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Shape Dependent EMA Model of Nanostructured Anisotropic Materials

Heterogeneous nanostructures containing nanoparticles of various sizes and shapes have attracted significant attention in the development of nano-biosensors. Especially, plasmonic properties of such materials are advantageously exploited for the detection of biological and chemical substances. Since...

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Detalles Bibliográficos
Autores principales: Otipka, Petr, Vlček, Jaroslav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6835424/
https://www.ncbi.nlm.nih.gov/pubmed/31561581
http://dx.doi.org/10.3390/nano9101380
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author Otipka, Petr
Vlček, Jaroslav
author_facet Otipka, Petr
Vlček, Jaroslav
author_sort Otipka, Petr
collection PubMed
description Heterogeneous nanostructures containing nanoparticles of various sizes and shapes have attracted significant attention in the development of nano-biosensors. Especially, plasmonic properties of such materials are advantageously exploited for the detection of biological and chemical substances. Since these media exhibit optical anisotropy, a valid homogenization procedure must be able to describe appropriately the relationship between the geometry of the inclusions and the nature of local field modes. We present a model approach for extension of the effective medium approximation (EMA) and its application to anisotropic nanostructures. The proposed model is based on a “strong-couple-dipole” (SCD) method including a volume-integral correction term in a Green tensor that enables to obtain more accurate representation of polarizability tensor. Derived depolarization factors for discs and bi-cone particles are compared with the early known shapes (spheroids, cylinders) and applied to nanostructures composed of the Fe or Au nanodots in polyacrylate.
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spelling pubmed-68354242019-11-25 Shape Dependent EMA Model of Nanostructured Anisotropic Materials Otipka, Petr Vlček, Jaroslav Nanomaterials (Basel) Article Heterogeneous nanostructures containing nanoparticles of various sizes and shapes have attracted significant attention in the development of nano-biosensors. Especially, plasmonic properties of such materials are advantageously exploited for the detection of biological and chemical substances. Since these media exhibit optical anisotropy, a valid homogenization procedure must be able to describe appropriately the relationship between the geometry of the inclusions and the nature of local field modes. We present a model approach for extension of the effective medium approximation (EMA) and its application to anisotropic nanostructures. The proposed model is based on a “strong-couple-dipole” (SCD) method including a volume-integral correction term in a Green tensor that enables to obtain more accurate representation of polarizability tensor. Derived depolarization factors for discs and bi-cone particles are compared with the early known shapes (spheroids, cylinders) and applied to nanostructures composed of the Fe or Au nanodots in polyacrylate. MDPI 2019-09-26 /pmc/articles/PMC6835424/ /pubmed/31561581 http://dx.doi.org/10.3390/nano9101380 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Otipka, Petr
Vlček, Jaroslav
Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title_full Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title_fullStr Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title_full_unstemmed Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title_short Shape Dependent EMA Model of Nanostructured Anisotropic Materials
title_sort shape dependent ema model of nanostructured anisotropic materials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6835424/
https://www.ncbi.nlm.nih.gov/pubmed/31561581
http://dx.doi.org/10.3390/nano9101380
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