A methodology for characterising nanoparticle size and shape using nanopores. Issue 1 (9th December 2019)
- Record Type:
- Journal Article
- Title:
- A methodology for characterising nanoparticle size and shape using nanopores. Issue 1 (9th December 2019)
- Main Title:
- A methodology for characterising nanoparticle size and shape using nanopores
- Authors:
- Maugi, R.
Hauer, P.
Bowen, J.
Ashman, E.
Hunsicker, E.
Platt, M. - Abstract:
- Abstract : The discovery and characterisation of nanomaterials represents a multidisciplinary problem, here we apply predictive logistic regression models with resistive pulse sensing to create an rapid analysis technology. 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 willAbstract : The discovery and characterisation of nanomaterials represents a multidisciplinary problem, here we apply predictive logistic regression models with resistive pulse sensing to create an rapid analysis technology. 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. … (more)
- Is Part Of:
- Nanoscale. Volume 12:Issue 1(2020)
- Journal:
- Nanoscale
- Issue:
- Volume 12:Issue 1(2020)
- Issue Display:
- Volume 12, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 12
- Issue:
- 1
- Issue Sort Value:
- 2020-0012-0001-0000
- Page Start:
- 262
- Page End:
- 270
- Publication Date:
- 2019-12-09
- Subjects:
- Nanoscience -- Periodicals
Nanotechnology -- Periodicals
620.505 - Journal URLs:
- http://www.rsc.org/Publishing/Journals/NR/Index.asp ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c9nr09100a ↗
- Languages:
- English
- ISSNs:
- 2040-3364
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9830.266000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 12556.xml