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Physical Model for Rapid and Accurate Determination of Nanopore Size via Conductance Measurement
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.ORCID iD: 0000-0003-4317-9701
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
2017 (English)In: ACS SENSORS, ISSN 2379-3694, Vol. 2, no 10, p. 1523-1530Article in journal (Refereed) Published
Abstract [en]

Nanopores have been explored for various biochemical and nanoparticle analyses, primarily via characterizing the ionic current through the pores. At present, however, size determination for solid-state nanopores is experimentally tedious and theoretically unaccountable. Here, we establish a physical model by introducing an effective transport length, L (eff) that measures, for a symmetric nanopore, twice the distance from the center of the nanopore where the electric field is the highest to the point along the nanopore axis where the electric field falls to e-(1)of this maximum. By G = sigma(s0)/L-eff, a simple expression S-0=/(G, sigma, h, beta) is derived to algebraically correlate minimum nanopore cross-section area S (0)to nanopore conductance G, electrolyte conductivity a, and membrane thickness h with (3 to denote pore shape that is determined by the pore fabrication technique. The model agrees excellently with experimental results for nanopores in graphene, single-layer MoS2, and ultrathin SiNx films. The generality of the model is verified by applying it to micrometer-size pores.

Place, publisher, year, edition, pages
2017. Vol. 2, no 10, p. 1523-1530
Keywords [en]
nanopores, physical model, effective transport length, algebraic solution, conductance measurement in electrolyte
National Category
Nano Technology
Identifiers
URN: urn:nbn:se:uu:diva-340952DOI: 10.1021/acssensors.7b00576ISI: 000414238600021PubMedID: 28974095OAI: oai:DiVA.org:uu-340952DiVA, id: diva2:1182524
Funder
Swedish Research Council, 621-2014-6300Available from: 2018-02-13 Created: 2018-02-13 Last updated: 2018-04-11Bibliographically approved

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Wen, ChenyuZhang, ZhenZhang, Shi-Li

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