In any electrical device, unwanted heat produced by electronic components is usually wasted. A thermoelectric device can convert this waste heat to electricity through Seebeck effect. Generation of electricity from heat via the Seebeck effect is silent, environmentally friendly and requires no moving parts. Unfortunately current thermoelectric materials are difficult to process, have limited global supply and are not sufficiently efficient to meet the requirements of current energy demands. That is why there is a world-wide race to develop materials with a high thermoelectric efficiency. To realise a high-performance thermoelectric material, both electron and phonon transport should be optimised. Since both electrons and phonons (vibrations) behave like waves, they can exhibit interference phenomena at a molecular scale, which could be used to optimise their transport properties. Therefore simultaneous control of room-temperature quantum interference (RTQI) of electrons and room-temperature phonon interference (RTPI) have the potential to underpin new design strategies for efficient molecular thermoelectricity. This proposal, entitled 'MoQPI,' aims to design new highly-efficient thermoelectric materials for converting waste heat into electricity, by exploiting RTQI and RTPI in cross-plane (CP) sub-10nm thin films. Cross-plane structures are advantageous, because they do not suffer parallel heat paths through the substrate and can be engineered to suppress parasitic thermal conductance due to phonons. The radically-new CP nanostructured materials proposed in this Fellowship will be formed from single-molecules, parallel arrays of molecules in self-assembled monolayers (SAMs) and van-der-Waals (vdW) molecular nanoribbons sandwiched between metallic and/or graphene electrodes. I will exploit RTQI and RTPI simultaneously in many molecule systems and vdW molecular nanoribbons to yield a new generation of high-performance thermoelectric materials. Simultaneous assessment of quantum and phonon interference in molecular-scale thermoelectric materials will elucidate design strategies for the development of new generation of thermoelectric devices and consequently will change the community view on routes to engineer and realize highly efficient thermoelectric materials. MoQPI will also develop innovative applications of the Seebeck effect for discriminating biological sensing. Using the Seebeck coefficient for sensing is advantageous compared with current methods based on electrical sensing, because two biological species that might possess similar conductances could have Seebeck coefficients with different signs or magnitudes. Furthermore, the electrical conductances of biomolecules such as DNA nucleobases are extremely low, which is problematic for conductance-based sensing, but advantageous for Seebeck sensing, since low electrical conductances typically lead to high Seebeck coefficients. Seebeck sensing using single molecules and molecular nanoribbons proposed in this proposal will generate ground-breaking knowledge needed for next-generation biosensing. MoQPI will also explore hybrid molecular structures for energy harvesting. The identification of simultaneous RTPI and RTQI enhanced energy harvesting and molecular sensing in ultra-thin-film molecular layers is the first step to realise new types of quantum technologies with important societal and economic impacts in the real world.

Our concern in this proposal is for Base of the Pyramid (BoP) users, that is, those who are the most socio-economically disadvantaged. For these communities, there are several challenges to the digital utopia that governments and industry are regularly heralding. These range from low technological and textual literacy, a paucity of relevant, appropriate content, to a lack of affordable, high-bandwidth data connections. With the ubiquity of mobile phones, it is clear that now, and in the future, these platforms will be the most influential ICT solutions for these users in the poorest regions of the world. Understandably, a good proportion of the work in Human Computer Interaction for Development (HCI4D) and ICT for Development (ICTD) has focused on the technologically lowest common denominators - for example "dumbphones" and "feature" phones, the precursors to smartphones - to reach as many people as possible. In contrast, this proposal addresses the need to look ahead to a future that promises widespread availability of increasingly sophisticated devices. The most likely future in the next 5-10 years is that BoP users will have access to handsets that developed world users are now taking for granted. This trend is exemplified by the affordability of so-called "low-end smartphones." The GSMA - the global industry body for mobile service providers, one of our partners in this project - predicts that this trend will continue worldwide, with these devices already retailing for as little as £30. These devices are equipped with rich sets of sensors, connectivity facilities and output channels (from audio-visual to touch-output). While there is plentiful research on how to use and extend these platforms for more "natural" interaction (e.g., creating mobile pointing and gestural interfaces), the work has largely been from a "first world" perspective. That is, the techniques have been designed to fit a future, in terms of resource availability, cultural practice and literacy, that is out of