The aim of this project is to investigate a new technique, using a unique sensor technology - the Electric Potential (EP) Sensor, invented at Sussex, for the measurement of electric field activity related to the build-up of stress in geological and man-made materials. This will result in a sensor design and the fabrication of a batch of EP sensors, capable of coupling to the electric field produced in a representative selection of rock and concrete samples. Choice of material and testing regimes will be advised from project partners and collaborators. The EP sensors will be used concurrently with strain gauges and acoustic emission sensors in bespoke acquisition and analysis instrumentation. Project partner, British Geological Survey (BGS), has committed the in-kind use of a state-of-the-art rock mechanics laboratory for all stress testing programmes. The sensor instrumentation system will correlate EP sensor outputs with stress and internal damage processes occurring in samples subjected to the rock testing system. The correlated EP sensor output is referred to as E-Stress. There is conclusive evidence that supports the existence of electrical activity in stressed rock and concrete however, the measurements made to date, by other workers, are of weak current signals at the pico to micro Amp level, a difficult measurement even in a laboratory environment. There is also evidence that various materials exhibit pre-fracture signal activity which can be of great importance to structural health and geoscience. The investigator has already published preliminary results that identify large (Volts) electric pre-fracture signals in a range of rock samples. This combination of a large available signal, an appropriate sensor, and expertise in the application of the technology, presents a unique opportunity with specific expert partners to develop a new measurement tool with predictive capability and insight to internal processes. To achieve these objectives the work packages will be: WP1 - Initial planning meetings, consultations with BGS and Arup in materials to test. Trial tests at BGS for familiarisation and sensor instrument planning. WP2 - Develop an EP sensor design capable of detecting electric field in both rock and concrete samples. The investigator has experience in applying EP sensors to couple to the electric signals produced in the diversity of rock and concrete under stress. The sensors will be integrated with strain gauge and an acoustic emissions system into one portable instrument using a high quality data acquisition and processing system. This system will also require work on software analysis of the signals for correlation. WP3 - The application of the EP sensor and instrumentation within a rigorous material testing regime to destruction at BGS. Three testing programmes will be refined in consultation with partners and all data recorded to storage systems. WP4 - Analysis and correlation to calibrate EP sensor as an E-Stress instrument for use in research and industry. Results will be disseminated and presented to international conferences and industry networks. Work will conclude by exploring the commercial opportunities with technology licensee, Plessey Semiconductors to fabricate custom sensors. The work is novel and timely since the investigator's preliminary publication and interest from BGS. The results will be of direct interest to the project partners: Arup, for structural health monitoring (SHM) of civil infrastructure and to BGS, as a tool for monitoring natural hazards caused by rock fracture or slippage. There is a route to commercialisation through the support of Plessey Semiconductors.

The Wearable Computing market is expected to explode, as evidenced in 2014 and early 2015 with a plethora of new products primarily in the sports and fitness domain. Business Insider in 2013 estimated that 300 million units would be shipped by 2018. What makes wearables (and similarly mobile phones) unique is their contextual intelligence: they use sensors to infer users' context, such as location, activities or social interactions. This contextual intelligence allows a fitness tracker to detect by itself that the user is running, walking, or doing push-ups. We are motivated by the vision of pervasive "wearable smart assistants" that provide situated contextual support in daily life. They may act as "memory reminders" for people with dementia, or encourage healthy behaviours through supportive prompts presented at the right time (e.g. to fight obesity, diabetes, cardiovascular diseases). This project deals with the heart of any such assistive technology: the ability to recognise general human activities and context from sensors. Current methods can only recognise pre-defined or "closed sets" set of activities and context. This is insufficient for the scenarios outlined above. In such applications, the set of relevant activities is not necessarily known at design-time, as different users tend to have different routines, routines may change as users change interests, and activities may be performed differently, for instance after an injury. Therefore the set of relevant activities and contexts is potentially unbounded and is