def test_calculate_absorption_profile_rcwa():
import numpy as np
from solcore import material, si
from solcore.structure import Layer, Structure
from solcore.absorption_calculator.rigorous_coupled_wave import calculate_rat_rcwa, calculate_absorption_profile_rcwa
T = 300
Air = material("Air")(T=T)
TiO2 = material("TiO2", sopra=True)(T=T) # for the nanoparticles
GaAs = material("GaAs")(T=T)
th = 50
NP_layer = Layer(
si(th, "nm"),
Air,
geometry=[{
"type": "ellipse",
"mat": TiO2,
"center": (200, 200),
"halfwidths": [70, 100],
"angle": 30
}],
)
np_struct = Structure([NP_layer])
wl = np.linspace(300, 1000, 10)
rat_np = calculate_rat_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air)
A_output = rat_np['A_pol']
step_size = 2
dist = np.arange(0, th, step_size)
result = calculate_absorption_profile_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
rat_output_A=A_output,
steps_size=step_size)
parallel_result = calculate_absorption_profile_rcwa(np_struct,
size=((400, 0), (0,
400)),
orders=10,
wavelength=wl,
rat_output_A=A_output,
parallel=True,
steps_size=step_size)
assert sorted(list(result.keys())) == ["absorption", "position"]
assert sorted(list(parallel_result.keys())) == ["absorption", "position"]
assert len(result["position"]) == len(dist)
assert len(parallel_result["position"]) == len(dist)
assert result["absorption"] == approx(parallel_result["absorption"],
abs=1e-5)
def test_TMM_ellipsometry():
GaAs = material("GaAs")(T=300)
my_structure = Structure(
[Layer(si(3000, "nm"), material=GaAs), Layer(si(300, "um"), material=GaAs)]
)
wavelength = np.linspace(450, 1100, 300)
idx = np.argmin(abs(wavelength - 800))
angles = [60, 65, 70]
out = calculate_ellipsometry(my_structure, wavelength, angle=angles)
data = (
22.2849089096,
181.488417672,
16.4604621886,
182.277656469,
9.10132195668,
184.509752582,
)
for i in range(len(angles)):
assert data[2 * i] == approx(out["psi"][idx, i])
assert data[2 * i + 1] == approx(out["Delta"][idx, i])
def test_64_quantum_mechanics_schrodinger(self):
bulk = material("GaAs")(T=293)
barrier = material("GaAsP")(T=293, P=0.1)
bulk.strained = False
barrier.strained = True
top_layer = Layer(width=si("30nm"), material=bulk)
inter = Layer(width=si("3nm"), material=bulk)
barrier_layer = Layer(width=si("15nm"), material=barrier)
bottom_layer = top_layer
E = np.linspace(1.15, 1.5, 300) * q
alfas = np.zeros((len(E), 6))
alfas[:, 0] = E / q
alpha_params = {
"well_width": si("7.2nm"),
"theta": 0,
"eps": 12.9 * vacuum_permittivity,
"espace": E,
"hwhm": si("6meV"),
"dimensionality": 0.16,
"line_shape": "Gauss"
}
QW = material("InGaAs")(T=293, In=0.2)
QW.strained = True
well_layer = Layer(width=si("7.2nm"), material=QW)
my_structure = Structure(
[top_layer, barrier_layer, inter] +
1 * [well_layer, inter, barrier_layer, inter] + [bottom_layer],
substrate=bulk)
band_edge, bands = QM.schrodinger(my_structure,
quasiconfined=0,
num_eigenvalues=20,
alpha_params=alpha_params,
calculate_absorption=True)
for key in band_edge['E']:
for i in range(len(band_edge['E'][key])):
band_edge['E'][key][i] = solcore.asUnit(
band_edge['E'][key][i], 'eV') * 1000
band_edge['E'][key][i] = round(band_edge['E'][key][i])
Ehh = np.all(np.equal(band_edge['E']['Ehh'], my_energies['Ehh']))
Elh = np.all(np.equal(band_edge['E']['Elh'], my_energies['Elh']))
Ee = np.all(np.equal(band_edge['E']['Ee'], my_energies['Ee']))
idx = 100
out = [band_edge['alpha'][0][idx] / q, band_edge['alpha'][1][idx]]
# Test over the energies
self.assertTrue(Ehh and Elh and Ee)
# Test over the absorption coefficent at a given energy
for i, data in enumerate(out):
self.assertAlmostEqual(out[i], my_absorption[i])
def test_TMM_rat():
GaAs = material("GaAs")(T=300)
my_structure = Structure([Layer(si(3000, "nm"), material=GaAs)])
wavelength = np.linspace(450, 1100, 300)
idx = np.argmin(abs(wavelength - 800))
out = calculate_rat(
my_structure, wavelength, coherent=True, no_back_reflexion=False
)
out = (out["R"][idx], out["A"][idx], out["T"][idx])
