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===Electron density in nanowires using equilibrium density matrix===
===Electron density in nanowires using equilibrium density matrix===
*[http://www.physics.udel.edu/~bnikolic/teaching/phys824/MATLAB/electron_density.m electron_density.m]
*[http://www.physics.udel.edu/~bnikolic/teaching/phys824/MATLAB/electron_density.m electron_density.m]
*[[Media:poisson_schrodinger.m|poisson_schrodinger.m]]
*[[Media:poisson_schrodinger.m|poisson_schrodinger.m]] and [[Media:Fhalf.m|Fhalf.m]]


===DOS of 1D disordered nanowire using eigenvalues + visualization of Anderson localization of eigenfunctions===
===DOS of 1D disordered nanowire using eigenvalues + visualization of Anderson localization of eigenfunctions===

Revision as of 11:35, 28 September 2016

Unix Training

MATLAB Training

Hands-on tutorials by Instructor

nohup matlab -nojvm < your_script.m > output_messages & 

Hands-on tutorials by MathWorks

Books

Reference

Python training

Using Anaconda Python on ulam

  • in order to enable the python environment provided by Anaconda you need to add the following to your ~/.bashrc:
export PATH="/opt/anaconda/1.9.2/bin:$PATH"

MATLAB Scripts

Matrix representation of single-particle Hamiltonians

Electron density in nanowires using equilibrium density matrix

DOS of 1D disordered nanowire using eigenvalues + visualization of Anderson localization of eigenfunctions

Density of states using equilibrium Green functions

  • dos_negf_closed.m computes DOS for finite 1D wire
  • dos_negf_open.m computes DOS for finite 1D wire attached to one or two macroscopic reservoirs
  • graphene_dos.m computes DOS for a supercell of graphene with periodic boundary conditions

Subband structure of graphene nanoribbons using tight-binding models

Quantum transport in 1D nanowires using NEGF

Tunneling magnetoresistance in tight-binding models of magnetic tunnel junctions using NEGF

  • mtj_1d.m (computes TMR of F/I/F MTJs modeled using 1D tight-binding chain)
  • mtj_3d.m (computes TMR of F/I/F MTJs modeled using mixed real space and k-space tight-binding model of 3D junctions

Quantum transport in graphene nanostructures using NEGF

Self.m, (code to compute the conductance of a finite graphene nanoribbon attached to two semi-infinite graphene electrodes)

MATLAB functions

  • matrix_exp.m (Exponential, or any other function with small changed in the code, of a Hermitian matrix)
  • visual_graphene_H.m (For a given tight-binding Hamiltonian on the honeycomb lattice, function plots position of carbon atoms and draws blue lines to represent hoppings between them; red circles to represent on-site potential between them; and cyan lines to represent the periodic boundary conditions; it can be used to test if the tight-binding Hamiltonian of graphene is set correctly); This function calls another three function which should be placed in the same directory (or in the path): atomCoord.m, atomPosition.m, and constrainView.m
  • self_energy.m (Self-energy of the semi-infinite ideal metallic lead modeled on the square tight-binding lattice - the code shows how to convert analytical formulas of the lead surface Green function into a working program)
  • transmission.m (Transmission function for 1D tight-binding chain with spin-dependent terms)

Quantum transport simulations using KWANT package

Tutorials

Manuals

Band structure calculations for tight-binding models using PythTB package

Density functional theory with GPAW package

How to run GPAW on ulam

GPAW has been installed on ulam with the OS installed python 2.6.

  • in order to use the serial version of GPAW type:
 python your_gpaw_program.py
  • in order to use the parallel version of gpaw use the following syntax (replace 8 with the number of cores you want to use):
 mpirun -np 8 gpaw-python_openmpi your_gpaw_program.py

Getting started with GPAW

from ase import Atoms
from ase.io import write
from ase.optimize import QuasiNewton
from gpaw import GPAW

d = 1.10  # Starting guess for the bond length
atoms = Atoms('CO', positions=((0, 0, 0),
                               (0, 0, d)), pbc=False)
atoms.center(vacuum=4.0)
write('CO.cif', atoms)
calc = GPAW(h=0.20, xc='PBE', txt='CO_relax.txt')
atoms.set_calculator(calc)

relax = QuasiNewton(atoms, trajectory='CO.traj', logfile='qn.log')
relax.run(fmax=0.05)

GPAW Exercises Related to Midterm Project

References

First-principles quantum transport calculations using NEGF+DFT within GPAW package

Theory Background

  • Crash course on NEGF+DFT codes
  • NEGF+DFT within GPAW - see also J. Chen, K. S. Thygesen, and K. W. Jacobsen, Ab initio nonequilibrium quantum transport and forces with the real-space projector augmented wave method, Phys. Rev. B 85, 155140 (2012). [PDF]
  • M. Strange, I. S. Kristensen, K. S. Thygesen, and K. W. Jacobsen, Benchmark density functional theory calculations for nanoscale conductance, J. Chem. Phys. 128, 114714 (2008). [PDF]
  • D. A. Areshkin and B. K. Nikolić, Electron density and transport in top-gated graphene nanoribbon devices: First-principles Green function algorithms for systems containing a large number of atoms, Phys. Rev. B 81, 155450 (2010). [PDF]

GPAW Exercises