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 1

2. Polymers in the Real World 2 [10] [11] [12] [13]

3. Why Simulations? “Because they provide the freedom to fail!” Cost Time “Assess real-world processes too complex to analyze via spreadsheets or flowcharts” 3 [1] [2]

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

5. Timeline Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Training Literature Review Create Surfaces Create Polymers Run Simulations Analyze Simulations Work on Deliverables Finish Research Paper Finish Final Presentation Finish Research Poster 5

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

7. POLYMER GENERATION 7

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

9. Polymer Adsorption 9

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

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

12. CREATE SURFACES 12

13. Surfaces 13 1. Regular, Rough Oscillations in the x direction: 1 Oscillations in the y direction: 1 Amplitude: 0.5 Oscillations in the x direction: 2 Oscillations in the y direction: 2 Amplitude: 0.1

14. Surfaces 14 2. Random, Rough Roughness Factor: 0.9Roughness Factor: 0.1

15. Testing Surfaces 15 www-ee.ccny.cuny.edu

16. Face Centered Cubic with MATLAB 3 rows, 3 columns, Depth of 1 16

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

18. Problems? It’s not that simple! 18

19. Brownian Fields Created Using Fractals Fractals are a mathematical concept: ◦ Self similar with a change of scale (magnification) 19

20. Brownian Field Uses Fractals Since Brownian Field has holes or gaps we have simulated a FCC structure using fractals: 20

21. Surface Area Using axb = IaIIbIsin(Ø) (Area) we find area between those two vectors. 21

22. RUN SIMULATIONS 22

23. LAAMPS File 23

24. Polymer Adsorbing onto Surface Polymer is randomly placed around surface while data is taken http://www.technewsworld.com/story/71829.html 24

25. Polymers are Constantly Moving 25 Surface

26. RUN ANALYSIS 26

27. Analysis In order to receive usable data – all variables must be controlled except one Independent Variable: ◦ Roughness Dependent Variables: ◦ Entropy ◦ Energy Controlled Variables: ◦ Surface Area ◦ Polymer make-up ◦ Surface make-up 27

28. 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 28

29. Energy vs. Distance Analysis – “The Sweet Spot” 29

30. Lennard Jones Potential Equation [2] Energy (v) is a function of distance (r). Interactive Force (Epsilon) Diameter of atom (sigma) 30

31. Lennard Jones Potential Equation 31 Energy Distance

32. 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 ◦ Where is that “sweet spot?” 32

33. Example: 33 http://www.naturalcosmeticne ws.com/recent-news/pg- introduces-pantene-plant- based-plastic-bottles/ Conditioner!

34. How does this information help us? In the development of conditioner: ◦ What is the total change in entropy of the conditioner when adsorbing onto hair? ◦ What is the distance from conditioner to hair that achieves the lowest energy level? If P&G knew these things they could make better conditioner! 34

35. What will this save? Time Effort Money 35 [7] [8] [9]

36. Works Cited [1] (2010). “Polymers”, Chemical of the Week, (May 31, 2013).http://scifun.chem.wisc.edu/chemweek/polymers/polymers.html [2] (2010). “Lennard-Jones Potential”,UCDavisChemWiki, (May 31, 2013).http://chemwiki.ucdavis.edu/Physical_Chemistry/Quantum_Mechanics/Atomic_Theory/Interm olecular_Forces/Lennard-Jones_Potential [3] (2012). “Solutions: Simulation Software Overview.” Imagine That!, (May 29, 2013).http://www.extendsim.com/sols_simoverview.html#monteCarlo [4] (2012). “What are Polymers?, MAST, (May 31, 2013).http://matse1.matse.illinois.edu/polymers/ware.html [5] (2013). “Why Simulations?” TATA Interactive Systems, (May 29,2013).http://blog.tatainteractive.com/2013/01/why-simulations.html [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/http://www.empowernetwork.com/teameaglefreedom/blog/the-clock-is-ticking-tic-toc-tic-toc/ [8] http://emotibot.net/?i=504http://emotibot.net/?i=504 [9] http://www.merchantcircle.com/business/National.Lawsuit.Funding.302-792- 1400/picture/view/3137972http://www.merchantcircle.com/business/National.Lawsuit.Funding.302-792- 1400/picture/view/3137972 [10] www.idahofamilyvision.com www.idahofamilyvision.com [11] www.plasticstoday.com www.plasticstoday.com [12] carterpaintingboulder.com carterpaintingboulder.com [13] www.pennysimkin.com www.pennysimkin.com 36