data = (0.33328918841743332, 0.65996607786373396, 0.0067447337188326914)
assert all([d == approx(o) for d, o in zip(data, out)])
def test_TMM_absorption_profile():
GaAs = material("GaAs")(T=300)
my_structure = Structure([
Layer(si(3000, "nm"), material=GaAs),
Layer(si(300, "um"), material=GaAs)
])
out = calculate_absorption_profile(my_structure,
np.array([800]),
z_limit=3000,
steps_size=20)
data_path = Path(__file__).parent / "data" / "absorption_profile.txt"
data = tuple(np.loadtxt(data_path))
assert all([d == approx(o) for d, o in zip(data, out["absorption"][0])])
def test_44_TMM_ellipsometry(self):
GaAs = material('GaAs')(T=300)
my_structure = Structure([
Layer(si(3000, 'nm'), material=GaAs),
Layer(si(300, 'um'), material=GaAs),
])
wavelength = np.linspace(450, 1100, 300)
idx = np.argmin(abs(wavelength - 800))
angles = [60, 65, 70]
out = calculate_ellipsometry(my_structure, wavelength, angle=angles)
data = (22.2849089096, 181.488417672, 16.4604621886, 182.277656469,
9.10132195668, 184.509752582)
for i in range(len(angles)):
self.assertAlmostEqual(data[2 * i], out['psi'][idx, i])
self.assertAlmostEqual(data[2 * i + 1], out['Delta'][idx, i])
def test_42_TMM_rat(self):
GaAs = material('GaAs')(T=300)
my_structure = Structure([
Layer(si(3000, 'nm'), material=GaAs),
])
wavelength = np.linspace(450, 1100, 300)
idx = np.argmin(abs(wavelength - 800))
out = calculate_rat(my_structure,
wavelength,
coherent=True,
no_back_reflexion=False)
out = (out['R'][idx], out['A'][idx], out['T'][idx])
data = (0.33328918841743332, 0.65996607786373396,
0.0067447337188326914)
for i in range(3):
self.assertAlmostEqual(data[i], out[i])
def test_calculate_rat_rcwa():
import numpy as np
from solcore import material, si
from solcore.structure import Layer, Structure
from solcore.absorption_calculator.rigorous_coupled_wave import calculate_rat_rcwa
T = 300
Air = material("Air")(T=T)
TiO2 = material("TiO2", sopra=True)(T=T) # for the nanoparticles
GaAs = material("GaAs")(T=T)
NP_layer = Layer(
si("50nm"),
Air,
geometry=[{
"type": "circle",
"mat": TiO2,
"center": (200, 200),
"radius": 50
}],
)
np_struct = Structure([NP_layer])
wl = np.linspace(300, 1000, 150)
rat_np = calculate_rat_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air)
assert sorted(list(
rat_np.keys())) == ["A", "A_per_layer", "A_pol", "R", "T"]
for v in rat_np.values():
assert v.shape[0] == len(wl)
}
# We are going to calculate the absorption coefficient of InGaAs QWs of fixed thickness but different compositions
comp = [0.05, 0.1, 0.15, 0.2, 0.25]
colors = plt.cm.jet(np.linspace(0, 1, len(comp)))
plt.figure(figsize=(4, 4.5))
for j, i in enumerate(comp):
# We create the QW material at the given composition
QW = material("InGaAs")(T=293, In=i, strained=True)
# And the layer
well_layer = Layer(width=si("7.2nm"), material=QW)
# The following lines create the QW structure, with different number of QWs and interlayers
test_structure = Structure(
[barrier_layer, inter, well_layer, inter, barrier_layer])
test_structure.substrate = bulk
# Finally, the quantum properties are claculated here
output = QM.schrodinger(test_structure,
quasiconfined=0,
num_eigenvalues=20,
alpha_params=alpha_params,
calculate_absorption=True)
alfa = output[0]['alphaE'](E)
plt.plot(1240 / (E / q), alfa / 100, label='{}%'.format(int(i * 100)))
alfas[:, j + 1] = alfa / 100
plt.xlim(826, 1100)
import solcore.quantum_mechanics as QM
# First we create the materials we need
bulk = material("GaAs")(T=293, strained=False)
barrier = material("GaAsP")(T=293, P=0.1, strained=True)
# As well as some of the layers
top_layer = Layer(width=si("30nm"), material=barrier)
inter = Layer(width=si("3nm"), material=bulk)
barrier_layer = Layer(width=si("5nm"), material=barrier)
bottom_layer = top_layer
# We create the QW material at the given composition
QW = material("InGaAs")(T=293, In=0.15, strained=True)
# And the layer
well_layer = Layer(width=si("7.2nm"), material=QW)
