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Predicting Nanocomposite Permeability via Monte Carlo Simulations: Insights and Implications

This study explores the permeability of nanocomposites through Monte Carlo simulations, focusing on the constrained polymer region. Nanoparticles of size 1-100 nm enhance the properties of polymers, resulting in improved tensile strength and reduced gas permeability. We analyze the tortuous path model that describes gas diffusion through nanocomposites influenced by clay particles. Our findings establish a new relationship for tortuosity as a function of geometric factors, providing a more accurate insight into permeability. This research lays the groundwork for future studies on variable effects in nanocomposite behavior.

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Predicting Nanocomposite Permeability via Monte Carlo Simulations: Insights and Implications

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  1. A Prediction of Nanocomposite Permeability from Monte Carlo Simulations and the Implications of the Constrained Polymer Region SumitGogia Patrick Kim Vincent Yu

  2. Introduction • Nanoparticles • Generally between 1-100 nm in length • High surface area to volume ratio • Nanocomposites • Polymers with dispersed nanoparticles • Polymer-clay nanocomposites • Increased tensile strength • Increased elastic modulus • Decreased gas permeability

  3. Applications • Food packaging • Prolong shelf life • Tennis balls • Prevent depressurization • Protective equipment • Reduce thickness

  4. Tortuous path model • Impermeable clay plates create tortuous paths for permeating molecules • Nanocomposite is less permeable as a result (Nielsen, 1967)

  5. Tortuous path model • Two main factors determine the magnitude of the tortuous path • Aspect ratio (α) • Volume fraction (ϕ)

  6. Constrained polymer model • Polymer-clay interactions • May cause phase changes in the pristine polymer • Significant effect observed in amorphous polymers (Adame and Beall, 2009)

  7. Computer simulation • Allows complete control over variables • Easily reproducible and verifiable • Quicker than gas permeation measurements

  8. Quantifying tortuosity • Tortuosity • is the diffusion coefficient of pristine polymer • is the diffusion coefficient of resulting nanocomposite • is the distance that a molecule has to travel to diffuse through the nanocomposite • is the distance that a molecule has to travel to diffuse through the pristine polymer

  9. Monte Carlo simulation

  10. Monte Carlo simulation

  11. Simulation parameters • Run on a supercomputing grid over a period of one month • Data obtained for and • Other parameters (t is time)

  12. Data

  13. Results and discussion • We suggest considering τ as a function of χ, where • μ is a geometric factor depending on clay shape • s is the cross-sectionalarea of a clay plate • is the number of clay plates per volume

  14. Data

  15. Results and discussion • χ is composed of two main components: • Cross-sectional area of clay plates per volume of polymer • Average distance travelled by a molecule to get around a clay plate

  16. Conclusion • Established τ as a function of χ • χ is more accurate than αϕ • Monte Carlo simulations • Improved efficiency • Feasible

  17. Further research • Account for more variables in simulations • Clay plate size • Orientation • Incomplete exfoliation • Calculate effect of constrained polymer region

  18. Acknowledgements • Gary Beall, Texas State University • Max Warshauer, Texas State University • Siemens Foundation • University of Texas at Austin • Our families Further information Website: code.google.com/p/rwalksim

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