joint with that lying ahead for BoP users. Our aim is to radically innovate for key future interaction opportunities, drawing on a network of organisations and individuals deeply connected to BoP users, along with BoP end-users themselves. These stakeholders have helped shape the proposal and will be integral to the work itself. The programme will be comprehensive and integrative, involving three driver regions in Kenya, South Africa and India, each allowing us to consider needs from three perspectives: the urban, sub-urban and rural. In solving pressing problems of effective interaction for BoP users we will also seek new basis premises of HCI design in the wider developed world. In our view, the established information interaction techniques (like copy/paste) derive from desktop, textual and knowledge work framings of interaction. Mobile interaction articulates an alternative framework - sociality, personal narrative and highly context orientated practices of friendship, family and community. With the emergence of smartphones and their remarkable processing powers, the temptation to make them mini-PCs, with all the interaction principles to match, has led many HCI researchers to avoid designing for those social practices, blurring the distinction between the mobile and the PC. Given that most of those who have access to these devices are living in cultures where knowledge work is the norm, this tends to be accepted - sociality is often achieved through by-passing the device and engaging with 'apps.' The "living lab'' of our BoP communities, where exposure to and suitability of desktop UIs is very low, provides an exciting resource that draws attention to how users seek to appropriate mobile devices for social ends in and through the device itself. This in turn can provide the basis for uncovering new better basic and innovative HCI principles that can allow these ends to be more readily achieved.

We, human beings, acquire information from our surroundings through our sensory receptors of vision, sound, smell, touch and taste -the five senses. The sensory stimulus is converted to electrical signals as nerve impulse data communicated with our brain. What is really intriguing is the communication network. When one or more senses fail (impairment), we are able to reestablish communication and improve our other senses to protect us from incoming dangers. Furthermore, we have developed the mechanism of "reasoning", effectively analyzing the present data and generating a vision of the future, which we might call our 6th Sense (6S). Is it possible to develop a 6S technology to predict a catastrophic disaster? Industrial processes are already equipped with five senses: "hearing" from acoustic sensors, "smelling" from gas and liquid sensors, "seeing" from camera, "touching" from vibration sensors and "tasting" from composition monitors. 6S could be achieved by forming a sensing network which is self-adaptive and self-repairing, carrying out deep-thinking analysis with even limited data, and predicting the sequence of events via integrated system modelling. This project is the first step towards developing a 6S technology for industrial processes by bringing together research expertise in process systems engineering, wireless communication network, robotic and autonomous systems. The 6S technology developed in this project could be further explored to a wide range of industrial and manufacturing processes.

At the 2015 Paris climate conference, 195 countries agreed that global greenhouse gases should peak as soon as possible and that countries should thereafter rapidly reduce their emissions. The process industries must therefore reduce their energy consumption and increase efficiency while maintaining consumer services. Next generation decision-making software at the interface of engineering, computer science, and mathematics is critical for these efficient systems of the future. Already, state-of-the-art computational packages are routine in the process industries; practically every major company uses simulation and optimisation to model production in different modes including: continuous, batch, and semi-continuous production systems. But more efficient industrial systems require simultaneously considering many tightly integrated subsystems which exponentially increase complexity and necessitate many temporal/spatial scales; the resulting decision making problems may not be solvable with current techniques. Increasing efficiency may also jeopardise safety: the process integration required for efficiency implies interchanging heat between processes and may damage safety precautions by transferring disturbances across a plant. During this fellowship, we propose to develop GALINI, new decision-making software constructing and deploying next generation process optimisation tools dealing with combinatorial complexity, disparate temporal/spatial scales, and safety considerations. The GALINI project proposes step-changes in optimisation algorithms that are immediately applicable to efficiency challenges in process systems engineering (PSE): safely operating batch reactors, retrofitting heat-exchanger networks, intermediate blending, and integrating planning and scheduling. We will freely release our software on open-source platform Pyomo and build an international user community. The primary GALINI research aim is to develop optimisation software that pushes the boundary