# The following lines create the QW structure, with different number of QWs and interlayers. Indicating the substrate
# material with the keyword "substrate" is essential in order to calculate correctly the strain.
# A single QW with interlayers
test_structure_1 = Structure([top_layer, inter, well_layer, inter, bottom_layer], substrate=bulk)
output_1 = QM.schrodinger(test_structure_1, quasiconfined=0, graphtype='potentials', num_eigenvalues=20, show=True)
# 10 QWs without interlayers
test_structure_2 = Structure([top_layer, barrier_layer] + 10 * [well_layer, barrier_layer] + [bottom_layer],
substrate=bulk)
output_2 = QM.schrodinger(test_structure_2, quasiconfined=0.05, graphtype='potentialsLDOS', num_eigenvalues=200,
show=True)
def test_arbitrary_pol_rcwa():
import numpy as np
from solcore import material, si
from solcore.structure import Layer, Structure
from solcore.absorption_calculator.rigorous_coupled_wave import calculate_rat_rcwa, \
calculate_absorption_profile_rcwa
T = 300
Air = material("Air")(T=T)
TiO2 = material("TiO2", sopra=True)(T=T) # for the nanoparticles
GaAs = material("GaAs")(T=T)
th = 50
NP_layer = Layer(
si(th, "nm"),
Air,
geometry=[{
"type": "ellipse",
"mat": TiO2,
"center": (200, 200),
"halfwidths": [100, 70],
"angle": 40
}],
)
np_struct = Structure([NP_layer])
wl = np.linspace(300, 1000, 10)
step_size = 2
rat_np = calculate_rat_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air,
pol=[1, 0])
A_output = rat_np['A_pol']
result = calculate_absorption_profile_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
rat_output_A=A_output,
parallel=True,
steps_size=step_size,
pol=[1, 0])
rat_np_s = calculate_rat_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air,
pol='s')
A_output_s = rat_np_s['A_pol']
result_s = calculate_absorption_profile_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
rat_output_A=A_output_s,
parallel=True,
steps_size=step_size,
pol='s')
assert approx(A_output == A_output_s)
assert approx(result["absorption"] == result_s["absorption"])
return (energy, n_interp, k_interp)
# Load nk data using nk_convert function...
alinp_nk = nk_convert("AlInP_nk.csv", energy=E_eV)
gainp_nk = nk_convert("GaInP_nk.csv", energy=E_eV)
mgf_nk = nk_convert("MgF_nk.csv", energy=E_eV)
sic_nk = nk_convert("SiCx_nk.csv", energy=E_eV)
zns_nk = nk_convert("ZnS_nk.csv", energy=E_eV)
# Build the optical stack...
OptiStack = Structure([
[117, 1240/E_eV, mgf_nk[1], mgf_nk[2]],
[80, 1240/E_eV, sic_nk[1], sic_nk[2]],
[61, 1240/E_eV, zns_nk[1], zns_nk[2]],
[25, 1240/E_eV, alinp_nk[1], alinp_nk[2]],
[350000, 1240/E_eV, gainp_nk[1], gainp_nk[2]]
])
angles = np.linspace(0, 80, 10)
RAT_angles = []
print("Calculate RAT ::")
for theta in angles:
rat_data = []
print("Calculating at angle :: %4.1f deg" % theta)
