Generation of ocean lithosphere by seafloor spreading at mid-ocean ridges is one of the fundamental geological processes operating on Earth. One of the most important yet most intractable problems is to understand how the magma reservoir beneath ridges generates the lower crust, especially at fast spreading rates. Gabbroic rocks from the lower crust are normally inaccessible, but are now within reach of sampling as a result of the previous successes of scientific ocean drilling expeditions to a unique site within superfast spreading rate crust in the Pacific Ocean. A series of three previous expeditions to Integrated Ocean Drilling Program (IODP) Site 1256 have penetrated through 1500m of upper crustal layers, allowing a new expedition to extensively sample the lower crust for the first time. This will be acheived during IODP Expedition 335 which will return to Site 1256 to deepen the hole still further, hopefully providing a unique suite of lower oceanic crustal samples that will yield unique insights into magmatic and tectonic processes involved in seafloor spreading. As part of this endeavour, palaeomagnetic data will be collected from recovered core pieces and will be critical to understanding the evolution of the lower crust at this site. These data will provide valuable information on the direction and strength of magnetization locked into the gabbroic rocks we expect to encounter, providing a marker that can be used to infer the amount of tectonic rotation that has affected the site and insights into the contribution that lower crustal rocks make to marine magnetic anomalies. In addition, we intend to use a combination of palaeomagnetic data and geophysical images of the inside of the borehole wall to reorient some of the core pieces recovered by drilling, thereby allowing other directional properties (e.g. structural data) to be restored to the correct geographical reference frame.

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

Floating substructures that support offshore wind turbines have widely been constructed from steel, but research has suggested a shift towards use of concrete, due to its lower manufacturing costs, lower carbon footprint and better cost stability, which aligns with government target of achieving 60% UK content by 2030. However, lack of confidence in conventional concrete materials has led to exacting design requirements to ensure their water tightness, leading to excessive thickness that hinders their floatability. This project targets development of innovative polymer-modified concrete materials for lightweight floating platforms. Compared with conventional concrete, polymer-modified concrete has advantages of rapid curing, high impact resistance, high ductility and excellent bonding to reinforcement, which will enable thinner design and eventually less use of materials. Existing research has demonstrated the superior static structural behaviour, but no research has been published on the all-important fatigue failure mechanism. Fundamental research on fatigue is thus needed to unlock its significant potential for offshore structures. This project is a multi-disciplinary project, which involves materials characterisation, structural engineering, chemical engineering and marine engineering.

This project aims to develop a point-of-care diagnostic tool for the early-onset detection of pancreatic cancer. Pancreatic cancer is predicted to become the second leading cause of cancer-death in the next few years. It is mostly asymptomatic, and currently 80% of cases are diagnosed at an advanced stage. Late detection leads to an extremely poor survival prognosis, with average survival of around 5 months after diagnosis. An analysis methodology that leads to early diagnosis, such as that proposed here, will have a profoundly positive effect on pancreatic cancer survival. When tumours are present in the body, specific proteins, indicative of disease progression, are produced and appear in the blood. These proteins, referred to as biomarkers, are indicators of disease. In pancreatic cancer there are two significant biomarkers: CA19-9 and CEA. Unfortunately, these biomarkers alone cannot be used to make a diagnosis in the general population. However, a large number of other proteins have been identified and linked to disease progression. For our project, 30 biomarkers indicative of pancreatic cancer have been carefully selected. Current methods to identify key biomarkers lack the necessary sensitivity and specificity for the detection of early-stage pancreatic cancer, are time consuming to run, and require skilled operators to ensure results are reliable. Therefore, a new approach is needed to achieve early onset pancreatic cancer detection. Effective point-of-care diagnosis will significantly reduce preventable cases. Here we propose to develop an integrated sensor platform that makes measurements indicating the presence of biomarkers using novel sensors. It will then make use of machine leaning approaches to combine these measurements with secondary data, to enhance diagnosis. The secondary data will include 'risk' factors from patient medical history, such as having diabetes. To detect biomarkers at the very low levels they manifest themselves at pancreatic cancer onset, we propose to design a novel sensitive and selective transistor-based sensor system. Normally transistors are operated by directly applying an electrical signal to their channels. Here the sensor system will be based upon an array of transistors which are tuned for the detection of specific biomarkers by using "aptamers" placed onto their channels. The detection process relies upon on specific biomarkers binding to aptamers, which acts like an input signal to change the overall transistor electrical characteristics, which can be subsequently measured. To ensure effective and reliable biomarker detection, it is essential the transistor sensors are built in a consistent fashion, especially regarding aptamer-loaded channel construction, since this greatly affects operation. To achieve this, a 3D-bioprinter will be used to deliver controlled volumes of aptamers to the transistor in an automated fashion. The experimental phase of the research will systematically progress from simple to complex detection tasks. Phase 1 of will focus on creating the sensors for initial characterisation studies. In the second phase, sensor capacity to detect known biomarker concentrations will determine the sensor sensitivity and detection limits. The final stage 3 will examine biomarker detection in serum samples from patients with pancreatic cancer at varying stages of disease progression, as well as healthy controls. Sensor data will be combined with risk-life factors to train a machine learning system to detect the presence of pancreatic cancer. Finally, we will evaluate sensor performance as a diagnostic tool to predict early-onset pancreatic cancer.

To develop a capability to generate unique intelligent music composition tools to exploit a number of developed market opportunities.