Reliable, point-of-care and reusable sensors are highly needed to drive a revolution in medical diagnosis. In this respect, nanopore-based sensors are emerging as a promising technology for single-molecule sensing. After introducing the basic principles of nanopore sensing devices, we present open challenges related to their development as sensors, focusing on the role of modelling in the design of future biosensing devices. For this, we propose a hierarchical multiscale approach having a Brownian solver at its core. We show that it is able to efficiently calculate the capture statistics, integrating pore and particle features. Finally, we discuss possible improvements to include additional hydrodynamic/electric/chemical effects.
Chinappi, M., Di Muccio, G., Giordani, C., Cecconi, F., Morozzo della Rocca, B. (2022). A Brownian computational approach for supporting the design of nanopore-based biosensors. In 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) (pp.98-103). IEEE [10.1109/MetroInd4.0IoT54413.2022.9831727].
A Brownian computational approach for supporting the design of nanopore-based biosensors
Chinappi, M;Morozzo della Rocca, B
2022-01-01
Abstract
Reliable, point-of-care and reusable sensors are highly needed to drive a revolution in medical diagnosis. In this respect, nanopore-based sensors are emerging as a promising technology for single-molecule sensing. After introducing the basic principles of nanopore sensing devices, we present open challenges related to their development as sensors, focusing on the role of modelling in the design of future biosensing devices. For this, we propose a hierarchical multiscale approach having a Brownian solver at its core. We show that it is able to efficiently calculate the capture statistics, integrating pore and particle features. Finally, we discuss possible improvements to include additional hydrodynamic/electric/chemical effects.| File | Dimensione | Formato | |
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