said to be "open-ended The project investigates the methods required to recognise an "open-ended" set of activities and contexts from existing wearables, such as a smartwatch and a mobile phone, following lifelong learning principles. In other words, the system should discover that a user engages in a new activity, even if it was not initially programmed with the knowledge of that activity. We develop new open-ended learning techniques that can model changing number of classes at runtime. These methods run on a recognition infrastructure comprising software on the wearable devices and on a server. The infrastructure will be made open-source to benefit other projects. We develop methods that discover reoccurring wearable sensor patterns. Repeating patterns may correspond to new activities or contexts. Therefore they are modelled using open-ended learning techniques. Finally, we develop methods to decide whether a discovered pattern is meaningful and what it represents. This is achieved by involving the user and occasionally requesting to provide information about his/her current activity. We compare different feedback options that minimise the number of interruptions and the complexity of the queries. Overall, the system is evaluated on existing data as well as on a new long-term dataset collected within this project. Our approach is novel and timely. Performance increases in activity recognition are incremental and the inability to deal with unknown activities is most critical for large-scale deployments in daily life scenarios. This project addresses this fundamental limit. This is timely given raising costs of healthcare and calls to rely on technology to address this issue. The outcomes of this project along understanding daily human behaviour may lead to new smart assistants that could help support independent living or assist users in following healthy behaviour change. The outcomes may also find their use in psychology research and in the area of sustainable innovation, such as the assessment of consumer-product interaction and behaviour change initiatives. As such the project has clear societal benefits. This project is supported by our partners Unilever and Plessey Semiconductors, respectively interested in consumer behaviour research and new products in the healthcare domain.

Gallium Nitride (GaN) based optoelectronic devices have the potential to revolutionise our society. They are more efficient and more robust than the alternative device technologies used today and therefore last longer and deliver significant energy savings. For example, GaN LEDs can be used to replace compact fluorescent and incandescent light bulbs in our homes and places of work. Such LED light bulbs have the potential to reduce by up to 50% the energy we use for lighting. Since about 20% of all the electricity we generate is used for lighting applications this would save the equivalent of about 8 power stations worth of electricity in the UK each year. Another, potentially even larger area where Gallium Nitride could have a significant impact is power electronics. Power electronic devices are found in electric cars, power supplies for laptop, and the control systems for mains electricity. Since GaN power electronics can handle more power, operate at higher voltages and are again significantly more efficient than other semiconductor technologies, it is estimated that by switching to GaN power electronics it may be possible to save up to £1 trillion each year in global energy costs. From these examples it is clear that GaN devices can significantly help to reduce our demand for energy and therefore our Carbon footprint. However, for this potential to be realised, research still needs to be done to deliver the promised performance of these devices and to reduce their manufacturing cost so that they are widely accepted. Production of semiconductor devices involves the manufacture of thousands or even millions of devices simultaneously on a circular wafer. One of the developments which has allowed the low cost and pervasive nature of Silicon electronics today are the economies of scale that can be achieved when large diameter wafer are used. A key step therefore in the manufacturing of low cost GaN devices is the development of high quality GaN layers grown onto large diameter Silicon wafers. This will allow the high volume production techniques that have been developed for the Silicon electronics industry to be applied for GaN devices reducing their cost by up to 80%. Research carried out in this fellowship will provide new knowledge about how to grow and control GaN device layers. This will allow the promise of these devices to be realised enabling higher efficiencies, new applications and growth on large diameter Silicon substrates (upto 200mm). By carrying out this research in close collaboration with UK industry, the developments will be focused towards real products and address some of the real world challenges associated with delivering high performance and reliable devices. This will also ensure that the research supports the developing GaN device manufacturing base in the UK and can contribute to the commercial exploitation of GaN technology.

