Daniel Martins, a postdoctoral researcher working with the VistaMilk SFI Research Centre at TSSG, presented at the SFI Summit 2020.
Abstract: The fast and accurate detection of chemicals related to the misuse of natural resources, such as the overuse of pesticides, and diseases in animals is a need for the dairy industry. Therefore, researchers are proposing novel technologies to reduce the detection times and improve the sensing accuracy through systems that are specialised to the molecule of interest. In this work, we propose a different approach to this scenario, where a single-design device can detect a wide variety of molecules. We name this device as molecular computing-on-a-chip. In this case, bacterial populations are engineered, and confined in a microscale box, to compute the molecules of interest and the outcome of this process is a change in pH, or in the concentration of dissolved oxygen, in the environment that can be detected by conventional sensing silicon chips. We evaluated the performance of the proposed device in terms of the accuracy for the sensing of two chemicals concentrations (nitrile and acetate). Additionally, we compared two techniques to detect the changes in pH and dissolved oxygen concentration. Our results show that the proposed design has good accuracy (around 75%) and it can become the basis for the further development of smart sensing chips.