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Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures
In this paper, we present our optimization tool for fluorophore-conjugated metal nanostructures for the purpose of designing novel contrast agents for multimodal bioimaging. Contrast agents are of great importance to biological imaging. They usually include nanoelements causing a reduction in the ne...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6600714/ https://www.ncbi.nlm.nih.gov/pubmed/31151325 http://dx.doi.org/10.3390/ma12111766 |
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author | Fixler, Dror Tzur, Chen Zalevsky, Zeev |
author_facet | Fixler, Dror Tzur, Chen Zalevsky, Zeev |
author_sort | Fixler, Dror |
collection | PubMed |
description | In this paper, we present our optimization tool for fluorophore-conjugated metal nanostructures for the purpose of designing novel contrast agents for multimodal bioimaging. Contrast agents are of great importance to biological imaging. They usually include nanoelements causing a reduction in the need for harmful materials and improvement in the quality of the captured images. Thus, smart design tools that are based on evolutionary algorithms and machine learning definitely provide a technological leap in the fluorescence bioimaging world. This article proposes the usage of properly designed metallic structures that change their fluorescence properties when the dye molecules and the plasmonic nanoparticles interact. The nanostructures design and evaluation processes are based upon genetic algorithms, and they result in an optimal separation distance, orientation angles, and aspect ratio of the metal nanostructure. |
format | Online Article Text |
id | pubmed-6600714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66007142019-07-16 Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures Fixler, Dror Tzur, Chen Zalevsky, Zeev Materials (Basel) Article In this paper, we present our optimization tool for fluorophore-conjugated metal nanostructures for the purpose of designing novel contrast agents for multimodal bioimaging. Contrast agents are of great importance to biological imaging. They usually include nanoelements causing a reduction in the need for harmful materials and improvement in the quality of the captured images. Thus, smart design tools that are based on evolutionary algorithms and machine learning definitely provide a technological leap in the fluorescence bioimaging world. This article proposes the usage of properly designed metallic structures that change their fluorescence properties when the dye molecules and the plasmonic nanoparticles interact. The nanostructures design and evaluation processes are based upon genetic algorithms, and they result in an optimal separation distance, orientation angles, and aspect ratio of the metal nanostructure. MDPI 2019-05-31 /pmc/articles/PMC6600714/ /pubmed/31151325 http://dx.doi.org/10.3390/ma12111766 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 Fixler, Dror Tzur, Chen Zalevsky, Zeev Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title | Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title_full | Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title_fullStr | Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title_full_unstemmed | Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title_short | Genetic Algorithm-Based Design for Metal-Enhanced Fluorescent Nanostructures |
title_sort | genetic algorithm-based design for metal-enhanced fluorescent nanostructures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6600714/ https://www.ncbi.nlm.nih.gov/pubmed/31151325 http://dx.doi.org/10.3390/ma12111766 |
work_keys_str_mv | AT fixlerdror geneticalgorithmbaseddesignformetalenhancedfluorescentnanostructures AT tzurchen geneticalgorithmbaseddesignformetalenhancedfluorescentnanostructures AT zalevskyzeev geneticalgorithmbaseddesignformetalenhancedfluorescentnanostructures |