One of great 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 by the EU Drinking Water Directive. For example, DBP N-nitrosodimethylamine (NDMA) has been classified as “probably carcinogenic to humans” by the International Agency for Research on Cancer. Detection and quantitation of these key markers of water quality and safety require sensitive analytical techniques to satisfy the current, but also upcoming regulations.
For water utility companies, typical process to test these DBPs takes three days, including solid phase extraction (SPE), HPLC-MS and GC-MS for NDMA analysis. These analyses require the transportation of water samples to a lab, and is also expensive (e.g. £200 per sample for NDMA) and labour intensive. Quick turnaround time from sampling to analytical result is a further unmet imperative where contamination of water supplies is suspected. As part of the most recent "internet of things" and digital water technology adoption, there will be a trend towards providing real-time data and actionable information to all parties involved. Imagine providing consumers with real-time water quality data in addition to consumption metrics. It will be also the tipping point in a move from centralized water quality monitoring to instead providing real-time actionable information for service engineers, stakeholders and customers. This project will develop a single ultrafast sensor screening platform for in-situ detection of carcinogenic DBP by incorporating pattern recognition algorithms developed using artificial neural network method.
Project supervisors: Dr Wei Zhang and Professor K S Teng
Eligibility Candidates should hold a first or upper second class (2.1) honours degree in Chemical or Biochemical Engineering, or a related discipline (e.g. chemistry, biochemistry, physics, or other engineering discipline). Candidates with a Master’s degree in Chemical, Environmental or Materials Engineering are preferred.
Experience in water quality analysis, nanomaterials synthesis and/or electrochemistry is required.