Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/75575
Title: Self-assembly of polymer-like structures of magnetic colloids: Langevin dynamics study of basic topologies
Authors: Rozhkov, D. A.
Pyanzina, E. S.
Novak, E. V.
Cerdà, J. J.
Sintes, T.
Ronti, M.
Sánchez, P. A.
Kantorovich, S. S.
Issue Date: 2018
Publisher: Taylor and Francis Ltd.
Citation: Self-assembly of polymer-like structures of magnetic colloids: Langevin dynamics study of basic topologies / D. A. Rozhkov, E. S. Pyanzina, E. V. Novak et al. // Molecular Simulation. — 2018. — Vol. 44. — Iss. 6. — P. 507-515.
Abstract: We study the self-assembly of colloidal magnetic particles permanently cross-linked into polymer-like structures with different topologies, that we call supracolloidal magnetic polymers (SMPs). In order to understand the influence of the interparticle permanent links, we investigate SMPs holding the main topologies observed in the self-assembly of non-cross-linked magnetic particles via grand canonical Monte Carlo simulations: chains, rings and simple branched structures. Here, using molecular dynamics simulations, we focus on systems of SMP pairs. Our results evidence that the presence of crosslinkers leads to the formation of new types of aggregates, not previously observed for individual magnetic colloids. © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Keywords: CROSS-LINKED POLYMER-LIKE STRUCTURES
LANGEVIN DYNAMICS SIMULATIONS
MAGNETIC COLLOIDAL PARTICLES
SELF-ASSEMBLY
COLLOIDS
CROSSLINKING
INTELLIGENT SYSTEMS
MAGNETISM
MOLECULAR DYNAMICS
MONTE CARLO METHODS
POLYMERS
SHAPE MEMORY EFFECT
TOPOLOGY
BRANCHED STRUCTURES
COLLOIDAL PARTICLE
CROSS-LINKED POLYMERS
GRAND CANONICAL MONTE CARLO SIMULATION
LANGEVIN DYNAMICS
MAGNETIC PARTICLE
MOLECULAR DYNAMICS SIMULATIONS
POLYMER-LIKE STRUCTURES
SELF ASSEMBLY
URI: http://elar.urfu.ru/handle/10995/75575
Access: info:eu-repo/semantics/openAccess
RSCI ID: 35479321
SCOPUS ID: 85030159243
WOS ID: 000424947700009
PURE ID: 6512803
ISSN: 0892-7022
DOI: 10.1080/08927022.2017.1378815
Sponsorship: This research has been supported by the Russian Science Foundation [grant number 17-72-10145]. J.J.C. and T.S. acknowledge funding from a grant awarded by the Conselleria d’Innovació, Recerca i Turisme del Govern de les Illes Balears and the European Social Fund (ESF). T.S. also acknowledges financial support from the Spanish Ministerio de Economía y Competi-tividad and the European Regional Development Fund, [Project number FIS20015-63628-C2-2-R] (AEI/FEDER, UE). P.A.S and S.S.K acknowledge support from the Austrian Research Fund (FWF) [START-Projekt Y 627-N27]. S.S.K. also acknowledges support from the European Commission ETN-COLLDENSE [H2020-MSCA-ITN-2014], [grant number 642774]. The authors would like to thank F. Sciortino for his valuable contribution to the GCMC simulation results.
RSCF project card: 17-72-10145
CORDIS project card: 642774
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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