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Computational NanoEnginering of Polymer Surface Systems

Computational NanoEnginering of Polymer Surface Systems. Aquil Frost, Environmental Engineering, Central State University John Lewnard, Mechanical Engineering, University of Cincinnati Anne Shim, Biomedical Engineering, The Ohio State University. Conditioner!.

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Computational NanoEnginering of Polymer Surface Systems

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  1. Computational NanoEnginering of Polymer Surface Systems Aquil Frost, Environmental Engineering, Central State University John Lewnard, Mechanical Engineering, University of Cincinnati Anne Shim, Biomedical Engineering, The Ohio State University

  2. Conditioner! http://www.naturalcosmeticnews.com/recent-news/pg-introduces-pantene-plant-based-plastic-bottles/

  3. How do Simulations Help Pantene? • Simulation will help discover whether conditioner is sticking onto hair • If P&G knew these things they could make better conditioner! • Save time • Save effort • Save money

  4. What can we see? Macro Time Meso Nano Sub-atomic Size

  5. Timeline/Tasks

  6. Programs Used Large-scale Atomic/Molecular Massively Parallel Simulator Visual Molecular Dynamics

  7. Polymer Generation

  8. What Are Polymers? • Consist of repeating units called “monomers” • Polymer industry is larger than the aluminum, copper, and steel industries combined [4]

  9. Polymer Adsorption

  10. Using MATLAB to Generate “On-Lattice” Polymer Chains

  11. Using MATLAB to Generate “Off-Lattice” Polymer Chains

  12. Create surfaces

  13. Rough Surfaces

  14. Surfaces 1. Regular, Rough Oscillations in the x direction: 2 Oscillations in the y direction: 2 Amplitude: 1 Oscillations in the x direction: 1 Oscillations in the y direction: 1 Amplitude: 0.5

  15. Surfaces 2. Random, Rough Hurst Parameter: 0.1 Hurst Parameter0.9

  16. Testing Surfaces www-ee.ccny.cuny.edu

  17. Face Centered Cubic with MATLAB 3 rows, 3 columns, Depth of 1

  18. Face Centered Cubic with MATLAB 3 rows, 3 columns, Depth of 1

  19. Problems? • It’s not that simple!

  20. Fixing the Problem • Fractals • Self similar with a change of scale (magnification)

  21. Brownian Field Uses Fractals • Since Brownian Field has holes or gaps we have simulated a FCC structure using fractals:

  22. Surface Area • Using axb = IaIIbIsin(Ø) (Area) we find area between those two vectors.

  23. Run simulations

  24. The Simulation Process • In order to receive usable data – all variables must be controlled except one • Independent Variable: • Roughness • Sinusoidal Surface – Amplitude and Wavelength • Brownian Surface – Hurst Parameter • Dependent Variables: • Entropy • Energy • Controlled Variables: • Surface Area • Polymer make-up • Surface make-up

  25. LAMMPS Data File

  26. LAMMPS Input File • Controls and sets parameters for data file such as: • Bond Coefficients • Angle Coefficients • Dihedral Coefficients • Mass

  27. Polymer Adsorbing onto Surface http://www.technewsworld.com/story/71829.html Polymer adsorbs onto surface using molecular dynamics while data Is taken.

  28. Polymers are Constantly Moving Surface

  29. VMD Image of Polymer Adsorbing onto Surface Image courtesy of Dr. Anderson

  30. Run analysis

  31. Entropy • Entropy – How many options does the polymer have? • At bottom of trough – the polymer is compact - order • Not many options • At top of trough – the polymer is free to move - chaos • A lot of options

  32. Energy vs. Distance Analysis

  33. Lennard Jones Potential Equation [2] Energy (v) is a function of distance (r). Interactive Force (Epsilon) Diameter of atom (sigma)

  34. Lennard Jones Potential Equation Distance Energy

  35. What does this analysis tell us? • The extent at which a polymer exists at a certain entropy level • Depends on roughness • The distance that leads to the lowest energy potential

  36. What will this save? • Time • Effort • Money [7] [8] [9]

  37. Further Applications

  38. Works Cited [1] (2010). “Polymers”, Chemical of the Week, <http://scifun.chem.wisc.edu/chemweek/polymers/polymers.html>(May 31, 2013). [2] (2010). “Lennard-Jones Potential”,UCDavisChemWiki, <http://chemwiki.ucdavis.edu/Physical_Chemistry/Quantum_Mechanics/Atomic_Theory/Intermolecular_Forces/Lennard-Jones_Potential>(May 31, 2013). [3] (2012). “Solutions: Simulation Software Overview.” Imagine That!, <http://www.extendsim.com/sols_simoverview.html#monteCarlo>(May 29, 2013). [4] (2012). “What are Polymers? , MAST, <http://matse1.matse.illinois.edu/polymers/ware.html>(May 31, 2013). [5] (2013). “Why Simulations?” TATA Interactive Systems, <http://blog.tatainteractive.com/2013/01/why-simulations.html>(May 29,2013). [6] Landau D. P. Binder K. (2000). “Introduction,” “Simple Sampling Monte Carlo Methods ,“Monte Carlo Simulations in Statistical Physics, Press Syndicate of the University of Cambridge, Cambridge, United Kingdom, 1-6, 48-67 [7] http://www.empowernetwork.com/teameaglefreedom/blog/the-clock-is-ticking-tic-toc-tic-toc/ [8] http://emotibot.net/?i=504 [9] http://www.merchantcircle.com/business/National.Lawsuit.Funding.302-792-1400/picture/view/3137972 [10] www.idahofamilyvision.com [11] www.plasticstoday.com [12] carterpaintingboulder.com [13] www.pennysimkin.com

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