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A methodology for characterising nanoparticle size and shape analysis using nanopores

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journal contribution
posted on 27.11.2019, 11:24 by Rhushabh Maugi, Peter Hauer, Jenna Bowen, Elizabeth Ashman, Eugenie HunsickerEugenie Hunsicker, Mark PlattMark Platt

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.

History

School

  • Science

Department

  • Chemistry
  • Mathematical Sciences

Published in

Nanoscale

Volume

12

Pages

262-270

Publisher

Royal Society of Chemistry (RSC)

Version

AM (Accepted Manuscript)

Rights holder

© Royal Society of Chemistry

Publisher statement

This paper was accepted for publication in the journal Nanoscale and the definitive published version is available at https://doi.org/10.1039/c9nr09100a.

Acceptance date

26/11/2019

Publication date

2019-11-26

Copyright date

2020

ISSN

2040-3364

eISSN

2040-3372

Language

en

Depositor

Dr Mark Platt. Deposit date: 26 November 2019