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Characterization of Self-Assembled 2D Patterns with Voronoi Entropy
The Voronoi entropy is a mathematical tool for quantitative characterization of the orderliness of points distributed on a surface. The tool is useful to study various surface self-assembly processes. We provide the historical background, from Kepler and Descartes to our days, and discuss topologica...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512542/ https://www.ncbi.nlm.nih.gov/pubmed/33266680 http://dx.doi.org/10.3390/e20120956 |
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author | Bormashenko, Edward Frenkel, Mark Vilk, Alla Legchenkova, Irina Fedorets, Alexander A. Aktaev, Nurken E. Dombrovsky, Leonid A. Nosonovsky, Michael |
author_facet | Bormashenko, Edward Frenkel, Mark Vilk, Alla Legchenkova, Irina Fedorets, Alexander A. Aktaev, Nurken E. Dombrovsky, Leonid A. Nosonovsky, Michael |
author_sort | Bormashenko, Edward |
collection | PubMed |
description | The Voronoi entropy is a mathematical tool for quantitative characterization of the orderliness of points distributed on a surface. The tool is useful to study various surface self-assembly processes. We provide the historical background, from Kepler and Descartes to our days, and discuss topological properties of the Voronoi tessellation, upon which the entropy concept is based, and its scaling properties, known as the Lewis and Aboav–Weaire laws. The Voronoi entropy has been successfully applied to recently discovered self-assembled structures, such as patterned microporous polymer surfaces obtained by the breath figure method and levitating ordered water microdroplet clusters. |
format | Online Article Text |
id | pubmed-7512542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75125422020-11-09 Characterization of Self-Assembled 2D Patterns with Voronoi Entropy Bormashenko, Edward Frenkel, Mark Vilk, Alla Legchenkova, Irina Fedorets, Alexander A. Aktaev, Nurken E. Dombrovsky, Leonid A. Nosonovsky, Michael Entropy (Basel) Review The Voronoi entropy is a mathematical tool for quantitative characterization of the orderliness of points distributed on a surface. The tool is useful to study various surface self-assembly processes. We provide the historical background, from Kepler and Descartes to our days, and discuss topological properties of the Voronoi tessellation, upon which the entropy concept is based, and its scaling properties, known as the Lewis and Aboav–Weaire laws. The Voronoi entropy has been successfully applied to recently discovered self-assembled structures, such as patterned microporous polymer surfaces obtained by the breath figure method and levitating ordered water microdroplet clusters. MDPI 2018-12-11 /pmc/articles/PMC7512542/ /pubmed/33266680 http://dx.doi.org/10.3390/e20120956 Text en © 2018 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 | Review Bormashenko, Edward Frenkel, Mark Vilk, Alla Legchenkova, Irina Fedorets, Alexander A. Aktaev, Nurken E. Dombrovsky, Leonid A. Nosonovsky, Michael Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title | Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title_full | Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title_fullStr | Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title_full_unstemmed | Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title_short | Characterization of Self-Assembled 2D Patterns with Voronoi Entropy |
title_sort | characterization of self-assembled 2d patterns with voronoi entropy |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512542/ https://www.ncbi.nlm.nih.gov/pubmed/33266680 http://dx.doi.org/10.3390/e20120956 |
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