences another remotely, without there being any direct connection between them. Quantum dots are extremely well suited to exploiting these quantum mechanical effects (sometimes termed 'Quantum 2'). The favourable properties of III-V semiconductor quantum dots include on-demand single and entangled photon emission, ready incorporation in cavities, very long coherence and compatibility with well-developed III-V semiconductor processing technology. III-V semiconductors are familiar in everyday life as the basis of light emitting diodes, internet data transmission, and laser disk storage to name just a few. Here we turn the favourable III-V properties to enable new applications in Quantum Technologies, including as sources for secure Quantum Cryptography, quantum relays for Quantum Communications, integrated entangled sources for Quantum Cryptography and sensing, and longer-term opportunities for memories and spin chains for Quantum Networks. The crystal growth equipment, an Epitaxy Cluster Tool, is comprised of two principal chambers, one dedicated solely to the growth of highest quality quantum dots, and the second to the advanced processing of structured templates for growth of arrays of dots with pre-determined location, enabling the realisation of very high brightness sources of single photons and of arrays essential for scale-up. The two principal chambers will be connected together by an automated loading, transfer and analysis chamber, enabling high throughput of the system, and furthermore ensuring that only highest cleanliness wafers are transferred to the ultrahigh purity chamber. The Cluster Tool constitutes an integrated suite of growth, analysis and processing features. It will provide the UK with unique experimental infrastructure to take a leading position in the translation of quantum-dot-based science into Quantum Technologies.

We propose the development of a new technology for Non-Invasive Single Neuron Electrical Monitoring (NISNEM). Current non-invasive neuroimaging techniques including electroencephalography (EEG), magnetoencephalography (MEG) or functional magnetic resonance imaging (fMRI) provide indirect measures of the activity of large populations of neurons in the brain. However, it is becoming apparent that information at the single neuron level may be critical for understanding, diagnosing, and treating increasingly prevalent neurological conditions, such as stroke and dementia. Current methods to record single neuron activity are invasive - they require surgical implants. Implanted electrodes risk damage to the neural tissue and/or foreign body reaction that limit long-term stability. Understandably, this approach is not chosen by many patients; in fact, implanted electrode technologies are limited to animal preparations or tests on a handful of patients worldwide. Measuring single neuron activity non-invasively will transform how neurological conditions are diagnosed, monitored, and treated as well as pave the way for the broad adoption of neurotechnologies in healthcare. We propose the development of NISNEM by pushing frontier engineering research in electrode technology, ultra-low-noise electronics, and advanced signal processing, iteratively validated during extensive tests in pre-clinical trials. We will design and manufacture arrays of dry electrodes to be mounted on the skin with an ultra-high density of recording points. By aggressive miniaturization, we will develop microelectronics chips to record from thousands of channels with beyond state-of-art noise performance. We will devise breakthrough developments in unsupervised blind source identification of the activity of tens to hundreds of neurons from tens of thousands of recordings. This research will be supported by iterative pre-clinical studies in humans and animals, which will be essential for defining requirements and refining designs. We intend to demonstrate the feasibility of the NISNEM technology and its potential to become a routine clinical tool that transforms all aspects of healthcare. In particular, we expect it to drastically improve how neurological diseases are managed. Given that they are a massive burden and limit the quality of life of millions of patients and their families, the impact of NISNEM could be almost unprecedented. We envision the NISNEM technology to be adopted on a routine clinical basis for: 1) diagnostics (epilepsy, tremor, dementia); 2) monitoring (stroke, spinal cord injury, ageing); 3) intervention (closed-loop modulation of brain activity); 4) advancing our understanding of the nervous system (identifying pathological changes); and 5) development of neural interfaces for communication (Brain-Computer Interfaces for locked-in patients), control of (neuro)prosthetics, or replacement of a "missing sense" (e.g., auditory prosthetics). Moreover, by accurately detecting the patient's intent, this technology could be used to drive neural plasticity -the brain's ability to reorganize itself-, potentially enabling cures for currently incurable disorders such as stroke, spinal cord injury, or Parkinson's disease. NISNEM also provides the opportunity to extend treatment from the hospital to the home. For example, rehabilitation after a stroke occurs mainly in hospitals and for a limited period of time; home rehabilitation is absent. NISNEM could provide continuous rehabilitation at home through the use of therapeutic technologies. The neural engineering, neuroscience and clinical neurology communities will all greatly benefit from this radically new perspective and complementary knowledge base. NISNEM will foster a revolution in neurosciences and neurotechnology, strongly impacting these large academic communities and the clinical sector. Even more importantly, if successful, it will improve the life of millions of patients and their relatives