Deformation of Nanotubes Yang Xu and Kenny Higa MatSE 385

Slides:



Advertisements
Similar presentations
Simulazione di Biomolecole: metodi e applicazioni giorgio colombo
Advertisements

Introduction to Computational Chemistry NSF Computational Nanotechnology and Molecular Engineering Pan-American Advanced Studies Institutes (PASI) Workshop.
Molecular dynamics modeling of thermal and mechanical properties Alejandro Strachan School of Materials Engineering Purdue University
Transfer FAS UAS SAINT-PETERSBURG STATE UNIVERSITY COMPUTATIONAL PHYSICS Introduction Physical basis Molecular dynamics Temperature and thermostat Numerical.
Modelling of Defects DFT and complementary methods
1 Physical Chemistry III Molecular Interactions Piti Treesukol Chemistry Department Faculty of Liberal Arts and Science Kasetsart University :
A Digital Laboratory “In the real world, this could eventually mean that most chemical experiments are conducted inside the silicon of chips instead of.
Introduction to Molecular Orbitals
Chapter 3 Electronic Structures
Molecular Modeling: Molecular Mechanics C372 Introduction to Cheminformatics II Kelsey Forsythe.
Quantum Mechanics and Force Fields Hartree-Fock revisited Semi-Empirical Methods Basis sets Post Hartree-Fock Methods Atomic Charges and Multipoles QM.
Computational Chemistry
Molecular Modeling: Semi-Empirical Methods C372 Introduction to Cheminformatics II Kelsey Forsythe.
Computational Solid State Physics 計算物性学特論 第2回 2.Interaction between atoms and the lattice properties of crystals.
Screening of Water Dipoles inside Finite-Length Carbon Nanotubes Yan Li, Deyu Lu,Slava Rotkin Klaus Schulten and Umberto Ravaioli Beckman Institute, UIUC.
Master : Vitali Ghoghoberidze Supervisor : Full Professor Avtandil Tavkhelidze PhD David Kakulia.
Molecular Dynamics Simulation (a brief introduction)
Lecture 3 – 4. October 2010 Molecular force field 1.
Molecular Dynamics Classical trajectories and exact solutions
Joo Chul Yoon with Prof. Scott T. Dunham Electrical Engineering University of Washington Molecular Dynamics Simulations.
Physics of fusion power Lecture 2: Lawson criterion / some plasma physics.
Plasma Kinetics around a Dust Grain in an Ion Flow N F Cramer and S V Vladimirov, School of Physics, University of Sydney, S A Maiorov, General Physics.
Flow of Fluids and Solids at the Nanoscale Thomas Prevenslik QED Radiations Discovery Bay, Hong Kong, China Proc. 2nd Conference on Heat Transfer Fluid.
Physics of Fusion power Lecture4 : Quasi-neutrality Force on the plasma.
1 Physical Chemistry III Molecular Interactions Piti Treesukol Chemistry Department Faculty of Liberal Arts and Science Kasetsart University :
Molecular Modeling Fundamentals: Modus in Silico C372 Introduction to Cheminformatics II Kelsey Forsythe.
Solid State Physics Bands & Bonds. PROBABILITY DENSITY The probability density P(x,t) is information that tells us something about the likelihood of.
Algorithms and Software for Large-Scale Simulation of Reactive Systems _______________________________ Ananth Grama Coordinated Systems Lab Purdue University.
Molecular Dynamics Simulations An Introduction TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAA A A A A Pingwen Zhang.
Molecular Dynamics Simulation Solid-Liquid Phase Diagram of Argon ZCE 111 Computational Physics Semester Project by Gan Sik Hong (105513) Hwang Hsien Shiung.
Iain D. Boyd and Brandon Smith Department of Aerospace Engineering University of Michigan Ann Arbor, MI Molecular Dynamics Simulation of Sputtering.
Molecular Dynamics A brief overview. 2 Notes - Websites "A Molecular Dynamics Primer", F. Ercolessi
1 Electric Potential Reading: Chapter 21 Chapter 21.
Laboratoire Matériaux et Microélectronique de Provence UMR CNRS Marseille/Toulon (France) - M. Bescond, J-L. Autran, M. Lannoo 4 th.
Force Fields and Numerical Solutions Christian Hedegaard Jensen - within Molecular Dynamics.
Adsorption on Single-Walled Carbon Nanohorns Adam Scrivener.
Industrial chemistry Kazem.R.Abodollah (Asiaban) Introduction to Industrial chemistry 1.
Tutorial 4 Derek Wright Wednesday, February 9 th, 2005.
Molecular bonding. Molecular Bonding and Spectra The Coulomb force is the only one to bind atoms. The combination of attractive and repulsive forces creates.
Molecular Mechanics Studies involving covalent interactions (enzyme reaction): quantum mechanics; extremely slow Studies involving noncovalent interactions.
SECTION 2-1 CONT. Bonding. TYPES OF CHEMICAL BONDS  Bonds involve the electrons in an atom.  1. Ionic Bonds Electrons are transferred from one atom.
MODELING MATTER AT NANOSCALES 3. Empirical classical PES and typical procedures of optimization Classical potentials.
Van der Waals and Electrostatic Forces Acting on a Carbon Nanotubes Research Center for Applied Sciences, Academia Sinica,Taipei, Taiwan contact: Evgeny.
Chapter2. Some Thermodynamics Aspects of Intermolecular Forces Chapter2. Some Thermodynamics Aspects of Intermolecular Forces 한국과학기술원 화학과 계면화학 제 1 조 김동진.
Molecular Modelling - Lecture 2 Techniques for Conformational Sampling Uses CHARMM force field Written in C++
1 Statistical Mechanics and Multi- Scale Simulation Methods ChBE Prof. C. Heath Turner Lecture 18 Some materials adapted from Prof. Keith E. Gubbins:
1 CE 530 Molecular Simulation Lecture 14 Molecular Models David A. Kofke Department of Chemical Engineering SUNY Buffalo
Physics “Advanced Electronic Structure” Lecture 1. Theoretical Background Contents: 1. Historical Overview. 2. Basic Equations for Interacting Electrons.
Quantum Mechanics/ Molecular Mechanics (QM/MM) Todd J. Martinez.
Molecular dynamics (MD) simulations  A deterministic method based on the solution of Newton’s equation of motion F i = m i a i for the ith particle; the.
Computational Physics (Lecture 11) PHY4061. Variation quantum Monte Carlo the approximate solution of the Hamiltonian Time Independent many-body Schrodinger’s.
© Copyright Pearson Prentice Hall Slide 1 of 33 Polar Bonds and Molecules Snow covers approximately 23 percent of Earth’s surface. Each individual snowflake.
Why do molecules form? Molecular bonds Rotations Vibrations Spectra Complex planar molecules Molecules CHAPTER 9 Molecules Johannes Diderik van der Waals.
Intermolecular Forces
Macromolecular / giant covalent Molecular / simple covalent
Overview of Molecular Dynamics Simulation Theory
Chapter 2 Molecular Mechanics
5. Conductors and dielectrics
Solid state physics Lecture 3: chemical bonding Prof. Dr. U. Pietsch.
Molecular bonding.
Macromolecular / giant covalent Molecular / simple covalent
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Physics of fusion power
Masoud Aryanpour & Varun Rai
Chapter 29 Electric Potential Reading: Chapter 29.
Algorithms and Software for Large-Scale Simulation of Reactive Systems
Molecular Dynamics(MD)
Physical Chemistry Chapter VI Interaction between Molecules 2019/5/16
Presentation transcript:

