Insight research that monitors water quality in real time among the six projects funded

A joint investment of €9 million was today announced through a tripartite research and development partnership between the United States of America (USA), Republic of Ireland (RoI) and Northern Ireland (NI), spanning 16 research institutions. The seven awards will support more than 14 research positions in the Republic of Ireland and 10 research positions in Northern Ireland for three to five years.

Lead researchers Dr Margaret McCaul and Professor Noel O’Connor receieved an award for their DCU-based project titled ‘Ultrasensitive Nitrogen Sensor using Imprinted Polymer Assisted Bacteria for Real-Time Monitoring of Water Quality’.

The study is in the area of environmental monitoring and aims to design, build, validate and field test a prototype sensor system for the real-time detection of the three most commonly monitored forms of nitrogen: nitrate, nitrite and ammonia/ammonium. Such sensor will use 1) polymers to separate and concentrate each form of nitrogen, 2) bacteria to convert each form of nitrogen into a single form (nitrite), 3) advanced 3D printed microfluidics with integrated valves to ensure routes toward the active sensor in a complete analyser platform for field deployment, and 4) a more sensitive colorimetric-based detection system for nitrite using novel ultrasensitive hybrid material photodetectors.

Speaking about the award, Prof Noel O’Connor said “Given the global climate and sustainability challenges facing the world, it is vital that we have access to real-time high quality data so that we can measure the extent of the problem, which is the first step in finding solutions. The sensors to be developed in this project are an example of the type of advances needed in fundamental chemical science in order to produce more frequent and better quality environmental data. The Insight SFI Research Centre in Data Analytics is excited to be co-leading this project as it provides us with an opportunity to understand the future of environmental sensing, so that our analytics engines are primed and ready when this kind of data becomes widely available.”