Self-Assembly Kinetics of Amphiphilic Dendritic Copolymers

Zhang, Cuiyun; Fan, You; Zhang, Yunyi; Yu, Cong; Li, Hongfei; Chen, Yu; Hamley, Ian W.; Jiang, Shichun

doi:10.1021/acs.macromol.6b02331

Cited by 5 publications

(10 citation statements)

References 44 publications

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“…S3). The Rh of the micelles increases with the unimer concentration in the solvent mixture of chloroform and methanol as previously reported [22]. However, in the present system, the influence of the unimer concentration on the micelle size is different.…”

Section: The Micellization Kinetics Of the Adpssupporting

confidence: 83%

“…In this work, in order to track the aggregation processes from unimers to the final equilibrium micelles of the ADPs, after filtration the temperature was controlled to a critical value at which all the ADPs can undergo micellization. Also, in the previous reports [22], the influence of concentration on the relaxation times is contrary to the block copolymers and by 6 analysing the micelle concentration, we found that the increasing relaxation time is caused by the decreasing micelle concentration with increasing unimer concentration.…”

Section: Introductionmentioning

confidence: 39%

“…In our previous reports [22], we have investigated the micellization processes of the ADPs by mixing of a selective solvent with a common solvent, in which two steps could be distinguished clearly and this is the first time the detailed micellization kinetics has been studied. In the first step the small micelles quickly associate to form larger micelles and in the second step accompanying the fission and fusion of micelles, the aggregation approaches dynamical equilibrium.…”

Section: Introductionmentioning

confidence: 99%

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Investigations on the micellization of amphiphilic dendritic copolymers: From unimers to micelles

Zhang

Zhou

et al. 2018

Journal of Colloid and Interface Science

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Since the micellization kinetics is influenced by polymer structure, the spherical three-dimensional topology of amphiphilic dendritic copolymers (ADPs) which hinders the phase separation during micellization is assumed to make the micellization kinetics different. In the literatures, most of the attention has been paid to the morphology transition or the morphology at equilibrium and the micellization kinetics of ADPs is rarely reported. In this study, the micellization processes of amphiphilic dendritic copolymers from unimers to the final equilibrium micelles were monitored by laser light scattering. Based on the closed association mechanism, the thermodynamics of micellization was analysed. The negative thermodynamic quantities indicate that the micellization of ADPs is driven by enthalpy. Based on the change of scattering intensity and hydrodynamic radius (R) with time, the detailed micellization kinetics was analysed, which contains two steps. By controlling the temperature and type of solvent, a system in which the concentration has little influence on R is obtained. The relaxation times of the two steps decrease with concentration, indicating that at higher concentration the rate of micellization is quicker. With the increasing mass fraction of the hydrophobic part, the relaxation times decrease and the driving force of micellization increases.

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Section: The Micellization Kinetics Of the Adpssupporting

confidence: 83%

Section: Introductionmentioning

confidence: 39%

Section: Introductionmentioning

confidence: 99%

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Investigations on the micellization of amphiphilic dendritic copolymers: From unimers to micelles

Zhang

Zhou

et al. 2018

Journal of Colloid and Interface Science

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“…The dynamics of phase transitions and morphology formation in inhomogeneous polymeric systems is of fundamental as well as great practical interest [1][2][3][4][5][6]. Due to the large length and time scales on which these processes take place, simulation studies usually rely on coarse-grained models.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Density Functional Theories for Inhomogeneous Polymer Systems Compared to Brownian Dynamics Simulations

Schmid

2017

Macromolecules

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Dynamic density functionals (DDFs) are popular tools for studying the dynamical evolution of inhomogeneous polymer systems. Here, we present a systematic evaluation of a set of diffusive DDF theories by comparing their predictions with data from particle-based Brownian dynamics (BD) simulations for two selected problems: Interface broadening in compressible A/B homopolymer blends after a sudden change of the incompatibility parameter, and microphase separation in compressible A:B diblock copolymer melts. Specifically, we examine (i) a local dynamics model, where monomers are taken to move independently from each other, (ii) a nonlocal "chain dynamics" model, where monomers move jointly with correlation matrix given by the local chain correlator, and (iii,iv) two popular approximations to (ii), namely (iii) the Debye dynamics model, where the chain correlator is approximated by its value in a homogeneous system, and (iv) the computationally efficient "external potential dynamics" (EPD) model. With the exception of EPD, the value of the compressibility parameter has little influence on the results. In the interface broadening problem, the chain dynamics model reproduces the BD data best. However, the closely related EPD model produces large spurious artefacts. These artefacts disappear when the blend system becomes incompressible. In the microphase separation problem, the predictions of the nonlocal models (ii-iv) agree with each other and significantly overestimate the ordering time, whereas the local model (i) underestimates it. We attribute this to the multiscale character of the ordering process, which involves both local and global chain rearrangements. To account for this, we propose a mixed local/nonlocal DDF scheme which quantitatively reproduces all BD simulation data considered here.

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“…The DPD method was proven to be an effective mesoscopic simulation tool to study fluid events occurring at millisecond timescales and micrometer length scales via by tracking the motion of coarse-grained particles (composed of a group of atoms or molecules). Many researchers studied the thermodynamic and morphological behavior of polymers using the DPD method, for example, self-assembly of dendritic copolymers [25][26][27], micelle fusion or vesicle formation [28,29], and nanocomposite systems [30][31][32][33].…”

Section: Dpd With the Slip-spring Modelmentioning

confidence: 99%

Performance of Coarse Graining in Estimating Polymer Properties: Comparison with the Atomistic Model

2020

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Combining atomistic and coarse-grained (CG) models is a promising approach for quantitative prediction of polymer properties. However, the gaps between the length and time scales of atomistic and CG models still need to be bridged. Here, the scale gaps of the atomistic model of polyethylene melts, the bead-spring Kremer-Grest model, and dissipative particle dynamics with the slip-spring model were investigated. A single set of spatial and temporal scaling factors was determined between the atomistic model and each CG model. The results of the CG models were rescaled using the set of scaling factors and compared with those of the atomistic model. For each polymer property, a threshold value indicating the onset of static or dynamic universality of polymers was obtained. The scaling factors also revealed the computational efficiency of each CG model with respect to the atomistic model. The performance of the CG models of polymers was systematically evaluated in terms of both the accuracy and computational efficiency.

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Self-Assembly Kinetics of Amphiphilic Dendritic Copolymers

Cited by 5 publications

References 44 publications

Investigations on the micellization of amphiphilic dendritic copolymers: From unimers to micelles

Investigations on the micellization of amphiphilic dendritic copolymers: From unimers to micelles

Dynamic Density Functional Theories for Inhomogeneous Polymer Systems Compared to Brownian Dynamics Simulations

Performance of Coarse Graining in Estimating Polymer Properties: Comparison with the Atomistic Model

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