of computational tractability for PSE energy efficiency applications. Effective optimisation software in the process industries answers: How can we best achieve a definite engineering objective? Given constraints such as an existing plant layout or a contractual obligation to produce specific products, the software supports novel engineering by quantitatively comparing the implications of different options and identifying the best decision. GALINI is particularly interested in design: How should we build new facilities or modify existing ones to achieve our design goals with maximum efficiency? The state-of-the-art in decision making for the process industries is represented by commercial modelling software such as AspenTech and gPROMS. Practically every major company in the process industries uses these software tools since the outputs of the simulation or optimisation can be implemented with minimal day-to-day operational disruption and savings can be realised with a payback time as short as 6-12 months. GALINI will develop deterministic global optimisation software for mixed-integer nonlinear programs, a type of optimisation problem highly relevant to energy efficiency and process systems engineering. Energy efficiency instances may exhibit the mathematical property of nonconvexity, i.e. have many locally optimal solutions; global optimisation mathematically guarantees the best process engineering solution. GALINI proposes transformational shifts in algorithms that creatively reimagine the core divide-and-conquer algorithm typically applied to this type of optimisation problem. Our approach is to freely release GALINI to users including those in the process industries, publicise the software, demonstrate its utility, and build a user community that will feed back into software development.

The power demand of the world is staggering! In 2014, the power requirements of the earth were just over 17 TW, and with an ever increasing population, this value is growing every year. It is clear then, that one of greatest challenges facing humanity is the need for sustainable and clean sources of power. Sunlight provides this in abundance, and in recent years there has been a drive to utilise this resource, through the manufacture and installation of photovoltaics (PV) worldwide. The PV industry has experienced massive growth in the last 10 years, in part due to governmental support in the form of subsidies; however this support will not last forever. It is important that once subsidies have disappeared, the installation of PV around the world remains constant, and continues to deliver clean power to the population. Whilst the majority of the installed capacity is based on well-established silicon based solar cells, more and more cost savings can be found in thin film PV technologies, where cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS) solar cells deposited using vacuum deposition methods represent the leading materials which have successfully moved from lab to industry. However, cost reduction is still key, and to reduce costs further, it is important to move away from expensive methods involving vacuum deposition techniques, and towards devices produced using solution chemistry under atmospheric conditions. However, the deposition of thin film solar cells from solution is not easy. Typically, solutions are prepared by dissolving common metal salts in standard solvents, which are then cast onto a supporting substrate and annealed. As a result, undesired impurities from the salt are often included within the film (such as chlorine or oxygen), which is detrimental to solar cell performance. An alternative approach, which has been successfully developed by researchers at IBM, is to dissolve chalcogenides (such as copper sulphide, indium selenide and gallium selenide) in hydrazine, and produce the solar cell from this solution. In this case, hydrazine has been used as it had been the only known solvent to successfully dissolve chalcogenide materials at room temperature. Using this method, it is possible to fabricate CIGS thin films, without inclusion of detrimental impurities, since all the desired constituent elements are in the starting precursors (namely copper, indium, gallium, selenium and sulphur), with no foreign contaminants. Whilst this method has produced the highest solution processed thin film solar cells to date, hydrazine is a highly toxic, carcinogenic and explosive solvent, which makes up-scaling this technique very difficult. With this in mind, this project aims to fabricate highly efficient thin film CIGS solar cells, using the benefits of chalcogenide starting precursors (i.e. no detrimental impurities), whilst using a safer solvent combination without the use of hydrazine. Recent work by the PI at Loughborough has shown that it is possible to dissolve chalcogenides for use in CIGS thin film growth in a solvent combining an amine and a thiol source. The solvents can be used easily without the need of sophisticated protection equipment; they can be used in ambient atmosphere (hydrazine requires a nitrogen filled glove box); and they do not suffer from strict control laws unlike that of hydrazine (anhydrous hydrazine can not be purchased in the UK). The aim of the project is to fabricate 12-14% CIGS solar cells using the technique, combining the benefits of low toxicity solvents with the pure starting precursors used in the hydrazine method.