Computational Chemistry Molecular Mechanics/Dynamics F = Ma Quantum Chemistry Schr Ö dinger Equation H  = E 

Slides:



Advertisements
Similar presentations
Modelling of Defects DFT and complementary methods
Advertisements

Chemistry 6440 / 7440 Density Functional Theory. Electronic Energy Components Total electronic energy can be partitioned E = E T + E NE +E J + E X +E.
Tutorial: Time-dependent density-functional theory Carsten A. Ullrich University of Missouri XXXVI National Meeting on Condensed Matter Physics Aguas de.
First Principle Electronic Structure Calculation Prof. Kim Jai Sam ( ) Lab. 공학 ( ) Students : Lee Geun Sik,
CHE Inorganic, Physical & Solid State Chemistry Advanced Quantum Chemistry: lecture 4 Rob Jackson LJ1.16,
Molecular Quantum Mechanics
Introduction to Molecular Orbitals
Chapter 3 Electronic Structures
Time-dependent density-functional theory University of Missouri
Chemistry 6440 / 7440 Semi-Empirical Molecular Orbital Methods.
Density Functionals: Basic DFT Theory Sergio Aragon San Francisco State University CalTech PASI January 4-16, 2004.
Quantum Mechanics Discussion. Quantum Mechanics: The Schrödinger Equation (time independent)! Hψ = Eψ A differential (operator) eigenvalue equation H.
Computational Chemistry Molecular Mechanics/Dynamics F = Ma Quantum Chemistry Schr Ö dinger Equation H  = E 
Density Functional Theory: a first look Patrick Briddon Theory of Condensed Matter Department of Physics, University of Newcastle, UK.
Simulation of X-ray Absorption Near Edge Spectroscopy (XANES) of Molecules Luke Campbell Shaul Mukamel Daniel Healion Rajan Pandey.
Wavefunctions and Energy Levels Since particles have wavelike properties cannot expect them to behave like point-like objects moving along precise trajectories.
Quantum Calculations B. Barbiellini Thematics seminar April 21,2005.
FUNDAMENTALS The quantum-mechanical many-electron problem and Density Functional Theory Emilio Artacho Department of Earth Sciences University of Cambridge.
Lecture 9: Advanced DFT concepts: The Exchange-correlation functional and time-dependent DFT Marie Curie Tutorial Series: Modeling Biomolecules December.
Density Functional Theory And Time Dependent Density Functional Theory
Lecture 8: Introduction to Density Functional Theory Marie Curie Tutorial Series: Modeling Biomolecules December 6-11, 2004 Mark Tuckerman Dept. of Chemistry.
Computational Chemistry
Lectures Introduction to computational modelling and statistics1 Potential models2 Density Functional.
Lecture 17: Excitations: TDDFT Successes and Failures of approximate functionals Build up to many-body methods Electronic Structure of Condensed Matter,
Norm-conserving pseudopotentials and basis sets in electronic structure calculations Javier Junquera Universidad de Cantabria.
The Nuts and Bolts of First-Principles Simulation Durham, 6th-13th December : DFT Plane Wave Pseudopotential versus Other Approaches CASTEP Developers’
Physical Chemistry 2 nd Edition Thomas Engel, Philip Reid Chapter 23 The Chemical Bond in Diatomic Molecules.
Computational Solid State Physics 計算物性学特論 第8回 8. Many-body effect II: Quantum Monte Carlo method.
MODULE 8 APPROXIMATION METHODS I Once we move past the two particle systems, the Schrödinger equation cannot be solved exactly. The electronic inter-repulsion.
First principles electronic structure: density functional theory
Density Functional Theory (DFT) DFT is an alternative approach to the theory of electronic structure; electron density plays a central role in DFT. Why.
H y = E y Density-Functional Theory SchrÖdinger Equation Wavefunction
1 Physical Chemistry III ( ) Chapter 3: Atomic Structure Piti Treesukol Kasetsart University Kamphaeng Saen Campus.
