• Canada
• 2013-2022close
• UK Research and Innovation close
• UKRI|EPSRC close
• 2015 close
• OA Publications Mandate: No close

Material innovations focussing on delivery and sustainability are key as our global efforts intensify in the development of a secure and sustainable future energy landscape. Many infrastructure-related material challenges have emerged as a result of the need (i) to explore offshore marine environments for wind power generation, (ii) for deeper and more complex underground wellbore systems for new oil & gas explorations, (iii) for robust containment and shielding structures for new nuclear power plants and (iv) for larger dam structures for future hydropower generation. Our vision for this proposal is to build a world leading and long lasting partnership between academics in the UK and China, integrated with industrial partners and other world leading academic groups around the world, to collectively address some of those construction material challenges with a focus on sustainability. The commonality in the assembled group is our interest and expertise in exploring potentials for magnesia-bearing construction materials in solving some of those new challenges, by either providing completely new solutions or enhanced solutions to existing material systems. This is a unique area to China and the UK where there is significant complementary expertise in the different grades of and applications for magnesia. The project consortium from the University of Cambridge, University College London, Chongqing University and Nanjing Tech University has the required interdisciplinary mix of materials, structural and geotechnical engineers, with world leading unique expertise in magnesia-based construction materials. The intention is to share and advance our global understanding of the performance of those proposed materials, road map future research and commercial needs and identify the ideal applications in our future energy infrastructures where most performance impact and sustainability benefits can be achieved. The proposed focusses two main areas of research. The first is the technical advantages and benefits that magnesia can provide to existing cement systems. This includes (i) its use as an expansive additive for large mass concrete constructions e.g. dams and nuclear installations, (ii) its role in magnesium phosphate cements for the developing of low pH cements suitable for nuclear waste applications and (iii) its role in advancing the development of alkali activated cements by providing low shrinkage and corrosion resistance. The second is the delivery of sustainable MgO production processes that focus on the use of both mineral and reject brine resources. An integral part of this project will be the knowledge transfer activities and collaboration with industry and other relevant research centres around the world. An overarching aspect of the proposed research is the mapping out of the team's capabilities and the integration of expertise and personnel exchange to ensure maximum impact. This will ensure that the research is at the forefront of the global pursuit for a sustainable future energy infrastructure and will ensure that maximum impact is achieved. The consortium plans to act as a global hub to provide a national and international platform for facilitating dialogue and collaboration to enhance the global knowledge economy.

There is mounting evidence that deficits in saccadic and smooth pursuit eye movements are characteristic of dementia. These deficits can be detected in a lab or clinical setting using specialised eye-tracking equipment but this is inconvenient for the patient, costly for the NHS and introduces the risk of sampling bias because clinic visits are inevitably intermittent. The aim of the Monitoring Of Dementia using Eye Movements (MODEM) project is to enable the longitudinal collection of data at low cost and with minimal inconvenience, to provide a novel platform for prognosis and diagnosis of dementia. We propose to tackle monitoring of disease progression with in-home eye tracking and computational analysis of eye movement embedded with patients' everyday activity. This is an entirely novel approach, and hence high risk. However, it has the potential to lead to major breakthroughs, for three reasons: (i) Eye movement and cognitive health are closely linked, including initial evidence of markers for dementia diagnosis. (ii) Eye trackers are on the verge of a step change from lab instrument to widely deployed sensor, and their adoption for contact-less health monitoring is becoming a realistic proposition. (iii) People/patients use their eyes in daily routines that are visually engaging, and that present rich contexts for collection of information about how their eye movement changes over time, as a function of disease progression. Our vision is that rather than patients having to attend a clinic or laboratory, eye movement data can be collected in settings where the technology is ambient and peoples' behaviour is relaxed and natural. The target settings are peoples' own homes and care homes. Eye trackers can be placed strategically to observe eye movement in the context of everyday tasks. For example they can be used to track hand-eye coordination in routine tasks such as tea-making for possible signs of change; these might signal cognitive decline long before routines become more obviously affected. Eye trackers can also be deployed interactively. People spend significant amounts of their daily lives as consumers of visual media, especially through TV, which affords interactive stimulation of eye movement. For example, content (e.g. TV programmes) can be designed to elicit behaviours of interest for diagnosis. People can also be provided with active gaze controls for interaction, for instance as alternative to remote control functions of a TV. Use of gaze for control stimulates specific eye movements which can be used for testing. Though beyond the scope project, this could also lead to therapeutic application of the technology. Moreover, as eye trackers are based on cameras and computer vision, this opens up avenues for integration with other vision-based approaches such as analysis of facial expressions, for multimodal cognitive health analysis.

VISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.

