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Nanoscale Science

Nanoscale Science

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Nanoscale Science

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  1. Nanoscale Science Jack C. Wells Computational Material Science Group Computer Science Division Oak Ridge National Laboratory Research Alliance for Minorities (RAM) Spring '03 Workshop for Faculty and Mentors

  2. G. A. Aramayo ( G.P. Brown ( O.J. Gonzalez ( B. C. Hathorn ( T. Kaplan ( T. Maier ( M. A. Majidi ( V. Meunier ( M. B. Nardelli ( D. M. Nicholson ( D. W. Noid ( P. Nukala ( B. Radhakrishnan ( G. B. Sarma ( W. A. Shelton ( A. V. Smirnov ( S. Simunovic ( B. G. Sumpter ( M. Upmanyu ( J. C. Wells ( L. Zhang ( X-G Zhang ( J. Zhong ( Computational Materials ScienceGroup Leader: Thomas Schulthess

  3. Computational Materials Science (CMS) • From nano-science to engineering applications. • Engineering sciences • Nano science • Applied mathematics • Soft materials (polymers) • Surface science (catalysis) • Magnetism and magneto transport in nanostructures • Light-weight materials • Carbon based nanostructures • Molecular electronics • Intersection of Two Strategic Thrusts • Computational Sciences ( • Advanced Materials & Nanoscale Science (,

  4. AFM Image Periodic QD arrays 1D QD Array Synthesis • Directed assembly of QDs along engineered DNA. • DNA modified with amine groups as binding sites. • Covalent QD attachment to DNA. • Advantages • Particles at desired locations. • Achieve desired nanometer-scale periodicity. • Long-range order. • Stable backbone along the length of duplex DNA. • Research Issues: • Control site occupation along DNA template. • Methylamine blocks excess binding sites. • Improved control of chemical binding sites on QD. K.A. Stevenson, G. Muralidharan, L. Maya, J.C. Wells, J. Barhen, T.G. Thundat, J. Nanosci. Nanotech. (2002)

  5. Gold nanoparticles bound to DNA strand with 10 nm spacing. Small, periodic structures Periodicity in QD Placement • Regular 1D Arrays • Method to covalently bond inorganic nanoparticles to duplex DNA in a programmable fashion. • Fabrication of nanostructures with nanoscale periodicity.

  6. Electron transport via tunneling HSGATCTA*CAACGGCTCA*CCAAGATCTA*CAACGGCTCA*CCAAGATCTA*CAACGGCTCA*CCAAGATCTA*CAACGGCTCA*CCAA TAGTTGCCGAGTAGGTTCTAGATAGTTGCCGAGTAGGTTCTAGATAGTTGCCGAGTAGGTTCTAGATAGTTGCCGAGTAGGTTCTAGASH Transport in QD Arrays • After assembly, DNA can be removed by UV-ozone technique. • Current measurement through array. • Develop techniques to measure I-V curves. • Use AFM / STM, with probe tip acting as electrode. • Two electrode measurements. Electrode Electrode

  7. Master Equation and Currents Tunneling Rates: • Fermi’s Golden Rule with approximations, • Tunneling between nearest neighbors only, • Neglects the effects of co-tunneling, • Rk, effective resistance of tunneling junction. Master Equation: • Time-development of probabilities for charge configurations, • Most often solved by Monte-Carlo techniques. Current-Voltage Characteristics (Average Current):

  8. The Coulomb Ladder In Collaboration with Dene Farrell, SUNY Brockport

  9. Single-Electron Latching Switch single- electron island Modeling Results: tunnel barrier Vinj (orthodox theory) C23/C = 2 C0/C = 1 Q1/e = -0.425 Q2 = 0 Q3/e= -0.2 kBT/(e2/C) = 0.001 3 2 n = 1 C0 1 axon dendrite n = 0 Va Molecular Implementation: 0 0 R R R R’ N N S C C C C N (2 to 4) R’’ R” R’’ 0 0 gold nanowire gold nanowire 0 0 R R R R” R’’ R’’ C C S C N N S C C C C C R R R R R R 0 0 SiO2 insulation p-Si substrate courtesy: A. Mayr (SBU)

