Distributed Multiscale Simulations of Clay-Polymer Nanocomposites
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Distributed Multiscale Simulations of Clay-Polymer Nanocomposites James Suter1, Derek Groen1, Lara Kabalan1 and Peter V. Coveney1 1 Centre for Computational Science, University College London, 20 Gower Street, WC1H 0AJ London, United Kingdom ABSTRACT The mechanical enhancement of polymers when clay nanoparticles are dispersed within it depends on factors over various length scales; for example, the orientation of the clay platelets in the polymer matrix will affect the mechanical resistance of the composite, while at the shortest scale the molecular arrangement and the adhesion energy of the polymer molecules in the galleries and the vicinity of the clay-polymer interface will also affect the overall mechanical properties. In this paper, we address the challenge of creating a hierarchal multiscale modelling scheme to traverse a sufficiently wide range of time and length scales to simulate clay-polymer nanocomposites effectively. This scheme varies from the electronic structure (to capture the polymer – clay interactions, especially those of the reactive clay edges) through classical atomistic molecular dynamics to coarse-grained models (to capture the long length scale structure). Such a scenario is well suited to distributed computing with each level of the scheme allocated to a suitable computational resource. We describe how the e-infrastructure and tools developed by the MAPPER (Multiscale Applications on European e-Infrastructures) project facilitates our multiscale scheme. Using this new technology, we have simulated clay-polymer systems containing up to several million atoms/particles. This system size is firmly within the mesoscopic regime, containing several clay platelets with the edges of the platelets explicitly resolved. We show preliminary results of a “bottom-up” multiscale simulation of a clay platelet dispersion in poly(ethylene) glycol. 1. INTRODUCTION Layered mineral composites have a substantial potential impact in areas such as energy applications (oil industry additives), materials applications (nano-composite materials) and biomedical applications (drug delivery) [1]. The microscopic structure and mechanisms of layered nanomaterials operate over many different length scales, ranging from nanometers to microns. One of the key challenges in the simulation of such systems is efficiently sampling these scales to understand how the microscopic structure affects the macroscopic properties of the composite. To overcome this problem of multiple length scales, we have developed a multiscale scheme where separate simulations at one length scale pass input parameters to higher length scales, starting from the electronic structure through classical atomistic molecular dynamics to coarse-grained models. We are also developing a reverse-mapping from the coarse-grained models onto the atomistic structures and from atomistic to electronic structure calculations which provides a double function; the higher levels of the scheme can be used to increase the sampling of the more accurate methods, and refinement of
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