Polymer-Clay Nanocomposites: A Multiscale Molecular Modeling Approach Giulio Scocchi, † Paola Posocco, Maurizio Fermeglia, and Sabrina Pricl* Molecular Simulation Engineering (MOSE) Laboratory, Department of Chemical, EnVironmental and Raw Materials Engineering (DICAMP), UniVersity of Trieste, Piazzale Europa 1, I-34127 Trieste, Italy ReceiVed: NoVember 17, 2006; In Final Form: January 7, 2007 A hierarchical procedure bridging the gap between atomistic and mesoscopic simulation for polymer-clay nanocomposite (PCN) design is presented. The dissipative particle dynamics (DPD) is adopted as the mesoscopic simulation technique, and the interaction parameters of the mesoscopic model are estimated by mapping the corresponding energy values obtained from atomistic molecular dynamics (MD) simulations. The predicted structure of the nylon 6 PCN system considered is in excellent agreement with previous experimental and atomistic simulation results. Introduction Blending molten polymer and inorganic clays can result in a class of new materials, in which nanoscale clay particles, generally layered silicates, are molecularly dispersed within the polymeric matrix. Such polymer-clay nanocomposites (or PCNs) exhibit dramatic increases in several properties, including mechanical strength and heat resistance, and a decrease in gas permeability when compared to the polymeric matrix alone. 1-7 Importantly, the improvement in these properties is achieved at very low loadings of the inorganic component, typically 1-10 wt %, thus rendering PCNs lighter in weight than any other conventionally filled polymer. These unique features make PCNs ideal materials for applications such as high barriers for food or pharmaceutical packaging to strong, heat resistant automotive components, just to name a few. Fabricating these materials in an efficient and cost-effective manner, however, poses signifi- cant synthetic challenges. To appreciate these challenges, let us discuss briefly the structure of layered silicates by considering montmorillonite (MMT) as a prime example. This inorganic clay consists of stacked silicate sheets, each approximately 200 nm long and 1 nm thick. The spacing between each sheet (or gallery) is also of the order of 1 nm, and this quantity is clearly smaller than the average radius of gyration of any conventional polymer. Therefore, entropy generally constitutes a large barrier that prevents the polymer from penetrating these galleries and becoming an intercalated material. Accordingly, there is a number of critical issues that need to be addressed in order to optimize the design and production of PCNs. Of foremost importance is the isolation of the conditions that result in a promotion of the polymer penetration into the narrow clay galleries. If, however, the sheets ultimately phase-separate from the polymer matrix, the mixture will not exhibit the improved strength, heat resistance, or barrier properties mentioned above. Accordingly, it is also essential to determine the factors that control the macroscopic phase behavior of the mixture. Finally, the properties of the PCNs commonly depend on the structure of the material; thus, it is of particular interest to establish the morphology of the final composite. To date, there are few theories to pinpoint the critical parameters or to predict the thermodynamic stability of a PCN system, 8-10 forcing synthetic chemists to synthesize all possible mixtures in order to isolate the desired system. Therefore, in order to develop new materials and composites with designed new properties, it is essential for these properties to be predicted before preparation, processing, and experimental characteriza- tion. Despite the tremendous advances made in the modeling of structural, thermal, mechanical, and transport properties of materials at the macroscopic level (finite element (FE) analysis of complicated structures), there remains a tremendous uncer- tainty about how to predict many critical properties related to performance. The fundamental problem here is that these properties depend on the atomic level of interactions and chemistry, dealing with the electronic and atomic level of description and at a length/time scale of nanometers/nano- seconds. The material designer, however, needs answers from macroscopical modeling (the finite element paradigm) of components having scales of centimeters and milliseconds, if not larger. To substantially advance the ability to design useful high performance materials, it is then essential that we insert the chemistry into the mesoscopic (MS) and macroscopic (FE) modeling. Currently, atomistic level simulations such as mo- lecular dynamics (MD) or Monte Carlo (MC) techniques allow one to predict the structure and properties for systems of a considerably large number of atoms and time scales of the order of microseconds. Although this can lead to many relevant results in material design, many critical issues in materials design still require time and length scales far too large for practical MD/ MC simulations. Therefore, we need to develop methods treating the mesoscale in between the atomistic length and time scales of MD/MC and the macroscopic length and time scales (micrometers to millimeters and microseconds to seconds) pertaining to FE analysis. This linking through the mesoscale, in which we can describe a system microstructure, is probably the greatest challenge to developing reliable first principles methods for practical and effective material design. Indeed, only by establishing this connection from microscale to mesoscale, it is possible to build first principles methods for describing the properties of new materials and composites. One of our major aims is to reach the domain of materials science and engineering by building from fundamental principles * Corresponding author. Phone: +390405583750. Fax: +39040569823. E-mail: sabrina.pricl@dicamp.unis.it. † Presently at the University for Applied Sciences of Southern Switzerland (SUPSI) - Institute for Applied Computer Science and Industrial Technology (ICIMSI), Centro Galleria 2, CH-6928 Manno, Switzerland. 2143 J. Phys. Chem. B 2007, 111, 2143-2151 10.1021/jp067649w CCC: $37.00 © 2007 American Chemical Society Published on Web 02/10/2007