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Clustering and self-organization in small-scale natural and artificial systems
Author(s) -
Edward Bormashenko,
Alexander A. Fedorets,
Mark Frenkel,
Leonid A. Dombrovsky,
Michael Nosonovsky
Publication year - 2020
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2019.0443
Subject(s) - cluster analysis , cluster (spacecraft) , curse of dimensionality , statistical physics , self organization , entropy (arrow of time) , computer science , physics , artificial intelligence , thermodynamics , programming language
Physical properties of clusters, i.e. systems composed of a ‘small’ number of particles, are qualitatively different from those of infinite systems. The general approach to the problem of clustering is suggested. Clusters, as they are seen in the graphs theory, are discussed. Various physical mechanisms of clustering are reviewed. Dimensional properties of clusters are addressed. The dimensionality of clusters governs to a great extent their properties. Weakly and strongly coupled clusters are discussed. Hydrodynamic and capillary interactions giving rise to clusters formation are surveyed. Levitating droplet clusters, turbulent clusters and droplet clusters responsible for the breath-figures self-assembly are considered. Entropy factors influencing clustering are considered. Clustering in biological systems results in non-equilibrium multi-scale assembly, where at each scale, self-driven components come together by consuming energy in order to form the hierarchical structure. This article is part of the theme issue ‘Bioinspired materials and surfaces for green science and technology (part 3)’.

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