When manufacturing any kind of electronic device, patterning is required to achieve small features, such as different regions of materials with different functions. The ever-increasing complexity of modern electronics and photonics has led to a plethora of approaches to substrate patterning. For each of these approaches, there are always compromises between the speed of patterning (write speed), the minimum feature size, versatility and cost. The most dominant patterning process in electronics and photonics manufacturing is mask-based photolithography. Here, the chip to be patterned is coated with a light-sensitive material known as a "resist," and light is shone onto the resist through a mask with deliberately placed holes. Light that passes through the holes causes a chemical change in the resist, and thus the pattern is transferred from the mask onto the chip. The disadvantage is that each photolithography mask is only suitable for a one particular type of chip design and cannot be reconfigured for the manufacture of other chip designs, and mask design and fabrication is time-consuming and costly. Alternative patterning techniques, known as direct-write lithography, do enable great flexibility in device design, but at the expense of slow patterning speeds, and often large capital and operating costs. Here, we propose a novel process for photolithography, which we name holographic multi-beam interference lithography (HMBIL). HMBIL promises large area patterning with sub-wavelength resolution as well as fast write speeds, short development times, low costs and a dynamically reconfigurable choice of exposure pattern. Using HMBIL, we will demonstrate patterning of arbitrarily-shaped 100 nm feature sizes over large areas with high throughput (>25 cm^2 device area in under 1 hour), which is currently unachievable with direct-write lithography techniques. As a proof-of-principle, we will demonstrate the capability of HMBIL for manufacturing an example device structure: multispectral filter arrays. These filter arrays, when integrated with an image sensor, will allow the acquisition of light spectra for applications as diverse as medical imaging to remote sensing. HMBIL manufacture of multispectral filter arrays will open up a range of avenues for custom detectors and imaging sensors for security, industrial or medical applications. We envisage this versatile new HMBIL process primarily in two locations in the manufacturing chain: Firstly, as a means of rapid prototyping of nanofabricated designs and secondly, as a means of large scale production of individually customised components. This will revolutionise manufacturing processes across a broad range of application areas including miniaturised optoelectronics, versatile point-of-care diagnostic devices, displays and image sensors, on-chip photonics (waveguides and photonic crystals), plasmonics, nano/micro-electromechanical machines, microfluidics, embedded systems and the internet of things, and many more.

AlGaN/GaN high electron mobility transistors (HEMT) are a key enabling technology for future power conditioning applications in the low carbon economy, and for high efficiency military and civilian, microwave and RF systems. Although the performance of AlGaN/GaN HEMTs presently reaches RF powers up to 40W/mm, at frequencies exceeding 300 GHz, their long-term reliability, often thermally limited, is still a serious issue, in the UK & Europe, but also in the USA & Japan. Corresponding challenges exist for power conditioning applications. To mitigate the present thermal device challenges, the aim of this proposal is innovation and step change in thermal management of AlGaN/GaN HEMT devices by developing novel substrates, in particular (1) high value substrates that have higher heat extraction capability than high cost SiC substrates commonly used for GaN RF applications, and (2) low cost substrates that have improved heat extraction capability to GaN-on-Si substrates for more cost sensitive power electronics markets. The resulting step-change in improvement in heat spreading will improve reliability, circuit efficiency and ease system constraints of GaN electronics. To enable the optimization of the thermal substrate properties key enabling new thermal analysis technologies will be developed. The UK has roadmaps for employing RF and microwave GaN electronics in defence as well as satellite communication. The key UK industrial players in this field include Selex, MBDA, Astrium & others, all requiring reliable and efficient GaN RF and microwave electronics, which the proposed work will advance and enable via the new heat extracting substrate technologies and improved methods of thermal characterisation, furthermore with opportunities for IQE UK, supporter of this proposal, of being a key component in the supply chain for RF GaN applications. The corresponding roadmap for power electronics requires cost-effective GaN presently on Si substrates power devices with UK based manufacture at NXP, supporter of this project, and International Rectifier (IR) which the outcome of this proposed work can innovate. Further business opportunities will emerge with the substrate development itself, such as via Element-6, at IQE through the developments of III-Nitride epitaxial growth for best heat extraction, or spin-out companies. Dissemination of results and insights from this project will be via publications in internationally leading journals, via conferences, via the UK Nitrides Consortium, i.e., established dissemination routes will be used to transfer knowledge into academia, and directly with the industrial supporters of this project, as well as other companies Bristol and Bath have links to (e.g. Selex, MBDA). The CDTR in Bristol and the III-Nitride group in Bath have both a strong track record in being successful using these dissemination routes, in particular with companies. The field of thermal management of semiconductor devices is an important academic research field, and is especially topical and useful at the current stage of implementation of this genuinely disruptive technology. It not only trains UK workforce for industry, but also it is essential to help maintain the present high level of device physics and engineering in the UK. It provides stimulus for an efficient interaction between universities and industry to maximize benefit of EPSRC research investment. This includes in this project interaction with UK industry, in particular, IQE, NXP, and Plessey in this project.