Functional Perovskites

We investigate the band gaps and optical spectra of functional perovskites composed of layers of the two cubic perovskite semiconductors BaSnO3-BaTaO2N and LaAlO3-LaTiO2N.

Ivano E. Castelli, Mohnish Pandey, Kristian S. Thygesen, and Karsten W. Jacobsen

Bandgap Engineering of Functional Perovskites Through Quantum Confinement and Tunneling

Phys. Rev. B 91, 165309.

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Key-value pairs

key	description	unit
gllbsc_dir_gap	Direct bandgap GLLB-SC	eV
gllbsc_ind_gap	Indirect bandgap GLLB-SC	eV
gllbsc_disc	Derivative discontinuity GLLB-SC	eV
gllbsc_gamma	Bandgap at Gamma GLLB-SC	eV
comb_A	Cubic perovskite labeled as A-combination
comb_B	Cubic perovskite labeled as B-combination
sequence	Sequence of A and B layers
gllbsc_gamma_gap	GLLBSC Gamma-gap

Band gaps

Here, we plot the band gaps at $\mathrm{\Gamma }$ when n A-layers is stuck with n B-layers (with n between 1 and 6). The changes in the gaps can be understood in terms of quantum confinement and tunneling. The cubic perovskites selected as building blocks are BaSnO3 (A) with BaTaO2N (B) or LaAlO3 (A) with LaTiO2N (B).

# creates: gaps.svg
import numpy as np
import matplotlib.pylab as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.cm as cm
import ase.db

con = ase.db.connect('funct_perovskites.db')

comb_A = 'BaSnO3'
comb_B = 'BaTaO2N'

gaps = []

for nA in range(1, 7):
    for nB in range(1, 7):
        name = nA * 'A' + nB * 'B'
        row = con.get(comb_A=comb_A, comb_B=comb_B, sequence=name)
        gaps.append(row.gllbsc_gamma_gap)

colors = []
for gap in gaps:
    c = cm.jet(int(gap / max(gaps) * 255))
    colors.append([c[0], c[1], c[2]])

x, y = np.meshgrid(range(1, 7), range(1, 7))
x = x.flat
y = y.flat
z = np.zeros_like(x)
dx = dy = 0.5 * np.ones_like(x)
dz = gaps
fig = plt.figure()
ax = Axes3D(fig, auto_add_to_figure=False)
fig.add_axes(ax)
plt.xlabel('nB, B = ' + comb_B)
plt.ylabel('nA, A = ' + comb_A)
ax.set_zlabel('Bandgap [eV]')
ax.bar3d(x, y, z, dx, dy, dz, color=colors)
plt.savefig('gaps.svg')