PhD Studentship: Smart nutrient sensor networks using miniaturised optical and electrochemical detection
DoS: Dr. Simon Ussher (Email: [email protected] )
2nd Supervisor: Dr. Angela Milne (Email: [email protected] )
3rd Supervisor: Dr. Paul Davey (Email: [email protected] )
4th Supervisor: Malcolm Woodward (Email: [email protected] ) Plymouth Marine Laboratory
Project Partner: Rob Passmore, Additive Catchments
Applications are invited for a 3.5 years PhD studentship within the Environmental Intelligence doctoral training programme at the University of Plymouth, starting on 01 October 2024.
Project Description
Scientific background: Phosphorus (P) and nitrogen (N) are essential elements for life but excess quantities of fixed nutrients in catchments cause eutrophication, toxicity and affect catchment ecosystem function [1]. Dissolved ammonia (NH3 ) is a critical chemical parameter required by UK legislation [2], whereas P is often the growth limiting element in catchments, particularly in areas of high N (Nitrate Vulnerable Zones) [3]. Recent legal standards (e.g. Nutrient Neutrality Programme and Environment Act 2021) require nutrient emissions to be determined at catchment scale and concentration limits to be legally enforced. Hence, there is a demand for better spatial and temporal data from water quality monitoring networks [4] and application of emerging technology, including off-the shelf Internet of Things (IoT) sensors and novel miniaturised chemical sensors (nanomaterials, microfluidic spectrophotometric/fluorescence, fiber-optic, microelectrodes) [5-7]. As data flow increases in size and complexity, well designed systems-based approaches are needed to improve cost, efficiency, reduce carbon emissions, minimise computing requirements and support the deployment of sensing systems. Real-time data offers the opportunity for Artificial Intelligence (AI) integration, with the potential for predictive models for phosphate [8] and ammonia [9] from other water parameters, with the final goal of developing catchment digital twins [10].
Research methodology: Starting with commercial sensors (e.g. conductivity, pH), ion selective electrodes and liquid core waveguides (PO4 3- and NH4 + ) [11,12], the student will automate these using established interfaces developed at UoP [13]. Novel detection methods will be explored, including microfluidic spectrophotometry, fibre-optics, and microelectrodes for detection of PO4 3- and NH3 -N (Co-S Woodward). Microcontroller engineering, optical detection and telemetry (Co-S Davey) will allow custom design, miniaturisation, data acquisition and fabrication of novel sensors [14,15]. Through the project partner, sensor data flow will be integrated with AI to develop and validate next-generation water monitoring solutions that interface with catchment management platforms.
Training: The student will receive tuition in environmental sensing, networks and data processing. Initial training in nutrient analysis and automation will be provided using existing sensors and established interfaces at UoP running on LabVIEW. The student will develop skills in big data analysis and programming (R and Python) alongside instruction in analytical quality assurance in ISO 9001 laboratories. Training in microcontroller engineering and fabrication of optical detectors (Co-S Davey) and expertise in sub-micromolar nutrient analysis and cutting-edge techniques (Co-S Woodward) will be offered, as well as training opportunities in AI and industry experience will be provided by project partner Additive Catchments.
Person specification:
We are looking for a graduate with practical hands-on skills with a will to develop knowledge and desirable skill set bridging physical and environmental science, analytical chemistry and engineering.
If you wish to discuss this project further informally, please contact Dr Simon Ussher, email [email protected]
For further information on Eligibility & Funding , please click on the links below:
To apply, please click the 'Apply' button, above.
The closing date for applications on 26 April 2024.