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Issue 1, 2020
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A methodology for characterising nanoparticle size and shape using nanopores

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Abstract

The discovery and characterisation of nanomaterials represents a multidisciplinary problem. Their properties and applications within biological, physical and medicinal sciences depend on their size, shape, concentration and surface charge. No single technology can currently measure all characteristics. Here we combine resistive pulse sensing with predictive logistic regression models, termed RPS-LRM, to rapidly characterise a nanomaterial's size, aspect ratio, shape and concentration when mixtures of nanorods and nanospheres are present in the same solution. We demonstrate that RPS-LRM can be applied to the characterisation of nanoparticles over a wide size range, and varying aspect ratios, and can distinguish between nanorods over nanospheres when they possess an aspect ratio grater then two. The RPS-LRM can rapidly measure the ratios of nanospheres to nanorods in solution within mixtures, regardless of their relative sizes and ratios i.e. many large nanospherical particles do not interfere with the characterisation of smaller nanorods. This was done with a 91% correct classification of nanospherical particles and 72% correct classification of nanorods even when the fraction of nanorods in solution is as low as 20%. The methodology here will enable the classification of nanomedicines, new nanomaterials and biological analytes in solution.

Graphical abstract: A methodology for characterising nanoparticle size and shape using nanopores

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Article information


Submitted
24 Oct 2019
Accepted
26 Nov 2019
First published
26 Nov 2019

Nanoscale, 2020,12, 262-270
Article type
Paper

A methodology for characterising nanoparticle size and shape using nanopores

R. Maugi, P. Hauer, J. Bowen, E. Ashman, E. Hunsicker and M. Platt, Nanoscale, 2020, 12, 262
DOI: 10.1039/C9NR09100A

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