21–26 Jun 2026
U. Ottawa - Learning Crossroads (CRX) Building
America/Toronto timezone
Welcome to the 2026 CAP Congress Program website! / Bienvenue au siteweb du programme du Congrès de l'ACP 2026!

Nanomembrane -based Microfluidic Platform with Embedded Electrical Pressure Transducer for On-Chip Nanoparticle Quantification

23 Jun 2026, 16:45
15m
U. Ottawa - Learning Crossroads (CRX) Building

U. Ottawa - Learning Crossroads (CRX) Building

100 Louis-Pasteur Private, Ottawa, ON K1N 9N3
Oral Competition (Graduate Student) / Compétition orale (Étudiant(e) du 2e ou 3e cycle) Applied Physics and Instrumentation / Physique appliquée et de l'instrumentation (DAPI / DPAI) (DAPI) T3-9 | (DPAI)

Speaker

Zachary Morris (University of Ottawa)

Description

Accurate quantification of nanoparticle concentration is important in a host of fields, particularly in nanomedicine, electronics, and catalysis. Microfluidic systems present an opportunity to develop low-cost tests for nanoparticle quantification but often suffer technical challenges related to small sample volumes and optical interference from materials used to construct the device. Here we introduce a microfluidic device that integrates an ultrathin silicon nitride nanoporous membrane (nanomembrane) with an on-chip pressure transducer, designed to precisely quantify nanoparticle concentrations within a microfluidic device using an electrical readout for quantification. As nanoparticles are captured by the nanomembrane under pressure-driven flow, the pressure-differential across it changes and is measured by an on-chip transducer. The pressure transducer utilizes a thin PDMS membrane that deflects under pressure to change the cross-section and ionic flow resistance of an adjacent channel, which is measured using a pair of Ag/AgCl electrodes. This enables the determination of nano-particle concentration by analysis of the kinetics of trans-membrane pressure changes relative to particle blockage of the nanomembrane. We also propose a statistical model of nanomembrane fouling, which accounts for distributions in pore and particle sizes as well as the variety of blocking mechanisms and their interactions. This model provides a more detailed understanding of nanoparticle filtration behavior and the kinetics of nanopore blocking, enabling accurate concentration determination when used as a predictive model. Experimental validation of the model using the data acquired by the microfluidic device demonstrates a lower limit of detection on the order of 108 particles/mL, offering a versatile, non-optical approach for the in-situ quantification of nanoparticles in a microfluidic device.

Keyword-1 Microfluidics
Keyword-2 Membrane-fouling
Keyword-3 Biosensor

Author

Zachary Morris (University of Ottawa)

Presentation materials

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