Computational Chemistry Molecular Mechanics/Dynamics F = Ma Quantum Chemistry Schr Ö dinger Equation H  = E 
Electronic Band Structures electrons in solids: in a periodic potential due to the periodic arrays of atoms electronic band structure: electron states.
PA4311 Quantum Theory of Solids Quantum Theory of Solids Mervyn Roy (S6) www2.le.ac.uk/departments/physics/people/mervynroy.
Background 1927: Introduction of the Thomas-Fermi model (statistics of electrons). 1964: Hohenberg-Kohn paper proving existence of exact Density Function.
Lecture 12. Basis Set Molecular Quantum Mechanics, Atkins & Friedman (4th ed. 2005), Ch Essentials of Computational Chemistry. Theories and Models,
Lecture 17. Density Functional Theory (DFT)
Fundamentals of DFT R. Wentzcovitch U of Minnesota VLab Tutorial Hohemberg-Kohn and Kohn-Sham theorems Self-consistency cycle Extensions of DFT.
Density Functional Theory Richard M. Martin University of Illinois
Density Functional Theory A long way in 80 years L. de Broglie – Nature 112, 540 (1923). E. Schrodinger – 1925, …. Pauli exclusion Principle.
Ab initio Reactant – Transition State Structure – Product 1.Selection of the theoretical model 2.Geometry optimization 3.Frequency calculation 4.Energy.
Time-Dependent Density Functional Theory (TDDFT) part-2
Physics “Advanced Electronic Structure” Lecture 1. Theoretical Background Contents: 1. Historical Overview. 2. Basic Equations for Interacting Electrons.
Fundamentals of Density Functional Theory Santa Barbara, CA Walter Kohn Physics-Chemistry University of California, Santa Barbara
Ch 12. Chemical Bond in Diatomic Molecules MS310 Quantum Physical Chemistry The chemical bond is at the heart of chemistry. A qualitative molecular orbital.
Physics “Advanced Electronic Structure” Lecture 2. Density Functional Theory Contents: 1. Thomas-Fermi Theory. 2. Density Functional Theory. 3.
Lecture 11. Basis Functions & Basis Set
Quantum Chemistry in Molecular Modeling: Our Agenda Postulates, Schrödinger equation & examples (Ch. 2-8) Computational chemistry (Ch. 16) Hydrogen-like.
Start. Technische Universität Dresden Physikalische Chemie Gotthard Seifert Tight-binding Density Functional Theory DFTB an approximate Kohn-Sham DFT.
Advanced methods of molecular dynamics 1.Monte Carlo methods 2.Free energy calculations 3.Ab initio molecular dynamics 4.Quantum molecular dynamics 5.Trajectory.
© copyright 2011 William A. Goddard III, all rights reservedCh121a-Goddard-L14 Periodic Boundary Methods and Applications: Ab-initio Quantum Mechanics.
Time-Dependent Density Functional Theory (TDDFT) Takashi NAKATSUKASA Theoretical Nuclear Physics Laboratory RIKEN Nishina Center CNS-EFES Summer.
Lecture 9. Many-Electron Atoms
Computational Physics (Lecture 22) PHY4061. In 1965, Mermin extended the Hohenberg-Kohn arguments to finite temperature canonical and grand canonical.
Electron density: Probability of finding one electron of arbitrary spin within a volume element dr 1 (other electrons may be anywhere). Properties of electron.
Comp. Mat. Science School Electrons in Materials Density Functional Theory Richard M. Martin Electron density in La 2 CuO 4 - difference from sum.
Ch.1. Elementary Quantum Chemistry
Electrical Engineering Materials
Structure of Presentation
Introduction to Tight-Binding
Yosuke Harashima, Keith Slevin
Density Functional Theory (introduced for many-electron systems)
Department of Chemistry University of Hong Kong
Time Dependent Density Functional Theory (TDDFT)
Time-Dependent Density Functional Theory (TDDFT)
Basics of DFT and TDDFT E.K.U. Gross Max-Planck Institute of
TDDFT Prof. Dr. E.K.U. Gross Prof. Dr. Mark Casida.
Orbitals, Basis Sets and Other Topics
Presentation transcript:

