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Computer Simulations of Polymers For Materials and Energy Applications

Computer Simulations of Polymers For Materials and Energy Applications. Venkat Ganesan. Venkat Ganesan: CPE 3.414, 471-4856. venkat@che.utexas.edu. Research Group and Projects.

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Computer Simulations of Polymers For Materials and Energy Applications

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  1. Computer Simulations of Polymers For Materials and Energy Applications Venkat Ganesan Venkat Ganesan: CPE 3.414, 471-4856. venkat@che.utexas.edu

  2. Research Group and Projects Theme: Computer simulations and models to address how the synthetic chemistry controls the self-assembly and properties of polymeric, colloidal and biological materials Students, Postdocs & Ongoing Projects Dr. Ben Hanson: Multiscale simulations of properties of polymer nanocomposites membranes. David Trombly: Behavior and properties of protein-polysaccharide mixtures. C. Mahajan: Properties of direct methanol fuel cell membranes. Thomas Lewis: Dendrimer-DNA complexes for drug delivery applications. Gunja Pandav: Self-assembly of protein-like polymers. Dr. Victor Pryamitsyn: Simulations of properties of polymer nanocomposites. Dr. Arun Narayanan: Simulations of properties of organic solar cells.

  3. Molecularly Directed Design of Organic and Polymeric Solar Cells and LEDs (A collaboration with Prof. Rachel Segalman, UC Berkeley and Prof. Lynn Loo, Princeton University)

  4. Advantages of Organic Solar Cells • Even though Si based cells have higher efficiencies, they are extremely expensive. • Polymer solar cells are cheaper to manufacture, easy to process, and are flexible. Polymer Solar cells: Efficiencies ~ 5-6 %

  5. Morphology Requirements • Photogeneration leads to bound electron-hole pair called as exciton. • Continuous interface between donor and acceptor between the electrodes (heterojunction) • Lengthscale of phase separation ~ exciton diffusion length (10-20 nm) Acceptor (A) Donor (D) Bilayer structure BHJ structure

  6. Semiconducting Block Copolymers PPV-b-P(S-stat-C60) • Such polymers self-assemble into complex morphologies • Mechanisms underlying such • self-assembly ? • Model or predict the statistical • mechanics of such morphologies?

  7. Transport/Device Models • Photogeneration leads to bound electron-hole pair called as exciton. • Continuous interface between donor and acceptor between the electrodes (heterojunction) • Lengthscale of phase separation ~ exciton diffusion length (10-20 nm) Acceptor (A) Donor (D) • Fundamental statistical mechanical models for such transport processes and the impact of different morphologies ? • Identify optimum morphologies and materials for organic • solar cells and LEDs ?

  8. Tools of The Trade Process Models (Unit Operations) Statistical Mechanics, Models Time Continuum Models (Fields) Mesoscale Models (Segments, Blobs) New simulation tools Molecular Dynamics (Atoms, Bonds) Montecarlo, Molecular dynamics incorporating atomistic details Quantum Mechanics (Electrons) Fundamental mechanisms of proton conduction Length

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