  10. Objectives Elucidate the charging characteristics of monolayer-protected clusters. Describe ligand-cluster interface in MPC. Interpret the charging spectrum of MPCs to provide to distinguish between possible structural configurations for the clusters. Participants W. Andreoni, IBM-Zurich A. Curioni, IBM-Zurich S.A. Shevlin, ORNL/JICS J.C. Wells, ORNL Funding DOE/BES/DMSE ORNL-IBM CRADA Charging Characteristics of Monolayer-Protected Clusters • Computational Approach • Ab-Initio Density-Functional Theory • Pseudopotential Plane Wave (PSPW) • CPMD, NWChem, • Gaussian-type Obitals (LCAO) • NWChem

  11. Structure and Charge Transport in Molecular-Scale Electronics Transmission function computed through the electron-molecule-electrode system shown. • Objectives • Elucidate the role of the atomic structure of the molecule-electrode interface. • Role of charging and Coulomb blockade for molecular-scale latching switches. • Discrimination of bio-molecules (e.g., proteins, DNA. etc.) by their unique “conductance signature”. • Participants • D.J. Dean, P.S. Krstic, J. C. Wells, X.-G. Zhang ORNL • P.T. Cummings, Y. Leng Vanderbilt • D. Keffer, U. Tennessee • Funding • ARDA/ONR • DOE/BES/DMSE • ORNL-LDRD • Computational Approach • Ab-Initio Density-Functional Theory • Tight-binding Approach for Physically Realistic Electrode-molecule interface.

  12. Objectives Elucidate fundamental catalytic nucleation and growth mechanisms for carbon nanotubes. Develop expertise in multiscale modeling of carbon nanotube growth processes. Support ORNL’s experimental program in carbon nanotube growth. Participants R.F. Wood, Z. Zhang ORNL/CMSD D.W. Noid, S. Pannala, B.G. Sumpter, J.C. Wells, ORNL/CSMD Q. Zhang, U. Texas @ Arlington Funding ORNL-LDRD Simulation of Carbon Nanotube Nucleation and Growth Decomposition Rates: Dependence on Concentration, Temperature, Composition? Surface Carbide formation? How stable is it? Diffusion pathways? Catalyst clogging? Is diffusion the growth rate-limiting step? Precipitation of carbon? Is precipitation rate limiting? Control of length, diameter chirality? • Computational Approach • Continuum Mass and Heat Transfer • Ab-Initio Density-Functional Theory • Pseudopotential Plane Wave (PSPW) • CPMD, NWChem, • Gaussian-type Obitals (LCAO) • NWChem

  13. Multiscale Modeling (Overview) Time and space evolution of carbon concentration in the catalyst MD Simulations (Dynamic) Time Scale ~ pico s, Length ~ nm Mass Diffusion Rates Rules for Segregation of carbon into the CNT Growth Interface 2D Continuum Simulations Time Scale ~ ms-s, Length ~ mm Single Carbon Atom Addition (DFT Calculations)

  14. 3 sites for adsorption on Ni38. (100), (111) hcp, and (111) fcc. Localized relaxation of Ni38 at site. C will remain on cluster surface. Stable sites: (100), (110), (111) hcp and fcc. Adsorption Energetics order in same sequence on surface and Ni38. (111) fcc (111) hcp Interstitial (110) fcc (111) hcp (111) (100) (100) Carbon Adsorption on Clusters and Surfaces • Fundamental, new predictions on small NixCy clusters and Ni surfaces. • Insight into adsorption, nucleation for large clusters in CVD growth.

  15. “Ring”(9 C’s) grows into the tube. Energy: Against 9 remote/ separate C’s:-12.69eV Against 9 adjacent C’s: ~ -9 eV Reaction-limited growth. Need to compute Barriers, Dynamics. Surface diffusion barrier (bridge site) between hcp-fcc hollow: DE=0.26 eV. 3 different entries for single C: 2 hexagon, DE = -1.26eV 1 pentagon, DE = +0.63eV Growth of Baby Tubes on Ni(111) Surface Questions: How are C-atoms incorporated into the tube? Concerted motion, ring-by-ring growth Single Atom Addition

  16. Yc = 0.03, Typical Value Yc = 0.001, Carbon Activity = 1 dYc /dn= 0, Zero Flux Condition Schematic 2D Continuum Calculations Model

  17. Concluding Comments • Diversity of Computational Materials Science Research • Favorable collaboration would include RAM student, Faculty Advisor, and ORNL Staff, and remain active outside the constraints of one summer’s project. • Challenge of Undergraduate Research • Match project to student’s knowledge base • More knowledge is better, but we can often “make progress” with limited knowledge/experience. • Motivated, enthusiastic, “self-starters” wanted!