Coarse-grained molecular-dynamics simulations of nanoparticle diffusion in polymer nanocomposites

Volgin, Igor V.; Larin, Sergey V.; Lyulin, Alexey V.; Lyulin, Sergey V.

doi:10.1016/j.polymer.2018.04.058

Cited by 35 publications

(23 citation statements)

References 44 publications

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“…We are therefore using a coarse-grained model that is known to capture the relevant dynamics and structure of simple polymeric systems and detailed enough to study the effect of charge sequence on material behavior. There are a few attempts that aim at coarse-graining similar but uncharged systems based on atomistic simulation [16,[44][45][46].…”

Section: Methodsmentioning

confidence: 99%

Polymer Conformations, Entanglements and Dynamics in Ionic Nanocomposites: A Molecular Dynamics Study

et al. 2020

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We investigate nanoparticle (NP) dispersion, polymer conformations, entanglements and dynamics in ionic nanocomposites. To this end, we study nanocomposite systems with various spherical NP loadings, three different molecular weights, two different Bjerrum lengths, and two types of charge-sequenced polymers by means of molecular dynamics simulations. NP dispersion can be achieved in either oligomeric or entangled polymeric matrices due to the presence of electrostatic interactions. We show that the overall conformations of ionic oligomer chains, as characterized by their radii of gyration, are affected by the presence and the amount of charged NPs, while the dimensions of charged entangled polymers remain unperturbed. Both the dynamical behavior of polymers and NPs, and the lifetime and amount of temporary crosslinks, are found to depend on the ratio between the Bjerrum length and characteristic distance between charged monomers. Polymer–polymer entanglements start to decrease beyond a certain NP loading. The dynamics of ionic NPs and polymers is very different compared with their non-ionic counterparts. Specifically, ionic NP dynamics is getting enhanced in entangled matrices and also accelerates with the increase of NP loading.

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Section: Methodsmentioning

confidence: 99%

Polymer Conformations, Entanglements and Dynamics in Ionic Nanocomposites: A Molecular Dynamics Study

et al. 2020

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“…Ohkuma and Kremer [102] demonstrated that both the stress relaxation time scale and shear rate is recovered through time rescaling for two different models of cis-polyisoprene, with and without the incorporation of a pressure correction to the conservative force. More recently, Volgin et al [103] investigated time rescalings for nanoparticle diffusion in a polyimide-based melt employing both one-and three-site per monomer representations. Interestingly, they found that while the uniform time rescaling breaks down for intermediate time scales, taking into account the local viscosity of the polymer chain segments (whose size is comparable with the nanoparticle size) rescues the time-rescaling approach.…”

Section: A Polymersmentioning

confidence: 99%

Recent Progress towards Chemically-Specific Coarse-Grained Simulation Models with Consistent Dynamical Properties

Rudzinski

2019

Computation

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Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes, bottom-up CG models are systematically constructed from a higher-resolution model to retain a high level of chemical specificity. The removal of degrees of freedom from the system modifies the relationship between the relative time scales of distinct dynamical processes through both a loss of friction and a "smoothing" of the free-energy landscape. While these effects typically result in faster dynamics, decreasing the computational expense of the model, they also obscure the connection to the true dynamics of the system. The lack of consistent dynamics is a serious limitation for CG models, which not only prevents quantitatively accurate predictions of dynamical observables but can also lead to qualitatively incorrect descriptions of the characteristic dynamical processes. With many methods available for optimizing the structural and thermodynamic properties of chemically-specific CG models, recent years have seen a stark increase in investigations addressing the accurate description of dynamical properties generated from CG simulations. In this review, we present an overview of these efforts, ranging from bottom-up parametrizations of generalized Langevin equations to refinements of the CG force field based on a Markov state modeling framework. We aim to make connections between seemingly disparate approaches, while laying out some of the major challenges as well as potential directions for future efforts.

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“…58,131,189,[247][248][249][250][251][252][253] The extent of time-rescaling required can be sensitive to CG mapping in a manner that is not strictly set by the CG resolution (Figure 2D). 196 In a study on polymer nanocomposites, Volgin et al demonstrated how CG resolution of the polymer can dictate the dynamical behavior of other components, 254 indicating that the success of time-rescaling may depend on chemical heterogeneity present in the system. Timedependent rescaling relationships have also been deployed for predicting viscoelastic properties from bottom-up CG models.…”

Section: Incorporating Dynamicsmentioning

confidence: 99%

Chemically specific coarse‐graining of polymers: Methods and prospects

Dhamankar

Webb

2021

Journal of Polymer Science

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Coarse-grained (CG) modeling is an invaluable tool for the study of polymers and other soft matter systems due to the span of spatiotemporal scales that typify their physics and behavior. Given continuing advancements in experimental synthesis and characterization of such systems, there is ever greater need to leverage and expand CG capabilities to simulate diverse soft matter systems with chemical specificity. In this review, we discuss essential modeling techniques, bottom-up coarse-graining methodologies, and outstanding challenges for the chemically specific CG modeling of polymer-based systems. This methodologically oriented discussion is complemented by representative literature examples for polymer simulation; we also offer some advisory practical considerations that should be useful for new researchers. Given its growing importance in the modeling and polymer science community, we further highlight some recent applications of machine learning that enhance CG modeling strategies. Overall, this review provides comprehensive discussion of methods and prospects for the chemically specific coarse-graining of polymers.

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Coarse-grained molecular-dynamics simulations of nanoparticle diffusion in polymer nanocomposites

Cited by 35 publications

References 44 publications

Polymer Conformations, Entanglements and Dynamics in Ionic Nanocomposites: A Molecular Dynamics Study

Polymer Conformations, Entanglements and Dynamics in Ionic Nanocomposites: A Molecular Dynamics Study

Recent Progress towards Chemically-Specific Coarse-Grained Simulation Models with Consistent Dynamical Properties

Chemically specific coarse‐graining of polymers: Methods and prospects

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