Development of a coarse-grain model for the description of the metal oxide-polymer interface from a bottom-up approach

Autohesion Mechanisms at Interfaces Between Random Copolymer Melts: Mesoscopic Simulations with Realistic Coarse-Grained Models

The increase in welding time during the interdiffusion of a pair of non reacting random copolymer melts favors the strength rate of healing at the interface. Furthermore, the diffusion kinetic during the interpenetration of copolymer chains across the interface is strongly dependent on molecular weight. In this paper we perform mesoscopic simulations with realistic coarse grain models to study the autohesion mechanism across the interface between slightly entangled styrene-butadiene random copolymer melts.

Effect of Varying Stiffness and Functionalization on the Interfacial Failure Behavior of Isotactic Polypropylene on Hydroxylated γ-Al2O3 by MD Simulation

This study focuses on polymer-metal joints consisting of isotactic polypropylene (iPP) or iPP grafted with maleic anhydride (iPP-g-MA) and hydroxylated γ-Al₂O₃, which is a model for an oxidized aluminum surface, and investigates the contributions of the Young's moduli of iPP and iPP-g-MA and chemical functionality (MA groups) in iPP-g-MA to the interfacial failure behaviors using the molecular dynamics (MD) simulation method. First, our calculations demonstrated that the tensile strength observed in interfacial failures of the joints increases as Young's modulus of the polymer in the joints increases. This is because a higher stiffness makes it harder for a void to form within the polymer matrix under the applied tensile strain and to reach the interface. Second, in iPP-g-MA-γ-Al₂O₃ joints, MA groups work more effectively to improve the interfacial strength as the Young's modulus of the polymer in the joints increases. For iPP-g-MA with a lower Young's modulus, the polymer molecules are pulled off the surface in a peel mode with increasing normal strain due to their greater flexibility. This results in a gradual removal of the MA groups and thus reduces their contribution. Meanwhile, for a higher Young's modulus, iPP-g-MA molecules at the interface are removed in a tensile mode because of their increased stiffness. This leads to more MA groups required to be detached from the surface at the same time to cause interfacial failure, thus increasing the contributions of the MA groups.

Approaches and Perspective of Coarse-Grained Modeling and Simulation for Polymer-Nanoparticle Hybrid Systems

Molecular modeling and simulations have emerged as effective and indispensable tools to characterize polymeric systems. They provide fundamental and essential insights to design a product of the required properties and to improve the understanding of a phenomenon at the molecular level for a particular system. The polymer-nanoparticle hybrids are materials with outstanding properties and correspondingly large applications whose study has benefited from this new paradigm. However, despite the significant expansion of modern day computational powers, investigation of the long time and large length scale phenomenon in polymeric and polymer-nanoparticle systems is still a challenging task to complete through all-atom molecular dynamics (AA-MD) simulations. To circumvent this problem, a variety of coarse-grained (CG) models have been proposed, ranging from the generic CG models for qualitative properties predictions to more realistic chemically specific CG models for quantitative properties predictions. These CG models have already delivered some success stories in the study of several spatial and temporal evolutions of many processes. Some of these studies were beyond the feasibility of traditional atomistic resolution models due to either the size or the time constraints. This review captures the different types of popular CG approaches that are utilized in the investigation of the microscopic behavior of polymer-nanoparticle hybrid systems. The rationale of this article is to furnish an overview of the popular CG approaches and their applications, to review several important and most recent developments, and to delineate the perspectives on future directions in the field.

Consistent and Transferable Force Fields for Statistical Copolymer Systems at the Mesoscale

The statistical trajectory matching (STM) method was applied successfully to derive coarse grain (CG) models for bulk properties of homopolymers. The extension of the methodology for building CG models for statistical copolymer systems is much more challenging. We present here the strategy for developing CG models for styrene-butadiene-rubber, and we compare the quality of the resulting CG force fields on the structure and thermodynamics at different chemical compositions. The CG models are used through the use of a genuine mesoscopic method called the dissipative particle dynamics method and compared to high-resolution molecular dynamics simulations. We conclude that the STM method is able to produce coarse-grained potentials that are transferable in composition by using only a few reference systems. Additionally, this methodology can be applied on any copolymer system.

Rheological properties of polymer chains at a copper oxide surface: Impact of the chain length, surface coverage, and grafted polymer shape

We employ a recently derived semirealistic set of coarse-grained interactions to simulate polymer brushes of cis-1,4-polybutadiene grafted on a cuprous-oxide surface within the framework of dissipative particle dynamics. We consider two types of brushes, I and Y, that differ in the way they are connected to the surface. Our model explores the impact of free polymer chain length, grafting density of the brush, and imposed shear rate on the structural and dynamic properties of complex metal oxide polymer interfaces.

Assessing the derivation of time parameters from branched polymer coarse-grain model

The parameterization of rheological models for polymers is often obtained from experiments via the top-down approach. This procedure allows us to determine good fitting parameters for homogeneous materials but is less effective for polymer mixtures. From a molecular simulation point of view, the timescales needed to derive those parameters are often accessed through the use of coarse-grain potentials. However, these potentials are often derived from linear model systems and the transferability to a more complex structure is not straightforward. Here, we verify the transferability of a potential computed from linear polymer simulations to more complex molecular shapes and present a type of analysis, which was recently formulated in the framework of a tube theory, to a coarse-grain molecular approach in order to derive the input parameters for a rheological model. We describe the different behaviors arising from the local topological structure of molecular sub-units. Coarse-grain models and mean-field based tube theory for polymers form a powerful combination with potentially important applications.

Backbone oriented anisotropic coarse grains for efficient simulations of polymers

Despite the fact that anisotropic particles have been introduced to describe molecular interactions for decades, they have been poorly used for polymers because of their computing time overhead and the absence of a relevant proof of their impact in this field. We first report a method using anisotropic beads for polymers, which solves the computing time issue by considering that beads keep their principal orientation alongside the mean local backbone vector of the polymer chain, avoiding the computation of torques during the dynamics. Applying this method to a polymer bulk, we study the effect of anisotropic interactions vs isotropic ones for various properties such as density, pressure, topology of the chain network, local structure, and orientational order. We show that for different classes of potentials traditionally used in molecular simulations, those backbone oriented anisotropic beads can solve numerous issues usually encountered with isotropic interactions. We conclude that the use of backbone oriented anisotropic beads is a promising approach for the development of realistic coarse-grained potentials for polymers.

Multi-scale modeling of the polymer-filler interaction

We report mesoscopic simulations of the interaction between a silica nanoparticle and cis-1,4-polybutadiene chains with realistic coarse-(CG) grained models. The CG models are obtained with a bottom-up Bayesian method based on trajectory matching of atomistic configurations of the system. We then investigate the structural properties of the interfacial region as a function of the grafting density and polymer chain length. We take advantage of the realistic CG models to explore the dynamics of the nanoparticle over a period of 10 microseconds. We show that the dynamics of the nanoparticle is affected by the grafting density and the polymer chain length of the grafted chains.