Computational Chemistry Molecular Mechanics/Dynamics F = Ma Quantum Chemistry Schr Ö dinger Equation H  = E 

H  E  SchrÖdinger Equation Hamiltonian H =  h 2 /2m e )  i  i 2  i V(r i )  i  j e 2 /r ij Wavefunction Energy Density-Functional Theory Text Book: Density-Functional Theory for Atoms and Molecules by Robert Parr & Weitao Yang

Hohenberg-Kohn Theorems 1 st Hohenberg-Kohn Theorem: The external potential V(r) is determined, within a trivial additive constant, by the electron density  (r). Implication: electron density determines every thing.

2 nd Hohenberg-Kohn Theorem: For a trial density  (r), such that   (r)  0 and, Implication: Variation approach to determine ground state energy and density.

2 nd Hohenberg-Kohn Theorem: Application Minimize E ν [ρ] by varying ρ(r) : under constraint: ( N is number of electrons ) Then, construct Euler-Langrage equation : Minimize this Euler-Langrage equation: (chemical potential or Fermi energy)

Thomas-Fermi Theory

Ground state energy Constraint: number of electrons

Using :

Kohn-Sham Equations /2 In analogy with the Hohenberg-Kohn definition of the universal function F HK [ρ], Kohn and Sham invoked a corresponding noninteracting reference system, with the Hamiltonian in which there are no electron-electron repulsion terms, and for which the ground- state electron density is exactly ρ. For this system there will be an exact determinantal ground-state wave function The kinetic energy is Ts[ρ]:

/2 For the real system, the energy functional

ν eff (r) is the effective potential: ν xc (r) is exchange-correlation potential:

Density Matrix One-electron density matrix: Two-electron density matrix:

Thomas-Fermi-Dirac Theory

where, r s is the radius of a sphere whose volume is the effective volume of an electron;

The correlation energy: At high density limit: At low density limit: where, r s is the radius of a sphere whose volume is the effective volume of an electron. In general:

Xα method If the correlation energy is neglected: we arrive at Xα equation: Finally:

Further improvements General Gradient Approximation (GGA): Exchange-correlation potential is viewed as the functional of density and the gradient of density: Meta-GGA: Exchange-correlation potential is viewed as the functional of density and the gradient of density and the second derivative of the density: Hyper-GGA: further improvement

The hybrid B3LYP method The exchange-correlation functional is expressed as: where,,

B3LYP/6-311+G(d,p)B3LYP/6-311+G(3df,2p) RMS=21.4 kcal/molRMS=12.0 kcal/mol RMS=3.1 kcal/molRMS=3.3 kcal/mol B3LYP/6-311+G(d,p)-NEURON & B3LYP/6-311+G(d,p)-NEURON: same accuracy Hu, Wang, Wong & Chen, J. Chem. Phys. (Comm) (2003)

Usage: interpret experimental results numerical experiments Goal: predictive tools Inherent Numerical Errors caused by Finite basis set Electron-electron correlation Exchange-correlation functional How to achieve chemical accuracy: 1~2 kcal/mol? First-Principles Methods

In Principle: DFT is exact for ground state TDDFT is exact for excited states To find: Accurate / Exact Exchange-Correlation Functionals Too Many Approximated Exchange-Correlation Functionals System-dependency of XC functional ???

When the exact XC functional is projected onto an existing XC functional, it should be system-dependent Existing Approx. XC functional

E XC [  ] is system-dependent functional of  Any hybrid exchange-correlation functional is system-dependent

XC Functional Exp. Database Neural Networks Neural-Networks-based DFT exchange-correlation functional Descriptors must be functionals of electron density

v- and N-representability We can minimize E[ρ] by varying density ρ, however, the variation can not be arbitrary because this ρ is not guaranteed to be ground state density. This is called the v-representable problem. A density ρ (r) is said to be v-representable if ρ (r) is associated with the ground state wave function of Homiltonian Ĥ with some external potential ν(r).

v- and N-representability For more information about N-representable density, please refer to the following papers. ①. E.H. Lieb, Int. J. Quantum Chem. (1983), 24(3), p ②. J. E. Hariman, Phys. Rev. A (1988), 24(2), p

c cc c

Basis set of GTFs STO-3G, 3-21G, 4-31G, 6-31G, 6-31G*, 6-31G**  complexity & accuracy Minimal basis set: one STO for each atomic orbital (AO) STO-3G: 3 GTFs for each atomic orbital 3-21G: 3 GTFs for each inner shell AO 2 CGTFs (w/ 2 & 1 GTFs) for each valence AO 6-31G: 6 GTFs for each inner shell AO 2 CGTFs (w/ 3 & 1 GTFs) for each valence AO 6-31G*: adds a set of d orbitals to atoms in 2nd & 3rd rows 6-31G**: adds a set of d orbitals to atoms in 2nd & 3rd rows and a set of p functions to hydrogen Polarization Function

Diffuse/Polarization Basis Sets: For excited states and in anions where electronic density is more spread out, additional basis functions are needed. Polarization functions to 6-31G basis set as follows: 6-31G* - adds a set of polarized d orbitals to atoms in 2 nd & 3 rd rows (Li - Cl). 6-31G** - adds a set of polarization d orbitals to atoms in 2 nd & 3 rd rows (Li- Cl) and a set of p functions to H Diffuse functions + polarization functions: 6-31+G*, G*, 6-31+G** and G** basis sets. Double-zeta (DZ) basis set: two STO for each AO

6-31G for a carbon atom:(10s12p)  [3s6p] 1s2s2p i (i=x,y,z) 6GTFs 3GTFs 1GTF3GTFs 1GTF 1CGTF 1CGTF 1CGTF 1CGTF 1CGTF (s)(s) (s) (p) (p)

Time-Dependent Density-Functional Theory (TDDFT) Runge-Gross Extension: Phys. Rev. Lett. 52, 997 (1984) Time-dependent system  (r,t)  Properties P (e.g. absorption) TDDFT equation: exact for excited states

Yokojima & Chen, Chem. Phys. Lett., 1998; Phys. Rev. B, 1999  t    

HK Theorem P. Hohenberg & W. Kohn, Phys. Rev. 136, B864 (1964) Ground-state density functional theory (DFT)  First-principles method for isolated systems Time-dependent DFT for excited states (TDDFT) RG Theorem E. Runge & E. K. U. Gross, Phys. Rev. Lett. 52, 997 (1984)  r,t  Excited state properties  r  all  system properties

Open Systems particle energy H = H S + H B + H SB Time-dependent density-functional theory for open systems

 First-principles method for open systems?