The proposed research contributes to fundamental topics in Combinatorial Optimisation, aiming to devise strongly polynomial algorithms for new classes of linear and nonlinear optimisation problems. The notion of polynomial-time complexity, introduced in the 1970s, is a standard way to capture computational efficiency of a wide variety of algorithms. Strongly polynomial-time algorithms give a natural strengthening of this notion: the number of arithmetic operations should not depend on numerical parameters such as costs or capacities in the problem description, but only on the number of such parameters. Strongly polynomial algorithms are known for many important optimisation problems. However, it remains an outstanding open problem to devise such an algorithm for a very fundamental optimisation problem: Linear Programming. The most important goal of the proposal is to develop a strongly polynomial algorithm for linear programs with at most two nonzero entries per column. The problem is equivalent to minimum-cost generalised flows, a classical model in the theory of network flows. Finding a strongly polynomial algorithm was a longstanding open question even for the special case of flow maximisation, resolved by the applicant in a recent paper. Further goals of the proposal include strongly polynomial algorithms for related nonlinear optimisation problems. Nonlinear convex network flow models have important applications for market equilibrium computation in mathematical economics. Very few nonlinear problems are known to admit strongly polynomial algorithms. The proposal aims for a systematic study of such problems, and will also contribute to the understanding of computational aspects of market equilibrium models.

Condensed matter physics has developed a relatively complete theory of common phases in materials leading to many technologically important devices including electronic screens, memory storage, and switching devices. Landau, or mean-field theory, has provided a framework to model, predict, and understand phases and transitions in a surprisingly diverse variety of materials and also dynamical systems. While these conventional ground states have proven technologically important and the underlying theory represents a major success for scientists, these phases have proven incredibly difficult to suppress and often emerge when new materials properties are sought or engineered. To discover novel phases that will lead to a new materials revolution, these common phases need to be suppressed to allow exotic and unconventional properties to emerge. The most common vehicle to turn off conventional phases in materials has been through the introduction of disorder through chemical doping resulting in strong random fields. Many important theories have been formulated and tested to describe the effects of random fields and in particular to account for the fine balance between surface and bulk free energy. However, the use of disorder has proved limiting as properties are often templated into the material and not directly controllable and also the resulting ground state of the material is difficult to understand. Another route, which has more recently been explored in the last decade, to suppress conventional phases is by introducing strong fluctuations. While this can be trivially done with temperature, new phases have emerged by studying quantum systems where the physics are governed by quantum mechanics and the Heisenberg uncertainty principle. The study of quantum systems has resulted in the discovery of many new phases of matter including high temperature superconductors and also quantum spin-liquids where the magnetism is dynamic at any temperature. A limitation of quantum fluctuations is that the properties do not carry over directly to ferroelectric based systems and also multiferroics where magnetic and structural properties are strongly coupled. Also, owing to the strong fluctuating nature of the ground state, the properties have not been found to be easily tunable limiting immediate use for applications. This proposal aims to therefore take a different route by studying classically frustrated systems where a large ground state degeneracy is introduced naturally through the lattice and quantum mechanical effects are small. Emphasis will be placed on lattices based upon a triangular geometry. The lack of strong fluctuations (that exists in quantum systems) provides the ability to controllably tune between different ground states making this route a potential means of creating new switching devices or novel memory storage systems. The proposal aims to investigate classically frustrated magnets and ferroelectrics. These systems can be described within a common framework and will be studied using scattering techniques to provide a bulk real space image of the ground state. The properties will be tuned with magnetic and electric fields supplying a direct route for discovering a new route towards technologically applicable materials. The combined approach of investigating ferroelectrics and magnets will result in a complete understanding applicable to immediate industrial applications. These new materials will lead to the discovery of new phases including new high temperature multiferroics, classical spin liquids, or localized controllable boundaries or defects.

The global demand for smaller and more energy efficient devices has been sustained by a steady decrease in the scale on which silicon microelectronics can be manufactured, from 65nm processes in the mid 2000s to 14nm in the very latest Intel processors. To continue this trend beyond the mid 2020s devices with dimensions of just 1-2nm will be required, likely using alternatives to silicon. In this regime, the cross section of a wire might be no more than 2x2 or 3x3 atoms across, where the relevant materials physics is dominated by surface and confinement effects leading to dramatically different structural and electronic properties to the corresponding bulk material. Such wires can be formed by crystallisation of a molten salt within carbon nanotubes (CNTs) of "Buckytubes", leading to the smallest cross section nano crystals possible, sometimes referred to as Feynman crystals. Research into the fundamental materials physics of these CNT-encapsulated structures is still in its infancy, with UK experimentalists leading the way. Particularly exciting recent work by one of the applicants (Sloan) has demonstrated the possibility of these wires undergoing transitions between nano-crystalline structures with markedly different properties, in response to bending strain in the CNT. These "phase change" properties open the way for nanoscale electromechanical switches and non-volatile memory, as well as providing a playground for fundamental studies of phase changes at the smallest length scale possible in a material. Our aim with the current project, inspired by these results, is to develop a computational modelling capability to aid in interpretation of experiments, understand the origin of the phase change behaviour, and guide our experimental colleagues toward compounds with potentially advantageous properties. Counterintuitively, due to a reduction in symmetry, the computational expense of simulating nanowires can be more demanding when compared to bulk crystals. We will address the limitations of currently available modelling tools when applied to these systems. This will involve significant modifications to existing software and a rigorous study of the various approximations one might employ to increase the tractability of simulations. We will apply cutting-edge methods in structure prediction to these systems, a non-trivial exercise due to the possibility wires with non-crystalline (e.g. helical) symmetry, and connect directly to relevant experiments by computing spectra related to the encapsulated wire's electronic and vibrational properties. Finally, we will study the thermodynamics and kinetics of nano-crystalline phase change, developing an understanding of when and how rapidly structural changes are affected to assess the utility of this mechanism for device applications.