(77d) Monte Carlo Simulation For Polymer Nanocomposite Coating Formation Through Curing

Polymer nanocomposite resin for coating application has been of great interest, as it is expected to substantially improve coating properties. Such type of nanocomposite is usually designed by adding a small amount of organomodified nanoparticles into a conventional waterborne or solvent-borne resin. The resulting resin is applied on a substrate surface and a layer of thin film is formed through curing at elevated temperatures. During film curing, multiple interrelated phenomena occur simultaneously, among which, the most important ones are: (i) crosslinking reaction between the precursor polymer chains and crosslinkers, (ii) redistribution and reorientation of nanoparticles, and (iii) polymer chain adsorption onto the nanoparticle surface. These phenomena jointly determine the nano-to-mesoscale structures of the coating, which strongly influence final coating quality. It is widely agreed that understanding the structure formation dynamics is essential for effective material design, and computer simulation can be a promising tool to provide in-depth and quantitative investigation.

The nanoscale structures and interactions in the polymer/nanoparticle systems have been studied through Monte Carlo simulation (Zhang and Archer, 2004; Ozmusul et al., 2005). However, the known simulation work does not address the issue of structure formation in polymer nanocomposite coating through industrial-scale curing. Those simulated systems are exclusively for a fixed number of polymer chains, and those chains have a fixed length. This means that there is no crosslinking reaction in those systems. In most MC simulation, the positions of particles are essentially fixed in space. However, this is not true when considering the crosslinking of material at high temperatures, because some nanopartiles will be driven together by depletion interactions with growing polymer chains. On the other hand, considerable efforts have been devoted to model polymer network formation through crosslinking reaction, which can help generate detailed network structures for further analysis (Schulz and Sommer, 1992; Gilra and Cohen, 2000; Balabanyan, et al., 2005). However, the systems studied are conventional resins without nanoparticles incorporation.

In this work, the three interrelated phenomena listed above are simultaneously taken into account, which helps study nanocomposite coating formation through curing. We focus on the study of structural formation via Monte Carlo simulation and algorithmic analysis of the network structure. In simulation, lattice MC with a bond fluctuation (BF) model is utilized. Each individual spherical nanoparticle, monomer unit of precursor polymer chains, and crosslinker molecule are modeled as rigid cubes occupying an integer number of lattice sites. A set of allowed bond vectors connecting two successive monomer units are also constructed to ensure a non-intersection of bonds and an excluded volume of the monomer units. No attractive interaction between any pair of monomer units is considered. The polymer-nanoparticle and particle-particle energetic interactions are modeled as Lennard-Jones (LJ) potentials. Certain numbers of nanoparticles, precursor polymer chains, and crosslinkers are initially placed on a cubic lattice with an account of the excluded volume and non-intersection conditions. After an initial structure configuration is created, an equilibration process starts. Only local moves are allowed for each individual nanoparticle, monomer unit and crosslinker. Once a configuration is relaxed, crosslinking reactions are introduced as follows. When an unreacted functional group in the polymer chain and a not fully reacted crosslinker move into the nearest neighbor positions, a reaction takes place with a specified probability. The crosslinking is stopped after some time when a fraction of unreacted functional groups reaches a steady-state value. A structure analysis algorithm is then used to determine the connectivity in the polymer network, spatial distribution of nanoparticles, and polymer chain conformations. To the best of our knowledge, this work is the first effort of this kind on simulating polymer nanocomposite coating formation through curing.

The introduced method has been successfully applied to the study of curing of automotive acrylic-melamine clearcoat containing alumina nanoparticles. Simulation results are compared with the known experimental work (Hosseinpour et al., 2005; Nobel et al., 2007a,b). In agreement with the experimental observations, the nanoparticles will be redistributed during the curing process (Nobel et al., 2007b). Both the nanoscale structure (e.g., chain conformation in the vicinity of the polymer-nanoparticle surface) and the mesoscale structure (e.g., the nanoparticle distribution) can be obtained, which are essential for developing complete structure-property correlations (Nobel et al., 2007a). In addition, the effects of three important material parameters (i.e., the nanoparticle size and loading level, and the polymer-nanoparticle affinity) on the final coating nano-to-mesoscale structures are thoroughly investigated.

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