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Details of Grant 

EPSRC Reference: EP/W006294/1
Title: Microfluidic modelling and optimisation of statistical design for shape measurement in resistive pulse sensing: pilot project
Principal Investigator: Mazza, Dr M G
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Mathematical Sciences
Organisation: Loughborough University
Scheme: Standard Research - NR1
Starts: 04 January 2022 Ends: 03 January 2023 Value (£): 80,592
EPSRC Research Topic Classifications:
Continuum Mechanics Particle Technology
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
26 May 2021 EPSRC Mathematical Sciences Small Grants Panel May 2021 Announced
Summary on Grant Application Form
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.
Key Findings
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Organisation Website: http://www.lboro.ac.uk