Nanoscale Modeling and Simulation. George C. Schatz Northwestern University

Transcription

1 Nanoscale Modeling and Simulation George C. Schatz Northwestern University

2 Where can simulation play a role in nanoscience, both now and in the future? 1. Structures of disordered nanomaterials: peptide amphiphile micelles 2. Functionalization of nanoparticle interfaces? Chemical properties of carbon-based materials 3. Nonequilibrium processes: machines, pumps: bioinspiration and frustration 4. Plasmonic Optical Properties and Devices: Plasmonics without metals; Plasmonic lasers 5. Transitioning from nano to meso: Metamaterials from DNA-linked nanostructures

3 Structures of disordered nanomaterials: peptide amphiphile structures J.D. Hartgerink, E. Beniash, and S.I. Stupp, Science, 294, 1605 (2001).

4 Atomistic Modeling with Seeded Structures One-Sun Lee, Samuel I. Stupp and George C. Schatz, J. Am. Chem. Soc. 113, (2011)

5 Converged Cylindrical Micelle from Self-Assembly Beta sheet Alpha helix One-Sun Lee, Samuel I Stupp and George C. Schatz, J. Am. Chem. Soc. 113, (2011)

6 Molecular level structure facilitates new applications of the micelles Cytotoxic: Gets incorportated into cell membrane Not cytotoxic: Stabilized by beta sheets

7 Functionalization of nanoparticle interfaces? Chemical properties of carbon-based materials Nanodiamonds are an important material for diagnostics and drug delivery. But what is at the surface? Theory shows that surfaces are mostly functionalized graphene! Graphitized nanodiamond surfaces subject to KMnO 4, H 2 SO 4, HNO 3 treatment after bead milling. Use results to model drug delivery with NDs Hansung Kim, Han Bin Man, Biswajit Saha, Adrian M. Kopacz, One-Sun Lee, George C. Schatz, Dean Ho, Wing Kam Liu, J. Phys. Chem. Lett., 3, (2012). Jeffrey T. Paci, Han B. Man, Biswajit Saha, Dean Ho and George C. Schatz, J. Phys. Chem. C 117, (2013)

8 Configuration-Biased Monte Carlo Modeling of Graphene Oxidation DFT (PBE), DZP basis set and PBCs Observe: 1. Aliphatic regions of epoxide/hydroxide functionalization. No 1,3 ethers, no C=O (except at defects) 2. Aromatic regions, but sheet puckering is substantial. Jeffrey T. Paci, Ted Belytschko, George C. Schatz, J. Phys. Chem. C, 111, (2007)

9 Experimental Results Adv. Mater. 2010, 22, 4467 Defect-free GO only has epoxides, OH, aromatic regions Defected GO can show C=O

10 Nonequilibrium processes: machines, pumps: bioinspiration and frustration Biological ion pumps can operate with close to 100% efficiency. Can we make similarly efficient artificial molecule machines? Bioinspiration: correlated events 1. Left gate open, ion diffuses into pocket 2. This recruits ATP to active site 3. ATP can then hydrolyze, releasing ADP 4. Left gate closes, right gate opens 5. Ion diffuses to right 6. Phosphate is released 7. Right gate shuts, left gate opens 8. repeat

11 Rotaxane-based devices (Stoddart) Shuttles Bissell et al. Nature 369, 133 (1994) Switches Nanovalves Collier et al. JACS 123, (2001) Nguyen et al. PNAS 102, (2005) Molecular muscle analogues Liu et al. JACS 127, 9745 (2005)

12 Example of a machine that can be studied with simulation: J. Am. Chem. Soc. 133, (2011). azo benzene capped A 2 -T 2 We would like to stretch a photoswitchable hairpin between two surfaces such that an optical mechanical motor is produced that operates between two different force-distance curves.

13 Harsh reality: We don t know how to make machines with useful efficiency Max extractable work: Type I: 3.4 kcal/mol efficiency = 2.4% (actual number would be reduced to 0.4% due to quantum yield of cis/trans and trans/cis Type II: 3.5 kcal/mol Exptl efficiency: ~0.08% Gaub, Macromol for polyazopeptide Liphardt et. al., Science 292, 733 (2001)

14 Plasmonic optical properties: Plasmonics without metals; Plasmonic lasers Silver prisms with varying edge lengths Kelly, et al. J. Phys. Chem. B, 2003, 107, Xue, C. & Mirkin, C. Angew. Chem. Int. Ed., 2007, 46,

15 Computational Electrodynamics is a Powerful Simulation Tool for Nanoplasmonics t 1 E H J t H 1 E d J t J t E t p p p p 0 dt 2 Grid or Finite element methods: Discrete Dipole Approximation Finite Difference Time Domain Method Whitney-form Finite Element Method Beyond Conventional Maxwell: Coupled QM + EM

16 Plasmons can also be described with Quantum Mechanics Extinction ~ Im(α(ω)) Raman intensity ~ d ( ) dq α = polarizability Q= normal coordinate of molecule ω= frequency (needs to be on-resonance for metal excitation) Determine d ( ) ( ) and dq 2 from TDDFT using ADF Jensen, Autschbach, Schatz, JCP 122, (2005) Jensen, Zhao, Autschbach, Schatz JCP, 123 (2005) Much earlier version of this: P.K.K. Pandey and G.C. Schatz, J. Chem. Phys., 80, (1984).

17 Connection of Electronic Structure Results with Continuum Electrodynamics has been Established photon energy (ev) ev Ag nm ev /edge length (atoms) 3.0 ev Ag nm A/ size 2.5 ev 20 nm Ag tetrahedron 10 5 atoms C. Aikens, S. Li, GCS, JPC C 112, (2008)

18 Recent recognition that there are plasmonic states in polycyclic aromatic hydrocarbons opens the door to molecular plasmonics JPC 117, 21466, 2013 ACS Nano 4, 3635, 2013

19 Lattice plasmons were discovered by simulation; now being used in lasing applications S. Zou, N. Janel, and G. C. Schatz, JCP 120, (2004). Nature Nano 8, (2013)

20 Transitioning from nano to meso: Metamaterials from DNA-linked nanostructures Macfarlane, et al. Science, 2011, 334, Cutler, et al. JACS, 2012, 134,

21 3D Superlattices: Making Well-Define Crystal Habits Auyeung, et al., Nature 2014, 505, 73. scale bar: 5 um

22 Some crystal habits can be used for optical cavity applications Micro-Geometry: Photonic modes Nano-Materials: Electronic states Fabry-Perot modes Surface plasmon: Au/Ag nanoparticles Whispering gallery modes Exciton: Quantum dots Light focusing Plasmon-exciton complexes

23 Experiments have recently confirmed the influence of crystal habit on optical property M. B. Ross, J. C. Ku, V. M. Vaccarazza, GCS, C. A. Mirkin, to be published

24 The future: 1. Opportunities for simulation often involving a coupling of atomistic theories with continuum theories. 2. Intermediate length scale theories, such as coarse-grained theories are also important, but high performance computing with bottomup theory has an important role to play. 3. Opportunities are driven by theory/experiment collaboration. Often theory can be used to tell what is possible, and what are fundamental limits. But the interplay with experiment is crucial.