Computational Nano Enginering of Polymer Surface Systems Aquil

Computational Nano. Enginering 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

Why Simulations? �“Because they provide the freedom to fail!” • Cost • Time [3] �“Assess real-world processes too complex to analyze via spreadsheets or flowcharts” [5] 2

Research Triangle Simulation s Nature Theory Experiment (3)

Programs Used Visual Molecular Dynamics Large-scale Atomic/Molecular Massively Parallel Simulator 4

General Task Overview Literature Review 2. Generation of Surfaces and Polymers 3. Run Simulations and Analyze 4. Project Deliverables 1. 5

Task 1: Literature Review 6

What Are Polymers? � Substances which consist of a large number of repeating units called “monomers” � Polymers are used as adhesives, coatings, foams, and packaging materials to textile and industrial fibers, composites, electronic devices, biomedical devices, optical devices, and precursors for many newly developed high-tech ceramics � The polymer industry has grown to be larger than the aluminum, copper, and steel industries combined [4]

Physical Properties Of Polymers � Are dependent upon interchain and intrachain bonding, nature of the back bone, processing events, presence or absence of the additive, chain size and geometry, and molecular weight distribution. � Polymers are semi-crystalline � Polymers that crystallize are different in characteristics to equivalent low molecular weight materials. [1]

Energy vs. Distance (2)

Molecular Structure � Molecular arrangement of polymers can be compared to that of spaghetti � Amorphous organization of molecules has no longrange order or form in which the polymer chains arrange themselves � Amorphous polymers are generally transparent, which is an important characteristic for many applications including food wrap, plastic windows, headlight senses, and contact lenses [1]

Monte Carlo Method �Dependent on numbers randomly generated within confined spaces ◦ The data from the random generation are averaged in some way �Time is irrelevant ◦ Less time is required compared to wet lab ◦ MC Method is not proof that something has happen – it probably will happen [6]

Monte Carlo Method - Area Probability that ½ of dots will land in green section Probability that ¼ of dots will land in green section Probability can be used to calculate area! [6]

Monte Carlo Method - Area The integral of this curve can be found if enough dots are taken and the total area of the rectangle is known. [6] The value of pi can be calculated if enough dots are taken, the total area of the rectangle is known, and the radius of the circle is known. [6]

Monte Carlo Method: “On. Lattice” Random Walks [6]

Monte Carlo Method: “Off. Lattice” Random Walks [6] �“Off-Lattice” means it is not based on a lattice ◦ Infinite directions available ◦ Can have diagonals and crossing lines http: //www. pasteur. fr/ip/easysite/pasteur/fr/recherche/ departements-scientifiques/biologie-cellulaire-etinfection/unites-et-groupes/g 5 -imagerie-etmodelisation/objectives

How Monte Carlo Method will be Used �The creation of polymer chains ◦ “Off lattice” Random Walks �The placement of polymer chains �When polymer is adsorbing with surface randomly: ◦ Energy , entropy, and distance from surface will be measured for each random placement ◦ These values will be averaged for each simulation

Task 2: Generate Surfaces and Polymers 17

Surfaces Regular Random 18

Testing Surfaces www-ee. ccny. cuny. edu 19

Using MATLAB to Generate “On. Lattice” Polymer Chains

Using MATLAB to Generate “Off. Lattice” Polymer Chains

Task 3: Run Simulations and Analyze 22

Programs Used Visual Molecular Dynamics Large-scale Atomic/Molecular Massively Parallel Simulator 23

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

Data that might be taken from simulation �Entropy – How many options does the polymer have? ◦ At bottom of trough – the polymer is compact �Not many options ◦ At top of trough – the polymer is free to move �A lot of options �Energy – What is energy at a certain distance? ◦ Each distance corresponds to a certain energy level

Analysis of Data �Analysis will answer questions such as: ◦ What was the average entropy level? ◦ What was the average energy level? ◦ What was the average distance from the polymer to the surface?

Why is this important? �Companies may want to know how well there product is adsorbing onto a surface. ◦ Ex. P&G wants to know how well their conditioner is adsorbing onto hair http: //www. naturalcosmeticnews. com/recentnews/pg-introduces-pantene-plant-basedplastic-bottles/

Task 4: Project Deliverables Research Paper Final Poster Final Presentation 28

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 29

Works Cited [1] (2010). “Polymers”, Chemical of the Week, <http: //scifun. chem. wisc. edu/chemweek/polymers. html>(May 31, 2013). [2] (2010). “Lennard-Jones Potential”, UCDavis. Chem. Wiki, <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#monte. Carlo>(May 29, 2013). [4] (2012). “What are Polymers? , MAST, <http: //matse 1. 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, United Kingdom, 30 1 -6, 48 -67