Developing low-cost electrochemical biosensor for disinfection by-product (DPB) detection in drinking water

One of the greatest challenges in drink water safety is the increasing public concern with the contamination of carcinogenic disinfection by products (DBP), since chemical disinfection (e.g. chlorination) is widely adopted and referred to as the single process able to prevent water-borne disease (or pathogenic) outbreaks. For water utility companies, typical process to analyse these DBPs takes three days, which requires the transportation of water samples to a lab, and is also expensive (e.g. £200 per sample) and labour intensive. Therefore, quick turnaround time from sampling to analytical result is a unmet imperative where contamination of water supplies is suspected.

The key objectives of this PhD project is to design, fabricate and validate electrochemical biosensor platform based on low-cost carbon transducers for the rapid, sensitive and reliable detection of carcinogenic DBPs in water. This will reduce the existing analysis time of UK water companies for DBP contamination from three days to three minutes in situ, so that water treatment processes (both drinking water and wastewater discharge to the environment) can be controlled and optimized in real time. The resulting knowledge, evidence and innovation will impact current urban water infrastructures and management in the UK by reducing the risk of water quality failure, their environmental footprint and the likelihood of excessive future investment on the infrastructures of water quality management.

This PhD project fits perfectly in the ESPRC 'Engineering' theme and priority research area: Water Engineering, which encompasses the aims of design and optimisation of technologies relating to assessment and control of water quality. In first stage, PhD student will be given the opportunity to develop novel low-cost sensor electrode from spent coffee grounds (SCG). Approximately 90% of coffee grounds in the UK are wasted, creating hundreds of thousands of tonnes of SCG per year-one of the most abundant type of food waste that remains largely unexploited by industry. SCG contains a high volume of carbon, which can be first turned into porous and conductive carbon powder through a modified carbonisation process and then mass produced into sensor electrodes via high-volume screen-printing technique. This novel recycling approach of sensor electrode fabrication from near zero-cost and toxic SCG waste will contribute to the UK long-term goal of food circular economy. In second stage, PhD student will develop pattern recognition algorithms for DBPs using artificial neural network method. As a result, low cost SCG sensor arrays -equipped with artificial intelligence (AI) derived algorithms- will then be able to identify characteristic patterns of electrochemical response for each DBP simultaneously, thus leading to innovative technology for in situ multiplex assessment of a range of key contaminants in drinking water.