Microfluidic modelling and optimisation of statistical design for shape measurement in resistive pulse sensing: pilot project

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A fruit juice company needs an efficient way to monitor beverages for bacterial contamination. A marine conservation research group needs a way to detect and characterise micro and nanoplastic contamination in ocean water and in the stomach fluids of marine animals. A researcher developing bacteriophage therapies needs to be able to tell the proportion of active phages in a sample. Each of these applications requires a method for detecting and characterising very small particles suspended in liquids. Resistive Pulse Sensing (RPS) is a technology that has been used for counting and determining the size distributions for micro to nano scale particles in solution. Recent work by the PI and her collaborators has demonstrated that RPS technology also has the potential to yield shape information for such particles. Adding this capacity to RPS technology would make it possible to distinguish different bacteria (rod shaped versus sphere shaped), characterise the shape of micro and nanoplastics (which is believed to influence their bioactivity), and distinguish active from inactive phages in a sample. This research project will develop a three dimensional model of the microfluidics, electrostatics and pulse generation in RPS sensors for a range of pore geometries and particle shapes. This will then be used to develop a statistically optimised pore design and a signal processing algorithm that will for the first time permit RPS technology to produce a shape measurement for particles. In collaboration with researchers in analytical science developing novel RPS sensors, as well as with end-users from the drinks industry, marine conservation and bacteriophage research, the pore design will be realised, and the signal processing algorithm tested on a range of relevant samples to produce a next generation RPS device.