https://github.com/freude/NanoNet
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Tip revision: 736fe9f6800a0229c9bd5ae9712a5ba6b3e014c1 authored by Mykhailo Klymenko on 24 September 2023, 06:50:24 UTC
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Tip revision: 736fe9f
nanostrip.py
"""
This example script computes DOS and transmission function for the four-atom-width nanostrip
using the recursive Green's function algorithm.
"""
import numpy as np
import nanonet.tb as tb
from nanonet.negf.recursive_greens_functions import recursive_gf
from nanonet.negf.greens_functions import surface_greens_function


def main(energy):
    # define the basis set - one s-type orbital
    orb = tb.Orbitals('A')
    orb.add_orbital('s', energy=-1.0)

    # set TB parameters
    tb.set_tb_params(PARAMS_A_A={"ss_sigma": 1.0})

    # define atomic coordinates for the unit cell
    input_file = """4
                    Nanostrip
                    A1 0.0 0.0 0.0
                    A2 0.0 1.0 0.0
                    A3 0.0 2.0 0.0
                    A4 0.0 3.0 0.0
                 """

    # compute Hamiltonian matrices
    h = tb.Hamiltonian(xyz=input_file, nn_distance=1.4)
    h.initialize()
    period = [0, 0, 1.0]
    h.set_periodic_bc([period])
    h_l, h_0, h_r = h.get_hamiltonians()

    # compute DOS and transmission using Green's functions

    dos = np.zeros((energy.shape[0]))
    tr = np.zeros((energy.shape[0]))

    for j, E in enumerate(energy):
        # compute surface Green's functions
        L, R = surface_greens_function(E, h_l, h_0, h_r)
        # recursive Green's functions
        g_trans, grd, grl, gru, gr_left = recursive_gf(E, [h_l], [h_0 + L + R], [h_r])
        # compute DOS
        dos[j] = np.real(np.trace(1j * (grd[0] - grd[0].conj().T)))
        # compute left-lead coupling
        gamma_l = 1j * (L - L.conj().T)
        # compute right-lead coupling
        gamma_r = 1j * (R - R.conj().T)
        # compute transmission
        tr[j] = np.real(np.trace(gamma_l.dot(g_trans).dot(gamma_r).dot(g_trans.conj().T)))

        print("{} of {}: energy is {}".format(j + 1, energy.shape[0], E))

    tr = np.array(tr)
    dos = np.array(dos)

    return dos, tr


if __name__ == '__main__':

    import matplotlib.pyplot as plt

    energy = np.linspace(-5.0, 5.0, 150)
    dos, tr = main(energy)

    # plot DOS and transmission spectrum
    fig, ax = plt.subplots(1, 2)
    ax[0].plot(energy, dos, 'k')
    ax[0].set_ylabel(r'DOS (a.u)')
    ax[0].set_xlabel(r'Energy (eV)')

    ax[1].plot(energy, tr, 'k')
    ax[1].set_ylabel(r'Transmission (a.u.)')
    ax[1].set_xlabel(r'Energy (eV)')
    fig.tight_layout()
    plt.show()
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