Elsevier

Progress in Polymer Science

Volume 33, Issue 2, February 2008, Pages 191-269
Progress in Polymer Science

Multiscale modeling and simulation of polymer nanocomposites

https://doi.org/10.1016/j.progpolymsci.2007.09.002Get rights and content

Abstract

Polymer nanocomposites offer a wide range of promising applications because of their much enhanced properties arising from the reinforcement of nanoparticles. However, further development of such nanomaterials depends on the fundamental understanding of their hierarchical structures and behaviors which requires multiscale modeling and simulation strategies to provide seamless coupling among various length and time scales. In this review, we first introduce some computational methods that have been applied to polymer nanocomposites, covering from molecular scale (e.g., molecular dynamics, Monte Carlo), microscale (e.g., Brownian dynamics, dissipative particle dynamics, lattice Boltzmann, time-dependent Ginzburg–Landau method, dynamic density functional theory method) to mesoscale and macroscale (e.g., micromechanics, equivalent-continuum and self-similar approaches, finite element method). Then, we discuss in some detail their applications to various aspects of polymer nanocomposites, including the thermodynamics and kinetics of formation, molecular structure and dynamics, morphology, processing behaviors, and mechanical properties. Finally, we address the importance of multiscale simulation strategies in the understanding and predictive capabilities of polymer nanocomposites in which few studies have been reported. The present review aims to summarize the recent advances in the fundamental understanding of polymer nanocomposites reinforced by nanofillers (e.g., spherical nanoparticles, nanotubes, clay platelets) and stimulate further research in this area.

Introduction

Polymer materials reinforced with nanoparticles (e.g., nanosphere, nanotube, clay platelet) have recently received tremendous attention in both scientific and industrial communities due to their extraordinary enhanced properties [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. However, from the experimental point of view, it is a great challenge to characterize the structure and to manipulate the fabrication of polymer nanocomposites. The development of such materials is still largely empirical and a finer degree of control of their properties cannot be achieved so far. Therefore, computer modeling and simulation will play an ever-increasing role in predicting and designing material properties, and guiding such experimental work as synthesis and characterization. For polymer nanocomposites, computer modeling and simulation are especially useful in addressing the following fundamental issues:

  • 1.

    the thermodynamics and kinetics of the formation of polymer nanocomposites;

  • 2.

    the hierarchical characteristics of the structure and dynamics of polymer nanocomposites ranging from molecular scale, microscale to mesoscale and macroscale, in particular, the molecular structures and dynamics at the interface between nanoparticles and polymer matrix;

  • 3.

    the dependence of polymer rheological behavior on the addition of nanoparticles, which is useful in optimizing processing conditions; and

  • 4.

    the molecular origins of the reinforcement mechanisms of nanoparticles in polymer nanocomposites.

The purpose of this review is to discuss the application of modeling and simulation techniques to polymer nanocomposites. This includes a broad subject covering methodologies at various length and time scales and many aspects of polymer nanocomposites. We organize the review as follows. In Section 2, we introduce briefly the computational methods used so far for the systems of polymer nanocomposites which can be roughly divided into three types: molecular scale methods (e.g., molecular dynamics (MD), Monte Carlo (MC)), microscale methods (e.g., Brownian dynamics (BD), dissipative particle dynamics (DPD), lattice Boltzmann (LB), time-dependent Ginzburg–Lanau method, dynamic density functional theory (DFT) method), and mesoscale and macroscale methods (e.g., micromechanics, equivalent-continuum and self-similar approaches, finite element method (FEM)). We do not aim to provide a detailed description of each method but its basic principles, strengths and weaknesses, and potential applications. Interesting readers can refer to relevant books, reviews and research articles for details. In Section 3, we discuss in detail the applications of these modeling and simulation methods in some specific aspects of polymer nanocomposites, including the thermodynamics and kinetics of the formation, molecular structure and dynamics, morphologies (i.e., phase behaviors), rheological and processing behaviors, and mechanical properties. We pay more attention to clay-based polymer nanocomposites because of their importance in polymer nanocomposites and our own research interests. Of course, we also refer to research activities in polymer systems reinforced by nanospheres and nanotubes, an area developed rapidly in the past few years. In Section 4, we highlight the importance of multiscale strategies of modeling and simulation in understanding and predicting the hierarchical structure and behaviors arising from the polymer and nanoparticle together with the properties observed at various scales. We discuss the current applications of some multiscale methods in polymer nanocomposites. Finally, we conclude the review by emphasizing the current challenges and future research directions.

Section snippets

Molecular scale methods

The modeling and simulation methods at molecular level usually employ atoms, molecules or their clusters as the basic units considered. The most popular methods include molecular mechanics (MM), MD and MC simulation. Modeling of polymer nanocomposites at this scale is predominantly directed toward the thermodynamics and kinetics of the formation, molecular structure and interactions. The diagram in Fig. 1 describes the equation of motion for each method and the typical properties predicted from

Nanocomposite thermodynamics

The formation of stable nanocomposites depends on the thermodynamics of the multicomponent mixture concerned. In the case of polymer–nanoparticle mixtures, their final structures are strongly influenced by the characteristics of nanoparticles (e.g., size, shape, aspect ratio), polymer (e.g., molecular weight, structure, polarity and its compatibility with the particle), and surfactant if employed. The remarkably improved properties are usually observed from the structure in which nanoparticles

Challenges

A main goal of computational materials science is the rapid and accurate prediction of new materials and their new properties and features, which is very difficult to achieve with traditional modeling and simulation methods at a single length and time scale with the current computer power [292], [293], [294], [295], [296], [297]. Therefore, it is expected to use the multiscale simulation strategies to bridge the models and simulation techniques across a broad range of length and time scales to

Concluding remarks

The development of polymer nanocomposites necessitates a comprehensive understanding of the phenomena at different time and length scales. In the past decade or so, this need has significantly stimulated the development of computer modeling and simulation, either as a complementary or alternative technique to experimentation. In this connection, many traditional simulation techniques (e.g., MC, MD, BD, LB, Ginzburg–Landau theory, micromechanics and FEM) have been employed, and some novel

Acknowledgment

The authors would like to thank Australian Research Council (ARC) for the finanical support through the ARC Centre of Excellence for Functional Nanomaterials.

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