# Calculate RAT data...
rat_data = calculate_rat(OptiStack, angle=theta, wavelength=1240 / E_eV)
def test_structure(b_mat, layer1, layer2, layer3):
structure1 = Structure([layer1, layer2], substrate=b_mat, T=t)
assert structure1.__len__() == 2
assert structure1.__dict__ == {
'substrate': b_mat,
'T': t,
'labels': [None, None]
}
assert structure1.width() == approx(width1 + width2)
assert structure1[0] == layer1
assert structure1[1] == layer2
structure2 = Structure([], substrate=b_mat, T=t)
structure2.append(layer1, layer_label='layer1')
assert structure2.__len__() == 1
assert structure2.__dict__ == {
'substrate': b_mat,
'T': t,
'labels': ['layer1']
}
assert structure2[0] == layer1
structure2.append_multiple([layer2, layer3],
layer_labels=['layer2', 'layer3'])
assert structure2.__len__() == 3
assert structure2.__dict__ == {
'substrate': b_mat,
'T': t,
'labels': ['layer1', 'layer2', 'layer3']
}
assert structure2[0] == layer1
assert structure2[1] == layer2
assert structure2[2] == layer3
assert structure2.width() == approx(width1 + width2 + width3)
assert structure2.relative_widths()['layer1'] == approx(width1 /
structure2.width())
assert structure2.relative_widths()['layer2'] == approx(width2 /
structure2.width())
assert structure2.relative_widths()['layer3'] == approx(width3 /
structure2.width())
structure3 = Structure([])
structure3.append(layer1, layer_label='layer1', repeats=2)
assert structure3.__len__() == 2
assert structure3.__dict__ == {'labels': ['layer1', 'layer1']}
assert structure3[0] == layer1
assert structure3[1] == layer1
assert structure3.width() == approx(width1 * 2)
# Below currently fails due to a bug when specifying labels and repeating more than once
# assert structure3.relative_widths()['layer1'] == width1 / structure3.width()
structure4 = Structure([])
structure4.append_multiple([layer1, layer2],
layer_labels=['layer1', 'layer2'],
repeats=2)
assert structure4.__len__() == 4
assert structure4.__dict__ == {
'labels': ['layer1', 'layer2', 'layer1', 'layer2']
}
assert structure4[0] == layer1
assert structure4[1] == layer2
assert structure4[2] == layer1
assert structure4[3] == layer2
assert structure4.width() == approx(width1 * 2 + width2 * 2)
Air = material("Air")(T=T)
TiO2 = material("TiO2", sopra=True)(T=T) # for the nanoparticles
GaAs = material("GaAs")(T=T)
# define a flat layer and another with circular discs with the same thickness
Flat = Layer(si('50nm'), TiO2)
NP_layer = Layer(si('50nm'),
Air,
geometry=[{
'type': 'circle',
'mat': TiO2,
'center': (200, 200),
'radius': 50
}])
flat_struct = Structure([Flat])
np_struct = Structure([NP_layer])
# And the wavelength in which the solve the problem
wl = np.linspace(300, 1000, 150)
rat_flat = calculate_rat_rcwa(flat_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air)
rat_np = calculate_rat_rcwa(np_struct,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
def test_TMM_absorption_profile():
GaAs = material("GaAs")(T=300)
my_structure = Structure(
[Layer(si(3000, "nm"), material=GaAs), Layer(si(300, "um"), material=GaAs)]
)
out = calculate_absorption_profile(
my_structure, np.array([800]), z_limit=3000, steps_size=20
)
data = (
0.00093920198054733134,
0.00091329190431268755,
0.00088809661793623094,
0.00086359640227330484,
0.00083977208217782804,
0.00081660501149482764,
0.0007940770584669893,
0.00077217059154379222,
0.00075086846558214263,
0.00073015400842769127,
0.00071001100786633451,
0.00069042369893569059,
0.00067137675158661923,
0.00065285525868512457,
0.00063484472434525627,
0.00061733105258387328,
0.00060030053628839001,
0.00058373984648887986,
0.00056763602192612503,
0.00055197645890746013,
0.00053674890144246557,
0.0005219414316507909,
0.00050754246043459913,
0.00049354071840833585,
0.00047992524707871981,
0.00046668539026805409,
0.0004538107857741483,
0.00044129135726031623,
0.00042911730636911071,
