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Single Particle Automated Raman Trapping Analysis
Enabling concurrent, high throughput analysis of single nanoparticles would greatly increase the capacity to study size, composition and inter and intra particle population variance with applications in a wide range of fields from polymer science to drug delivery. Here, we present a comprehensive pl...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189196/ https://www.ncbi.nlm.nih.gov/pubmed/30323298 http://dx.doi.org/10.1038/s41467-018-06397-6 |
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author | Penders, Jelle Pence, Isaac J. Horgan, Conor C. Bergholt, Mads S. Wood, Christopher S. Najer, Adrian Kauscher, Ulrike Nagelkerke, Anika Stevens, Molly M. |
author_facet | Penders, Jelle Pence, Isaac J. Horgan, Conor C. Bergholt, Mads S. Wood, Christopher S. Najer, Adrian Kauscher, Ulrike Nagelkerke, Anika Stevens, Molly M. |
author_sort | Penders, Jelle |
collection | PubMed |
description | Enabling concurrent, high throughput analysis of single nanoparticles would greatly increase the capacity to study size, composition and inter and intra particle population variance with applications in a wide range of fields from polymer science to drug delivery. Here, we present a comprehensive platform for Single Particle Automated Raman Trapping Analysis (SPARTA) able to integrally analyse nanoparticles ranging from synthetic polymer particles to liposomes without any modification. With the developed highly controlled automated trapping process, single nanoparticles are analysed with high throughput and sensitivity to resolve particle mixtures, obtain detailed compositional spectra of complex particles, track sequential functionalisations, derive particle sizes and monitor the dynamics of click reactions occurring on the nanoparticle surface. The SPARTA platform opens up a wide range of new avenues for nanoparticle research through label-free integral high-throughput single particle analysis, overcoming key limitations in sensitivity and specificity of existing bulk analysis methods. |
format | Online Article Text |
id | pubmed-6189196 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61891962018-10-17 Single Particle Automated Raman Trapping Analysis Penders, Jelle Pence, Isaac J. Horgan, Conor C. Bergholt, Mads S. Wood, Christopher S. Najer, Adrian Kauscher, Ulrike Nagelkerke, Anika Stevens, Molly M. Nat Commun Article Enabling concurrent, high throughput analysis of single nanoparticles would greatly increase the capacity to study size, composition and inter and intra particle population variance with applications in a wide range of fields from polymer science to drug delivery. Here, we present a comprehensive platform for Single Particle Automated Raman Trapping Analysis (SPARTA) able to integrally analyse nanoparticles ranging from synthetic polymer particles to liposomes without any modification. With the developed highly controlled automated trapping process, single nanoparticles are analysed with high throughput and sensitivity to resolve particle mixtures, obtain detailed compositional spectra of complex particles, track sequential functionalisations, derive particle sizes and monitor the dynamics of click reactions occurring on the nanoparticle surface. The SPARTA platform opens up a wide range of new avenues for nanoparticle research through label-free integral high-throughput single particle analysis, overcoming key limitations in sensitivity and specificity of existing bulk analysis methods. Nature Publishing Group UK 2018-10-15 /pmc/articles/PMC6189196/ /pubmed/30323298 http://dx.doi.org/10.1038/s41467-018-06397-6 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Penders, Jelle Pence, Isaac J. Horgan, Conor C. Bergholt, Mads S. Wood, Christopher S. Najer, Adrian Kauscher, Ulrike Nagelkerke, Anika Stevens, Molly M. Single Particle Automated Raman Trapping Analysis |
title | Single Particle Automated Raman Trapping Analysis |
title_full | Single Particle Automated Raman Trapping Analysis |
title_fullStr | Single Particle Automated Raman Trapping Analysis |
title_full_unstemmed | Single Particle Automated Raman Trapping Analysis |
title_short | Single Particle Automated Raman Trapping Analysis |
title_sort | single particle automated raman trapping analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6189196/ https://www.ncbi.nlm.nih.gov/pubmed/30323298 http://dx.doi.org/10.1038/s41467-018-06397-6 |
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