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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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Clustering and self-organization in small-scale natural and artificial systems
Edward Bormashenko1, Alexander A Fedorets2, Mark Frenkel1
1Department of Chemical Engineering, Engineering Sciences Faculty, Ariel University, Ariel 40700, Israel.
Summary
This study explores the unique physical properties of particle clusters, distinct from infinite systems. It reviews mechanisms, dimensionality, and interactions driving cluster formation across various scientific domains.
Area of Science:
- Physics
- Materials Science
- Complex Systems
Background:
- Physical properties of small particle systems (clusters) differ significantly from those of infinite systems.
- Clustering is a fundamental phenomenon observed across diverse scientific fields, from graph theory to biological self-assembly.
Purpose of the Study:
- To present a general approach to understanding and analyzing particle clusters.
- To review the physical mechanisms, dimensional properties, and interactions that govern cluster formation.
- To discuss the role of entropy and energy consumption in biological clustering.
Main Methods:
- Review of theoretical concepts from graph theory applied to physical clusters.
- Survey of physical mechanisms including hydrodynamic and capillary interactions.
- Analysis of dimensional properties and coupling strengths (weakly/strongly coupled).
Main Results:
- Dimensionality fundamentally influences cluster properties.
- Hydrodynamic, capillary, and entropic factors drive cluster formation.
- Biological clustering exemplifies non-equilibrium, multi-scale assembly driven by energy consumption.
Conclusions:
- A unified approach to cluster physics is proposed, integrating diverse mechanisms.
- Understanding cluster dimensionality and interactions is key to predicting their behavior.
- Clustering phenomena, from droplet patterns to biological structures, share underlying principles.
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