A real function is said to be analytic if it possesses derivatives of all orders and agrees with its Taylor series in the neighborhood of every point. Analyticity of basis functions Plane wave Slater-type orbital Gaussian-type orbital Linearized augmented plane wave (LAPW) Is the electron density function of any physical system a real analytical function ? D (r)(r)

 Holographic electron density theorem for time- independent systems Fournais (2004) Mezey (1999) Riess and Munch (1981)  D (r)  (r)  system properties Analytical continuatio n D (r)(r)

 Holographic electron density theorem for time- dependent systems It is difficult to prove the analyticity for  (r,t) rigorously! D  (r,t)  D (r,t) v(r,t)  system properties Holographic electron density theorem X. Zheng and G.H. Chen, arXiv:physics/ (2005); Yam, Zheng & Chen, J. Comput. Theor. Nanosci. 3, 857 (2006); Recent progress in computational sciences and engineering, Vol. 7A, 803 (2006); Zheng, Wang, Yam, Mo & Chen, PRB (2007).

Existence of a rigorous TDDFT for Open System The electron density distribution of the reduced system determines all physical properties or processes of the entire system!

Auguries of Innocence William Blake To see a world in a grain of sand, And a heaven in a wild flower, Hold infinity in the palm of your hand, And eternity in an hour...

Time-Dependent Density-Functional Theory EOM for density matrix: Time–dependent Kohn-Sham equation:

 Time-Dependent DFT for Open Systems Left electroderight electrode system to solve boundary condition Poisson Equation with boundary condition via potentials at S L and S R  L  R Dissipation functional Q (energy and particle exchange with the electrodes) Zheng, Wang, Yam, Mo & Chen, Phys. Rev. B 75, (2007)

Quantum kinetic equation for transport (EOM for Wigner function)  (r,r’;t)=  (R,  ;t)  Wigner function: f(R, k; t) Fourier Transformation with R = (r+r’)/2;  = r-r’ Our EOM: First-principles quantum kinetic equation for transport Very General Equation: Time-domain, O(N) & Open systems! Quantum Dissipation Theory (QDT): Louiville-von Neumann Equation where  is the reduced density matrix of the system Our theory: rigorous one-electron QDT

System: (5,5) Carbon Nanotube w/ Al(001)-electrodes Sim. Box:60 Carbon atoms & 48x2 Aluminum atoms

Xiamen, 12/2009 Color: Current Strength Yellow arrow: Local Current direction Transient Current Density Distribution through Al-CNT-Al Structure Carbon Nanotube Al Crystal Time dependent Density Func. Theory Al Crystal

Transient current (red lines) & applied bias voltage (green lines) for the Al- CNT-Al system. (a) Bias voltage is turned on exponentially, V b = V 0 (1-e - t/a ) with V 0 = 0.1 mV & a = 1 fs. Blue line in (a) is a fit to transient current, I 0 (1-e -t/τ ) with τ = 2.8 fs & I 0 =13.9 nA. (b) Bias voltage is sinusoidal with a period of T = 5 fs. The red line is for the current from the right electrode & squares are the current from the left electrode at different times. V b = V 0 (1-e -t/a ) V 0 = 0.1 mV & a = 1 fs Switch-on time: ~ 10 fs

(a) Electrostatic potential energy distribution along the central axis at t = 0.02, 1 and 12 fs. (b) Charge distribution along Al-CNT- Al at t = 4 fs. (c) Schematic diagram showing induced charge accumulation at two interfaces which forms an effective capacitor.

Dynamic conductance calculated from exponentially turn-on bias voltage (solid squares) and sinusoidal bias voltage (solid triangle). The red line are the fitted results. Upper ones are for the real part and lower ones are for the imaginary part of conductance.

R L 7.39 kΩ L 16.6 pH R c 6.45 kΩ (0.5g 0 -1 ) C aF g 0 =2e 2 /h ≈ 18.8 pH L ~ Q/  V = aF ~

Buttiker, Thomas & Pretre, Phys. Lett. A 180, 364 (1993) Science 313, 499 (2006)