Issue 20, 2023

Continuous-flow macromolecular sieving in slanted nanofilter array: stochastic model and coupling effect of electrostatic and steric hindrance

Abstract

Microfabricated slanted nanofilter arrays are a promising technology for integrated biomolecule analysis systems such as online monitoring and point-of-care quality validation, due to their continuous-flow and one-step operation capability. However, an incomplete understanding of the system limits the performance and wider applications of slanted nanofilter arrays. In this paper, we present rigorous theoretical and experimental studies on macromolecule sieving in a slanted nanofilter array. From both stochastic and kinetic models, an explicit theoretical solution describing size-dependent molecule sieving was derived, which was validated using experimental sieving results obtained for various sieving conditions. Our results not only detail the relationship between sieving conditions and sieving efficiency but also demonstrate that sieving is affected by multiple hindrance effects (electrostatic hindrance), not steric hindrance alone. There is an optimal sieving condition for achieving the greatest separation efficiency for DNAs of a certain size range. Small DNA has great size selectivity in small nanofilters and in weak electric fields, whereas large DNA is present in large nanofilters and in strong electric fields. This study provides insights into designing a slanted nanofilter array for particular target applications and understanding the sieving principles in the nanofilter array.

Graphical abstract: Continuous-flow macromolecular sieving in slanted nanofilter array: stochastic model and coupling effect of electrostatic and steric hindrance

Supplementary files

Article information

Article type
Paper
Submitted
10 May 2023
Accepted
21 Aug 2023
First published
22 Aug 2023

Lab Chip, 2023,23, 4422-4433

Continuous-flow macromolecular sieving in slanted nanofilter array: stochastic model and coupling effect of electrostatic and steric hindrance

S. H. Ko, P. J. Park and J. Han, Lab Chip, 2023, 23, 4422 DOI: 10.1039/D3LC00405H

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