First principle simulations in nano science
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First Principle Simulations in Nano-science. Tianshu Li University of California, Berkeley University of California, Davis. Outline. Introduction to the First Principle method Overview of Density Functional Theory Density Functional Theory calculation in Nano science

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First principle simulations in nano science

First Principle Simulations in Nano-science

Tianshu Li

University of California, Berkeley

University of California, Davis


Outline

Outline

  • Introduction to the First Principle method

  • Overview of Density Functional Theory

  • Density Functional Theory calculation in Nano science

  • Limitations in current theory

  • Summary remarks


It s all about quantum mechanics

It’s all about quantum mechanics!

  • Nano scope where the focus is electron, atom, or molecule.

  • The fundamental law in atomic world is Quantum Mechanics


Contribution of quantum mechanics to the technology

Contribution of Quantum Mechanics to the Technology

  • Bloch theorem-1928

  • Wilson-Implication of band theory-Insulators/metal-1931

  • Wigner-Seitz-Quantitative calculation for Na-1935

  • Slater-Bands of Na-1934

  • Bardeen-Fermi surface of a metal-1935

  • Invention of the Transistor-1940

    • Bardeen & Shockley

  • BCS theory for superconductivity-1957

    • Bardeen, Cooper, & Schrieffer

  • Kohn-Density Functional Theory-1965


What is the first principle method

What is the “First Principle” method?

  • “First principle” means things that cannot be deduced from any other

  • Ab initio : “From the beginning”

  • Most of physical properties are predictable based on the quantum mechanics laws.

  • Unlike many other simulation methods, the only input information in “First Principle” calculation is just the atomic number!

  • The most accurate simulation technique.


Real difficulty

Real difficulty

  • The simplest problem: single s electron in H atom

  • A little more difficult problem: two s electrons in H2 molecule (2x2 matrix)

  • A more tougher one: four s and eight p electrons in O2 molecule (12x12 matrix)

  • An overwhelming case: 1023 electrons (s, p, d, f,…) in real materials? (1023x1023 matrix)

“The difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble”

--Dirac


Basic methods of electronic structure calculations

Basic Methods of Electronic Structure Calculations

  • Hylleras-Numerically exact solution for H2-1929

  • Slater-Augmented Plane Waves-1937

  • Herring-Orthogonalized Plane Waves-1940

  • Boys-Gaussian basis functions-1950

  • Phillips, Kleinman, Antoncik-Pseudopotentials-1950

  • Kohn-Density Functional Theory-1964

  • Anderson-Linearized Muffin Tin Orbitals-1975


Most frequently used methods in simulating nano scale systems

Most frequently used methods in simulating nano-scale systems

  • Density Functional Theory

    • Most popular and widely adopted technique

  • Quantum Chemistry

    • Finite systems like molecules

  • Quantum Monte Carlo

    • Explicit many-body method, yet computationally demanding

  • Tight-binding Method

    • Fast, but parameters are adjustable. Empirical method in its nature


One of the most active areas in science

One of the most active areas in science

  • Physics Today, June 2005


Overview of dft

Overview of DFT

  • What is Density Functional Theory (DFT)?

    • Walter Kohn, 1998 chemistry Nobel prize

    • Hohenberg-Kohn theorems

    • Kohn-Sham

  • What can it do?

    • Mapping any interacting many-body system exactly to a much easier-to-solve non-interacting problem

  • Why is it important?

    • Numerous applications in both science and engineering. Open a new field.


Total hamiltonian for the interacting electron ion system

Total Hamiltonian for the interacting electron-ion system

Tel: Kinetic energy of electrons

Vel-ion: Electron-ion interactions

Vel-el: Electron-electron interactions

Vion-ion: Ion-ion interactions

A nasty problem!


Hohenberg kohn hk theorem

Hohenberg-Kohn (HK) theorem

  • HK theorem:

    • All properties of many-body system are determined by the ground state density n0(r)

    • The ground state total energy E is a functional of n0(r)

Aside: Functional vs. Function

  • Function maps a variable to a result

    • For example: g(x)->y

  • Functional maps a function to a result

    • For example: f[n(r)]->y


A diagram of hk theorem

A diagram of HK theorem


Comments on hk theorem

Comments on HK theorem

  • The functional is universal

    • Independent on the external potential

  • Exact theory, no approximation

    • Proof is rather simple, by contradiction

  • A new idea of solving ground state problem

    • The ground state total energy should only depend on the ground state electron density n(r).


Kohn sham ks equation interacting non interacting

Kohn-Sham (KS) equationInteracting->Non interacting

  • A non-interacting system should have the same ground state as interacting system

  • Only the ground state density and energy are required to be the same as in the original many-body system


Ks diagram

KS Diagram

Original system

Interacting

Kohn-Sham system

Non-interacting

KS

HK

HK


Solving ks self consistently

Initial guess

n(r)

Solve Kohn-Sham equation

EKSФKS=εKSФKS

Calculate electron density

ni(r)

No

Self consistent?

Yes

Output

Solving KS self-consistently

  • Solving an interacting many-body electrons system is equivalent to minimizing the Kohn-Sham functional with respect to electron density.


Comments of dft

Comments of DFT

  • The Kohn-Sham wavefunctions do not have explicit physical interpretations

  • Without further approximation, DFT remains “useless” in practice.

Exc[n]: contains everything that we don’t know. Unknown functional!


Approximation in solving ks equation local density approximation lda

Approximation in Solving KS equationLocal Density Approximation (LDA)

  • The simplest and easiest approximation

    • Assume Exc[n(r)] is a sum of contributions from each point depending only on the density at each point, i.e.,

    • εxc(n) can be computed exactly from Quantum Monte Carlo method

  • In principal, only supposed to work in a uniform electronic system


Approximation in solving ks equation local density approximation lda1

Approximation in Solving KS equationLocal Density Approximation (LDA)

  • In practice, LDA works surprisingly well for many systems.