Deformation of Nanotubes Yang Xu and Kenny Higa MatSE 385

Introduction We have adopted a simple model of a nanoelectromechanical switch [1] We have simulated the effect of introducing a defect by deleting atoms in a cylindrical region Presentation: Pull-in voltages of carbon nanotube-based nanoelectromechanical switches. Marc Dequesnes, et. al

Algorithm overview Hybrid tight-binding method [2] combines features of both ab initio and MD methods

Schrodinger equation Wave function Charge density Poisson solver Potential distribution Initial guess potential Solve Schrodinger equation self-consistently Iteration to get self- consistent results Tight-binding approximation: consider interactions between layers (cross-sectional slices) of the nanotube Interaction potential is non-zero only for nearest neighbors Copyright V. H. Crespi. Distributed under the Open Content License (

Schrodinger equation Wave function Charge density Poisson solver Potential distribution Initial guess potential Solve Schrodinger equation self-consistently * Construct the Potential Matrix Iteration Only considering potential terms of Hamiltonian Kinetic part which is relative to temperature (E k =3/2nKT) is constant in our model Image force e  m-n EFEF EcEc Metal Nanotube * Schottky barrier potential is included

Schrodinger equation Wave function Charge density Poisson solver Potential distribution Initial guess potential Solve Schrodinger equation self-consistently * Tight-Binding Approximation Iteration We got a block-diagonal matrix eigenvalue problem

Solve Schrodinger equation self-consistently Finite-element method used to solve Poisson equation to determine potential field Charge is non-zero only in nanotube giving sparse matrix system Iterate until self-consistent solution is obtained Schrodinger equation Wave function Charge density Poisson solver Potential distribution Initial guess potential Iteration

Quantum results

Electrostatic Force applied on the nanotube

Molecular dynamics Initialize velocities from Maxwell- Boltzmann distribution Velocity Verlet algorithm used to update carbon atom positions Particle motion influenced by van der Waals interactions, covalent bonding, electric field

Van der Waals interactions Nanotube interactions with graphite plane important on nanoscale [1] Modeled using Lennard-Jones potential Existing code used to calculate van der Waals force per unit length [1] Horizontal forces neglected

Tersoff Potential Tersoff potential has been successfully for carbon bonding in graphite, diamond [3] Realistic model of bond energies and lengths Sum over nearest neighbors Attractive and repulsive forms similar to Morse potential but considers bond order

Electric field Electric charge per length determined from quantum calculations Force due to external field calculated from analytical expression Force due to induced electric field calculated using image charges Horizontal forces neglected

Some pictures

Another picture

One last picture

Conclusion Quantum effects are important at the nanotube ends Simulating 6e-11 seconds takes around 10 hours We have not generated enough data for quantitative conclusions Nanotube has not made contact with graphite plate Simulations suggest that nanotubes tend to bend most near point of attachment

References [1] Desquesnes, M., Rotkin, S. V., and Aluru, N. R. “Calculation of pull-inn voltages for carbon-nanotube-based nanoelectromechanical switches”, Nanotechnology (13) , [2] Clementi E. “Ab initio computations in atoms and molecules”, (reprinted from IBM Journal of Research and Development 9, 1965), IBM J. Res. Dev. 44 (1- 2: , [3] Brenner, D. W. “Emperical potential for hydrocarbons for use in simulating the chemical vapor deposition of diamond films”, Physical Review B. Volume 42, Number 15: , Special thanks to Yan Li, Zhi Tang, Rui Qiao, and Marc Dequesnes for their advice and for writing the code that formed the basis for our project.