This PhD, which is an interdisciplinary creative-critical project, will investigate the depiction of motherhood focusing specifically on the representations of trauma as a consequence of bereavement and child disability. I will explore Denise Riley's Say Something Back and Time Lived, Without Its Flow, as well as Tory Peters' Detransition, Baby; I will use secondary sociological research to root the lyrical self within the context of real-world experience and explore literatures role as social messaging. Creatively I will explore alternative motherhood narratives to challenge social norms and praxis.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

This project will explore the significance of the Commission on Fees and conceptions of Monarchical Paternalism to State Formation in early modern England.

We will develop spray coated solar cell technology and explore the direct deposition of high efficiency perovskite solar cells onto curved surfaces. Sush devices will add minimal weight to the surface on which they are coated and will allow energy to be generated in locations close to where it is being used, for example on the roof or body of an electric vehicle, or the cladding that is attached to the surface of a building. Our preliminary measurements suggest such a mass penalty to be around 5 grams per square metre and therefore such solar cells will add relatively little overall weight of an electric vehicle (EV), but will be capable of trickle-charging the car's battery when it is parked in the sunshine. The low weight nature of our technology is expected to be particularly important for EV applications, as reduced weight extends their maximum driving range. The carbon fibre composite materials on which we spray-cast solar cells will also be light-weight, rigid and strong and will be of importance in building applications as they could be retro-fitted as cladding to older buildings that are unable to support the weight of relatively heavy conventional solar cell devices based on silicon. This research will build a unique toolbox of manufacturing process for the production of solar cells based around ultrasonic spray-coating. The process has recently been demonstrated at small 'lab-scale'. Our aim is to scale-up this technology, making it more repeatable and increasing the efficiency by which the solar cell converts light to electricity (the so-called power conversion efficiency). The surface on which we will spray-coat devices is of critical importance; surfaces have to be very smooth and contain a low rate of imperfections. Existing research has mainly targeted glass surfaces which are very smooth, however a process to spray-coat solar-cells onto carbon fibre composites having appropriate surface requirements will be developed. This process development will enable the transfer of this technology to a variety of other composites and can be expanded to include other emerging manufacturing methods. The research will culminate in the creation of a demonstrator device that will be fabricated over a non planar carbon-fibre surface. We plan to show the demonstrator to potential end users and build a collaboration network that will further develop this technology and drive it towards commercialisation.

Help feed the world! With a growing population, climate change and water scarcity it's important that we can design better formulations for agrochemicals. Being able to predict what formulation will be stable will speed up formulation and product design allowing us to improve efficacy, efficiency, sustainability and safety. The proposal is to model mixtures that can form stable Emulsion Concentrate (EC) formulations using machine learning from a dataset produced by Syngenta using Artemus (Robot). The ability to model this complex multi-dimensional problem cannot be currently completely solely using mechanistic models alone. This proposal would take our machine learning methodologies, expertise and state of the art from the literature and adapt them to model the data of a designed experimental dataset of formulation mixtures that cover the breadth of EC mixtures of interest to Syngenta. This currently has not been done to date however we have had success with for example metal organic frameworks in eutectic mixtures and many other datasets there is scope to discover how we can use machine learning in development of formulation design. The plan is to start with EC's as a simple formulation type to demonstrate the technology and to learn how best to adapt the methodology. You would need to be able to learn programming and be interested in learning machine learning techniques.