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CMBP Seminar Syracuse, February 4, 2011 BLOCK COPOLYMER GUIDED SELF- ASSEMBLY OF NANOPARTICLES Rastko Sknepnek Department of Materials Science and Engineering.

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Presentation on theme: "CMBP Seminar Syracuse, February 4, 2011 BLOCK COPOLYMER GUIDED SELF- ASSEMBLY OF NANOPARTICLES Rastko Sknepnek Department of Materials Science and Engineering."— Presentation transcript:

1 CMBP Seminar Syracuse, February 4, 2011 BLOCK COPOLYMER GUIDED SELF- ASSEMBLY OF NANOPARTICLES Rastko Sknepnek Department of Materials Science and Engineering Northwestern University

2 CMBP Seminar Syracuse, February 4, 2011 Supported by U.S. Department of Energy Grant DE-AC02-07CH11358 Collaborators Dr. Joshua Anderson (at Michigan) Prof. Monica Lamm (Chemical Engineering) Prof. Joerg Schmalian (Physics) Prof. Alex Travesset (Physics)

3 CMBP Seminar Syracuse, February 4, 2011 Outline Why assemble nanoparticles and copolymers? Coarse-grained model Detailed phase diagram Summary Outlook Molecular dynamics on graphics cards

4 CMBP Seminar Syracuse, February 4, 2011 Motivation (Wanka, et al. Macromolecules 27, 4145 (1994)) Growing need to control material properties at nanometer length scales. Assemble nanoparticles into ordered structures.  simple and robust approach  sufficiently versatile Use block copolymers to guide nanoparticle assembly  self-assemble at nano scales  widely available  relatively easy to manipulate Pluronic ® triblock copolymer:

5 CMBP Seminar Syracuse, February 4, 2011 Can functionalized triblocks be used to guide self-assembly of nanoparticles? coarse grain Attach functional groups with affinity for nanoparticles nanoparticle

6 CMBP Seminar Syracuse, February 4, 2011 Model Copolymer (CA 5 B 7 A 5 C) Nanoparticle 12 hydrophilic (A) 7 hydrophobic (B) Fully flexible bead-spring chain.Minimal energy cluster of N np Lennard-Jones particles ( Sloane, et al. Discrete Computational Geom. 1995 ) 2 functional (C) N np =13 N np =55N np =75 radius of gyration R g =2.3  2.1R g 2.5R g 1.2R g Non-bonded interactions (implicit solvent): Nanoparticle affinity  N is only tunable parameter! (set  =1,  =1, m=1)

7 CMBP Seminar Syracuse, February 4, 2011 Molecular dynamics in a nutshell Treat molecular (or molecular cluster) degrees of freedom as classical objects. Introduce effective (classical) interaction potentials. Numerically integrate Newton’s equations of motion: Discretize time in steps of  t << “characteristic time scale” 1.Calculate forces on each particle 2.Ballistically propagate for time  t 3.Goto 1. Pros: Can be efficiently parallelizedCan be efficiently parallelized Preserves true dynamicsPreserves true dynamicsPros: Can be efficiently parallelizedCan be efficiently parallelized Preserves true dynamicsPreserves true dynamics Cons: Can be slow to reach equilibriumCan be slow to reach equilibrium Hard to implementHard to implementCons: Can be slow to reach equilibriumCan be slow to reach equilibrium Hard to implementHard to implement

8 CMBP Seminar Syracuse, February 4, 2011 Simulation details LAMMPS – S. Plimpton, J. Comp. Phys. 117, 1 (1995) (lammps.sandia.gov) Explore phase diagram as a function of: nanoparticle affinity  N (  N /k B T = 1.0, 1.5, 2.0, 2.5, 3.0) packing fraction (  = 0.15, 0.20, 0.25, 0.30, 0.35) Each simulated system contains: p = 600 copolymer chains n = 40 – 270 nanoparticles of size N np =13(1.2R g ), 55(2.1R g ), 75(2.5R g ) all nanoparticles in a given system are monodisperse relative nanoparticle concentration (c = 0.09, 0.12, 0.146, 0.17, 0.193, 0.215, 0.235) NVT ensemble reduced temperature T = 1.2 harmonic bonds, k=330  -2, r 0 =0.9  time step  t = 0.005  m      10 7 time steps HOOMD – J. Anderson, et al. J. Comp. Phys. 227, 5342 (www.ameslab.gov/hoomd)

9 CMBP Seminar Syracuse, February 4, 2011 1.2R g Results A very rich phase diagram. nanoparticle concentration concentration 10% 18%23% Two-dimensional square columnar order dominates phase diagram. Square columnar order yields to 2D hexagonal columnar and 3D gyroid order. Square columnar order is fully suppressed and novel lamellar catenoid order appears.  N /k B T Sknepnek et al., ACS Nano 2, 1259 (2008)    M BCC hexagonal M BCC hexagonal M BCC hexagonal

10 CMBP Seminar Syracuse, February 4, 2011 10%18% hydrophilic hydrophobic functional nanoparticle (top view) 9.5  1.2R g squarecolumnar micellarliquid hexagonal columnar micellarliquid gyroid  N /k B T   squarecolumnar cylindrical mix disorderedcylinders Unconventional square columnar ordering

