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Modeling Au Nanostar Geometry in Bulk Solutions

[Image: see text] The findings within make it possible to reference gold nanostars based on their geometric properties, similar to how a radius describes a nanosphere, rather than just the LSPR of the structure—the current practice. The average tip approximation presented reduces the complexity of n...

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Autores principales: Morton, William, Joyce, Caoimhe, Taylor, Jonny, Ryan, Mary, Angioletti-Uberti, Stefano, Xie, Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884095/
https://www.ncbi.nlm.nih.gov/pubmed/36721768
http://dx.doi.org/10.1021/acs.jpcc.2c07520
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author Morton, William
Joyce, Caoimhe
Taylor, Jonny
Ryan, Mary
Angioletti-Uberti, Stefano
Xie, Fang
author_facet Morton, William
Joyce, Caoimhe
Taylor, Jonny
Ryan, Mary
Angioletti-Uberti, Stefano
Xie, Fang
author_sort Morton, William
collection PubMed
description [Image: see text] The findings within make it possible to reference gold nanostars based on their geometric properties, similar to how a radius describes a nanosphere, rather than just the LSPR of the structure—the current practice. The average tip approximation presented reduces the complexity of nanostars in discrete dipole approximation simulations. By matching the projected area and LSPR of the modeled nanostars to synthesized nanostars, the volume, surface area, and number of tips can be approximated without a lengthy characterization process. Knowing the nanoparticle geometry can determine drug carrier capacity, an approximate number of hot spots for EM imaging, and how the particle will interact with cells. The geometric data obtained will drive the biological application and increase the usability of this particle class.
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spelling pubmed-98840952023-01-29 Modeling Au Nanostar Geometry in Bulk Solutions Morton, William Joyce, Caoimhe Taylor, Jonny Ryan, Mary Angioletti-Uberti, Stefano Xie, Fang J Phys Chem C Nanomater Interfaces [Image: see text] The findings within make it possible to reference gold nanostars based on their geometric properties, similar to how a radius describes a nanosphere, rather than just the LSPR of the structure—the current practice. The average tip approximation presented reduces the complexity of nanostars in discrete dipole approximation simulations. By matching the projected area and LSPR of the modeled nanostars to synthesized nanostars, the volume, surface area, and number of tips can be approximated without a lengthy characterization process. Knowing the nanoparticle geometry can determine drug carrier capacity, an approximate number of hot spots for EM imaging, and how the particle will interact with cells. The geometric data obtained will drive the biological application and increase the usability of this particle class. American Chemical Society 2023-01-12 /pmc/articles/PMC9884095/ /pubmed/36721768 http://dx.doi.org/10.1021/acs.jpcc.2c07520 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Morton, William
Joyce, Caoimhe
Taylor, Jonny
Ryan, Mary
Angioletti-Uberti, Stefano
Xie, Fang
Modeling Au Nanostar Geometry in Bulk Solutions
title Modeling Au Nanostar Geometry in Bulk Solutions
title_full Modeling Au Nanostar Geometry in Bulk Solutions
title_fullStr Modeling Au Nanostar Geometry in Bulk Solutions
title_full_unstemmed Modeling Au Nanostar Geometry in Bulk Solutions
title_short Modeling Au Nanostar Geometry in Bulk Solutions
title_sort modeling au nanostar geometry in bulk solutions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884095/
https://www.ncbi.nlm.nih.gov/pubmed/36721768
http://dx.doi.org/10.1021/acs.jpcc.2c07520
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