Modeling and Prediction of Polymer Nanocomposite Properties (Polymer Nano-, Micro- and Macrocomposites)

Modeling and Prediction of Polymer Nanocomposite Properties (Polymer Nano-, Micro- and Macrocomposites)

Language: English

Pages: 320

ISBN: 3527331506

Format: PDF / Kindle (mobi) / ePub

The book series 'Polymer Nano-, Micro- and Macrocomposites' provides complete and comprehensive information on all important
aspects of polymer composite research and development, including, but not limited to synthesis, filler modification, modeling,
characterization as well as application and commercialization issues. Each book focuses on a particular topic and gives a balanced in-depth overview of the respective subfi eld of polymer composite science and its relation to industrial applications. With the books the readers obtain dedicated resources with information relevant to their research, thereby helping to save time and money.

This book lays the theoretical foundations and emphasizes the close connection between theory and experiment to optimize models
and real-life procedures for the various stages of polymer composite development. As such, it covers quantum-mechanical approaches to
understand the chemical processes on an atomistic level, molecular mechanics simulations to predict the filler surface dynamics, finite
element methods to investigate the macro-mechanical behavior, and thermodynamic models to assess the temperature stability. The whole is
rounded off by a look at multiscale models that can simulate properties at various length and time scales in one go - and with predictive

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constant rate of relaxation is exhibited for the initial fraction of attached monomers per chain close to the equilibrium value, that is, ϕad(t = 0) = ϕad,eq. 4.5.2 Steady Shear Flow We examine in this section the material functions for a steady shear flow described by a velocity field, u = γ y, where γ is the steady shear rate. As in the preceding investigation, the model parameters are summarized in Table 4.1. In Figure 4.4, we show the shear rate dependence of the viscosity for the neat polymer

candidates in several applications, including aerospace applications, automobile manufacturing, medical devices, coatings, and food packaging, just to name a few. More recent efforts have extended the above class of materials by examining the properties of nanocomposites involving polymer blends and block copolymers, where the potential to create multifunctional materials possessing novel electrical, magnetic, and optical properties has been explored [11]. Many of the common nanoreinforcements

of polymers onto coarse-grained models [29] have been made in recent years, in some cases providing nearly exact quantitative agreement between the two models for certain quantities. Scale integration in specific contexts in the field of polymer modeling can be done in different ways. Any “recipe” for passing information from one scale to another (upper) scale is based on the definition of multiscale modeling, which consider “objects” that are relevant at that particular scale, disregard all degrees

computation of mechanical properties of PNC, the MSFEM quantifies the variations of the SWCNT volume fraction (VF) observed in images, such as the ones shown in Figure 7.3a. Specifically, Figure 7.3a and b show that the method uses a grid of material points in the MR to model the variations observed in the SWCNT VF values. The relative concentrations of SWCNT in the MR are assumed to be statistically equivalent to the total amount of nanotubes in PNC. Therefore, υ = υSWCNT + υPolymer = 1 (7.1)

− φβb )⎟ ⎟ − ⎜ ⎠⎠ z =1 ⎝ α ,β H ∑∑ Θi ∑μ N i i H ⎛ i (2.1) ⎞ ∑ ⎜⎝ ∑ u (zz)φ (z)⎟⎠ z =1 α α α Here, a is the lattice unit dimension, M is the number of lattice units per clay platelet (so that the product Ma2 = A is the total area of the platelet), σ is the grafting density of “surfactants”, χαβ are the Flory–Huggins parameters between species α and β, μi is the chemical potential of the ith component, and Θi is the excess amount of the ith component in the system. The density

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