    • One of the most successful approximations

    • Still the most frequently used approximation nowadays, especially in materials science and physics.

  • LDA underestimates the Ex by 10% while overestimates the Ec by 200~300%. Usually Ex~10Ec, so net Exc (=Ex+Ec) is typically underestimated by ~7%.


Approximation in solving ks equation generalized gradient approximation gga

Approximation in Solving KS equationGeneralized Gradient Approximation (GGA)

  • Include the gradient of the density in functional, so that the exchange-correlation functional is non-local.

  • Improve performance in finite systems, like molecules.

  • Widely adopted in chemistry and biology

    • Why Kohn got a Nobel prize in Chemistry rather than Physics


Comparisons between predictions based on dft and experiments

Comparisons between predictions based on DFT and experiments


Prediction of new phase of si based on first principle calculations

Prediction of new phase of Si based on First Principle calculations

  • Phase transitions of Si under Pressure:

    • Si was predicted to be metal under very high pressure (>110GPa), which was then verified by experiments.

* M.Y. Tin and M.L. Cohen, Physical Review B 26, 5668(1982)


Comparison of the calculated and measured phonon band structures of nial

Comparison of the calculated and measured phonon band structures of NiAl

* Experimental data of phonon frequencies are extracted from M. Mostoller et al., Physical Review B 40, 2856(1989)


Cleavage anisotropy in transition metal aluminides

* NiAl: {100} being unfavorable

* FeAl: Preference of {100} type of cleavage

Cleavage anisotropy in Transition-metal Aluminides

* K.-M. Chang, R. Darolia, and H.A. Lipsitt,, Acta. Metall. Mater. 40, 2727 (1992)

  • Tianshu Li, J.W. Morris, Jr., D.C. Chrzan, Phys. Rev. B 70, 054107 (2004)

  • Tianshu Li, J.W. Morris, Jr., D. C. Chrzan, Phys. Rev. B 73, 024105 (2006)


Elastic moduli predicted by first principle method in ti v alloys

Elastic moduli predicted by First principle method in Ti-V alloys

Tianshu Li, J.W. Morris, Jr., D.C. Chrzan, to be submitted


Application in nano science

Application in Nano Science

  • Nano-materials containing 100~1000 atoms are the perfect match to the first principle (quantum) simulation.

  • Experimental technique alone is not adequate to probe all the features in nano structure

    • For example, surface structure

  • First Principle method can separate different physical effects and assess their relevance in determining various properties.


Schematic representations of nano structures

Schematic representations of Nano-structures


Quantum confinement

Quantum Confinement

  • Optical properties of nano-materials depend on the size (Quantum Dots)

CdSe: Size tunable energy gap provides size dependent emission

  • Visible light carries the photon energies 1.7eV~3eV.

Size of nano particles


Si nano clusters surface compensation

Si nano clustersSurface compensation

A.J. Williamson J. Grossman, R.Q. Hood, A. Puzder and G. Galli, Phys. Rev. Lett, 89, 196803 (2002).

Reboredo FA, Galli G, Phys. Chem. B 109, 1072 (2005).


Si quantum dots

Density Functional Theory and Quantum Monte Carlo calculations

5

Experiments

“Perfect” Si Q-Dots

4

Optical Absorption Gap (eV)

3

2

1

0

0

2

4

6

8

Q-Dot Diameter (nm)

Si Quantum Dots

  • Consider core, surface and solvent effects, one at a time:

  • Gaps reveal quantum confinement.

  • Key role of surfacechemistry (e.g. oxygen) and surface reconstruction.

A.Puzder et al. J Am Chem Soc 2003.;A Puzder et al, Phys Rev Lett 2003.;E Draeger et al, Phys Rev Lett 2003; F.Reboredo et al., J.Am Chem Soc 2003

D.Prendergast et al., JACS 2004; F.Reboredo et al. Nanolett. 2004 and JPC-B 2005


Diamond nanoparticles surface reconstruction

Diamond nanoparticlesSurface reconstruction

J.-Y. Raty, G. Galli, C. Bostedt, T. W. van Buuren, and L. J. Terminello, Phys. Rev. Lett. 90, 037401 (2003)


Ultradispersity of nano diamonds

Ultradispersity of nano-diamonds

Nano diamonds have stable size distribution between 2~5nm

J.-Y. Raty and G. Galli, Nature Materials 2, 792 (2003)


Cdse nano particles surface reconstruction

CdSe nano-particlesSurface reconstruction

A. Puzder, A.J. Williamson, F. Gygi, and G. Galli, Phy. Rev. Lett. 92, 217401 (2004)


Limitations of current techniques

Limitations of current techniques

  • Size restrictions. Max ~ 1000 atoms

  • Excited states properties, e.g., optical band gap.

  • Strong or intermediate correlated systems, e.g., transition-metal oxides

  • Soft bond between molecules and layers, e.g., Van de Waals interaction


The band gap problem

The band gap problem

  • Excitations are not well described by LDA or GGA within DFT. The Kohn-Sham orbitals are only exact for the ground states.

  • Famous “band gap” problem.

  • Promising solutions:

    • GW calculation

    • QMC


Correlated system

Correlated system

  • Electrons are strongly localized. Sparse system

  • Wrong ground state

  • Promising solutions

    • LDA+U (semi-ab initio)


Weak non local bonding

Weak non-local bonding

  • Soft bonding. Sparse system

  • Wrong ground state

  • Promising solution:

    • Van der Waals Density Functional

H. Rydberg et al., Phy. Rev. Lett. 91, 126402 (2003)


Summary remarks

Summary Remarks


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