Morphology selection kinetics of crystallization in a sphere

Chen, Yanshuang; Yao, Zhenwei; Tang, Shixiang; Tong, Hua; Yanagishima, Taiki; Tanaka, Hajime; Tan, Peng

doi:10.1038/s41567-020-0991-9

Cited by 34 publications

(32 citation statements)

References 50 publications

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“…The formation process of the icosahedral cluster is studied with a computer simulation. [ 26,34,35 ] [ 40,41 ] The evaporation of water and the resultant increase in the volume fraction ρ of the colloidal particle are the primary driving forces. Nijs et al.…”

Section: Discussionmentioning

confidence: 99%

Optical Characterization of Large Icosahedral Colloidal Clusters

Ohnuki

Kunimoto

Takeoka

et al. 2022

Part & Part Syst Charact

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Colloidal particles form a face‐centered‐cubic (FCC) lattice on crystallization; however, recent studies have indicated that the cluster with the icosahedral symmetry can be formed under spherical confinement. The icosahedral cluster appears only when the number of constituent particles is small because the FCC lattice is favored thermodynamically for a bulk colloidal crystal. This paper reports the observation of a large icosahedral colloidal cluster comprising ≈4.9 × 105 colloidal particles, which is considerably larger than the previously reported number. This large icosahedral cluster clearly exhibits the triangular reflection pattern that corresponds to one face of the icosahedron. Further, an oblique illumination with sample rotation is found to be an effective method to characterize the icosahedral cluster optically. In this study, larger colloidal particles are used than those in previous studies. It is hypothesized that slow reconfiguration during the evaporation process can result in the formation of a large icosahedral cluster due to the large particle size.

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Section: Discussionmentioning

confidence: 99%

Optical Characterization of Large Icosahedral Colloidal Clusters

Ohnuki

Kunimoto

Takeoka

et al. 2022

Part & Part Syst Charact

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“…While crystallization has been exhaustively studied through experiments, theory, and simulations, a lot of its aspects remain poorly understood, especially at the level of atoms and molecules. The complexity of the phenomenon increases appreciably when interfacial or surface effects and spatial heterogeneity are considered, beyond the reference bulk case [ 1 , 2 , 3 , 4 ]. Further intricacy is added by constraints imposed by inherent chain connectivity, as in the case of macromolecular systems, which are additionally characterized by a wide range of characteristic time and length scales, the global ones being dominated by the presence of entanglements [ 5 , 6 , 7 , 8 , 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Entropy-Driven Heterogeneous Crystallization of Hard-Sphere Chains under Unidimensional Confinement

et al. 2021

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We investigate, through Monte Carlo simulations, the heterogeneous crystallization of linear chains of tangent hard spheres under confinement in one dimension. Confinement is realized through flat, impenetrable, and parallel walls. A wide range of systems is studied with respect to their average chain lengths (N = 12 to 100) and packing densities (ϕ = 0.50 to 0.61). The local structure is quantified through the Characteristic Crystallographic Element (CCE) norm descriptor. Here, we split the phenomenon into the bulk crystallization, far from the walls, and the projected surface crystallization in layers adjacent to the confining surfaces. Once a critical volume fraction is met, the chains show a phase transition, starting from regions near the hard walls. The established crystal morphologies consist of alternating hexagonal close-packed or face-centered cubic layers with a stacking direction perpendicular to the confining walls. Crystal layer perfection is observed with an increasing concentration. As in the case of the unconstrained phase transition of athermal polymers at high densities, crystal nucleation and growth compete with the formation of sites of a fivefold local symmetry. While surface crystallites show perfection with a predominantly triangular character, the morphologies of square crystals or of a mixed type are also formed. The simulation results show that the rate of perfection of the surface crystallization is not significantly faster than that of the bulk crystallization.

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“…In the spherical one, the packing density changes from 0.30 (leftmost panel) up to 0.50 (rightmost panel). Reaching such densities allows the investigation of crystal nucleation and the growth of chain systems and eventually the comparison with monomeric analogs, as recently reported in [110,111].…”

Section: Polymers Under Confinementmentioning

confidence: 96%

Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions

Herranz

Martínez-Fernández

Ramos

et al. 2021

IJMS

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We present Simu-D, a software suite for the simulation and successive identification of local structures of atomistic systems, based on polymers, under extreme conditions, in the bulk, on surfaces, and at interfaces. The protocol is built around various types of Monte Carlo algorithms, which include localized, chain-connectivity-altering, identity-exchange, and cluster-based moves. The approach focuses on alleviating one of the main disadvantages of Monte Carlo algorithms, which is the general applicability under a wide range of conditions. Present applications include polymer-based nanocomposites with nanofillers in the form of cylinders and spheres of varied concentration and size, extremely confined and maximally packed assemblies in two and three dimensions, and terminally grafted macromolecules. The main simulator is accompanied by a descriptor that identifies the similarity of computer-generated configurations with respect to reference crystals in two or three dimensions. The Simu-D simulator-descriptor can be an especially useful tool in the modeling studies of the entropy- and energy-driven phase transition, adsorption, and self-organization of polymer-based systems under a variety of conditions.

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Morphology selection kinetics of crystallization in a sphere

Cited by 34 publications

References 50 publications

Optical Characterization of Large Icosahedral Colloidal Clusters

Optical Characterization of Large Icosahedral Colloidal Clusters

Entropy-Driven Heterogeneous Crystallization of Hard-Sphere Chains under Unidimensional Confinement

Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions

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