Project Overview
My project aims to develop an ultrafast biosensor platform for in-situ detection of
multiple contaminants (e.g., MIB, geosmin, PFAS, ammonia, nitrate, phosphate) in water by
incorporating pattern recognition algorithms. For water utility companies, typical
analyses of these contaminants require the transportation of water samples to a lab and is
also expensive and labour intensive. Quick turnaround time from sampling to analytical
result is a further unmet challenge where contamination of water supplies is suspected.
Low-cost carbon sensor electrodes with properties of enhanced electron transfer and
surface area will be derived from food wastes and fabricated using patented flexographic
printing. They will generate characteristic electrochemical signals upon interaction with
various contaminants in water that are distinct from those caused by non-specific
adsorption. This will provide an essential step towards label free, direct, and
easy-to-use in situ monitoring devices.
Project Aims
1. Detect PFAS using Molecular imprint polymer (MIP) with EIS
2. DPV based on ‘electronic tongue’ concept and algorithm developed using machine-learning.
3. Develop multiplexed system to detect various PFAS simultaneously which are prevalent in the environment.