11 CMBP Seminar Syracuse, February 4, 2011 Hexagonal ordering 18%23% hydrophilic hydrophobic functional nanoparticle (top view) (Toth, Regular figures, 1964) 11.5  1.2R g micellarliquid micellarliquid gyroid layeredhexagonal gyroid squarecolumnar  N /k B T   hexagonal columnar

12 CMBP Seminar Syracuse, February 4, 2011 Extended region of gyroid ordering 18%23% hydrophilic hydrophobic functional nanoparticle gyroid order confirmed by structure factor gyroid order confirmed by structure factor order shows Ia3d symmetry order shows Ia3d symmetry 1.2R g squarecolumnar hexagonalcolumnar micellarliquid micellarliquid gyroid gyroid  N /k B T   hexagonalcolumnar layeredhexagonal

13 CMBP Seminar Syracuse, February 4, 2011 Lamellar catenoid order 23% (top view) (side view) hydrophilic hydrophobic functional nanoparticle simple hexagonal lattice lattice honeycomb-likelayers layered structure 1.2R g  N /k B T  lamellarcatenoid hexagonalcolumnar micellarliquid gyroid

14 CMBP Seminar Syracuse, February 4, 2011 Cubic (CsCl) ordering 21% hydrophilic hydrophobic functional nanoparticle (cubic) (square columnar, top view) 2.5R g micellarliquid gyroid squarecolumnar cubic (CsCl)  N /k B T 

15 CMBP Seminar Syracuse, February 4, 2011 Summary and Conclusions End-functionalized block copolymers are shown to provide an efficient strategy for assembly of nanocomposite materials. Sknepnek et al., ACS Nano 2, 1259 (2008)  N /k B T  a rich phase diagram unconventional square columnar ordering enhanced stability of gyroid phase Anderson, et al. Phys. Rev. E 82, 021803 (2010)

16 CMBP Seminar Syracuse, February 4, 2011 Outlook DNA coated nanoparticles Surface patterns and assembly of grafted nanoparticles Ligand exchange on quantum dots Related projects Fully map phase diagram Introduce specific details of real systems Refine packing arguments

17 CMBP Seminar Syracuse, February 4, 2011 Condensed Matter Seminar Syracuse, February 4, 2011 Molecular Dynamics on Graphics Cards

18 CMBP Seminar Syracuse, February 4, 2011 What does this… …have to do with this… (IGN BioShock 3 screenshot) gyroid (courtesy of J. Anderson)

19 CMBP Seminar Syracuse, February 4, 2011 ~2000pixels ~1000pixels Estimate of floating point operations per second (FLOPs) to generate smooth animation: 2000x1000x50x10x100 ~ 10 11 (or 100 GFLOPs!) number of pixels frames per second iterations per pixel operations per pixel

20 CMBP Seminar Syracuse, February 4, 2011 Even the fastest CPU cannot handle this much load! A designated hardware is required – Graphics Processing Unit (GPU) (present in virtually all computers, including modern smart phones) Top of the line hardware: GTX 480 Key features: 480 cores 177 GB/s memory bandwidth 1 TFLOPs single precision Inexpensive - $450 Compared to a six-core Intel i7: 6 cores 17 GB/s memory bandwidth 100 GFLOPs A radically different architecture!

21 CMBP Seminar Syracuse, February 4, 2011 Computer graphics: J. A. Anderson, et al., Journal of Computational Physics 227, 5342 (2008) Large amount of relatively simple computations per pixel High data parallelization – same operations on all pixels Molecular dynamics: Large amount of relatively simple computations per particle High data parallelization – same operations on all particles (with a bit of caveats) In 2006 NVidia Co., released CUDA and made GPU available to non-graphics applications Original developed in Alex Travesset’s group at Iowa State University. Currently main development in Sharon Glotzer’s group at University of Michigan

22 CMBP Seminar Syracuse, February 4, 2011 N=14000 N=6908 N=18400 N=36360 N=20000 N=64000 tethered nanospheres surfactant coated surfaces polymer nanocomposites tethered nanorods supercooled liquid supercooled liquid (courtesy of Joshua A. Anderson) Real-world performance

23 CMBP Seminar Syracuse, February 4, 2011 People HOOMD-blue is open source! It’s being developed and used in research groups all over the world. Latest release includes code contributions from: J. Anderson, A. Keys, T. D. Nguyen, C. Phillips – University of Michigan R. Sknepnek – Northwestern University A. Travesset – Iowa State University A. Kohlmeyer, D. Lebard, B. Levine – Temple (formerly at Penn) I. Morozov, K. Andrey, B. Roman – Joint Institute for High Temperatures of RAS (Moscow, Russia) Research groups developing for HOOMD-Blue: Sharon Glotzer – University of Michigan Alex Travesset – Iowa State University/DOE Ames Laboratory Michael Klein – Temple (formerly at Penn) Athanassios Panagiotopoulos – Princeton Monica Olvera de la Cruz – Northwestern http://codeblue.umich.edu/hoomd-blue

24 CMBP Seminar Syracuse, February 4, 2011 GPU based project in Olvera de la Cruz group Surface patterns and assembly of grafted nanoparticles Ligand exchange on quantum dots (Guo, et al., submitted) (Donakowski, et al., J. Phys. Chem. C (2010)) (Jha, et al., J. Chem. Theory Comput. (2010))

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