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Computational Modeling of Nanoparticle Coalescence
Author(s) -
Grammatikopoulos Panagiotis,
Sowwan Mukhles,
Kioseoglou Joseph
Publication year - 2019
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.201900013
Subject(s) - coalescence (physics) , nanoparticle , nanotechnology , nanoclusters , fractal dimension , materials science , cluster (spacecraft) , fractal , computer science , chemical physics , physics , mathematics , mathematical analysis , astrobiology , programming language
The coalescence of nanoclusters fabricated in the gas phase is a fundamental growth mechanism determining cluster shapes, sizes, compositions, and structures, with resultant effects on practically all of their physical and chemical properties. Furthermore, coalescence can affect properties of larger structures that consist of nanoparticles as their elementary building blocks, such as the fractal dimension of cluster aggregates and the porosity and conductance of thin films. Therefore, it comes as no surprise that a great body of research, both experimental and theoretical, has focused on nanoparticle coalescence over the course of the past few decades. This review attempts to summarize the most important recent results from computational studies on nanoparticle coalescence and draw parallels between theoretical and experimental findings. The approach used here aspires to explain nanoparticle coalescence within the framework of a single intuitive narrative by integrating previous results obtained using various methods by the authors and others. Simultaneously, it is discussed where understanding and controlling (i.e., enhancing or inhibiting) nanoparticle coalescence can have great technological interest.

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