0.00041727910505361793,
0.00040576748812031177,
0.00039457344597762961,
0.00038368821758459675,
0.00037310328359397839,
0.00036281035968459497,
0.00035280139007758007,
0.00034306854123150837,
0.00033360419571145685,
0.00032440094622720458,
0.00031545158983589954,
0.00030674912230466134,
0.00029828673262870248,
0.00029005779770068137,
0.00028205587712711315,
0.00027427470818778237,
0.00026670820093421067,
0.00025935043342334711,
0.00025219564708274435,
0.00024523824220360293,
0.00023847277355814448,
0.00023189394613789383,
0.00022549661100952902,
0.0002192757612850577,
0.00021322652820316562,
0.00020734417731867015,
0.00020162410479709653,
0.00019606183381147725,
0.00019065301103855347,
0.0001853934032516379,
0.00018027889400747007,
0.00017530548042447405,
0.00017046927004989423,
0.00016576647781335848,
0.00016119342306448588,
0.00015674652669221659,
0.00015242230832361372,
0.00014821738359994165,
0.00014412846152789071,
0.00014015234190387394,
0.00013628591280938143,
0.00013252614817542982,
0.0001288701054142039,
0.00012531492311603331,
0.00012185781880990432,
0.00011849608678575335,
0.00011522709597683633,
0.00011204828790051968,
0.00010895717465587773,
0.00010595133697653208,
0.00010302842233720751,
0.00010018614311252307,
9.7422274786577231e-05,
9.4734654211925496e-05,
9.2121177916588886e-05,
8.9579800457766819e-05,
8.7108532820967001e-05,
8.470544086329888e-05,
8.2368643799712795e-05,
8.009631273099949e-05,
7.7886669212397987e-05,
7.573798386169243e-05,
7.3648575005706959e-05,
7.1616807364140996e-05,
6.9641090769713272e-05,
6.7719878923614451e-05,
6.5851668185292527e-05,
6.4034996395625842e-05,
6.2268441732560816e-05,
6.0550621598319883e-05,
5.8880191537308663e-05,
5.7255844183874585e-05,
5.5676308239094561e-05,
5.41403474757902e-05,
5.2646759770991723e-05,
5.1194376165094236e-05,
4.9782059946968693e-05,
4.8408705764312587e-05,
4.7073238758543685e-05,
4.5774613723559514e-05,
4.4511814287704784e-05,
4.3283852118305772e-05,
4.2089766148149713e-05,
4.0928621823303459e-05,
3.9799510371682887e-05,
3.8701548091800482e-05,
3.7633875661134488e-05,
3.6595657463578247e-05,
3.5586080935443529e-05,
3.4604355929505788e-05,
3.3649714096593824e-05,
3.2721408284239568e-05,
3.1818711951917646e-05,
3.0940918602416916e-05,
3.0087341228898868e-05,
2.9257311777210295e-05,
2.8450180623029266e-05,
2.7665316063435288e-05,
2.6902103822505617e-05,
2.6159946570550893e-05,
2.5438263456613905e-05,
2.4736489653865175e-05,
2.4054075917540213e-05,
2.3390488155071715e-05,
2.2745207008081107e-05,
2.211772744590139e-05,
2.1507558370314028e-05,
2.0914222231189692e-05,
2.0337254652732693e-05,
1.9776204070036316e-05,
1.9230631375664536e-05,
1.8700109575983667e-05,
1.8184223456974879e-05,
1.7682569259266036e-05,
1.7194754362128619e-05,
1.6720396976192213e-05,
1.6259125844636267e-05,
1.5810579952625165e-05,
1.5374408244759177e-05,
1.4950269350320186e-05,
1.4537831316097222e-05,
)
assert all([d == approx(o) for d, o in zip(data, out["absorption"][0])])
def test_rcwa_polygon():
import numpy as np
from solcore import material, si
from solcore.structure import Layer, Structure
from solcore.absorption_calculator.rigorous_coupled_wave import calculate_rat_rcwa, \
calculate_absorption_profile_rcwa
T = 300
Air = material("Air")(T=T)
TiO2 = material("TiO2", sopra=True)(T=T) # for the nanoparticles
GaAs = material("GaAs")(T=T)
th = 50
NP_layer_square = Layer(
si(th, "nm"),
Air,
geometry=[{
"type": "rectangle",
"mat": TiO2,
"center": (200, 200),
"halfwidths": [50, 50],
"angle": 0
}],
)
np_struct_square = Structure([NP_layer_square])
NP_layer_polygon = Layer(
si(th, "nm"),
Air,
geometry=[{
"type": "polygon",
"mat": TiO2,
"center": (200, 200),
"vertices": ((150, 150), (250, 150), (250, 250), (150, 250)),
"angle": 0
}],
)
np_struct_polygon = Structure([NP_layer_polygon])
wl = np.linspace(300, 1000, 10)
step_size = 2
rat_np_sq = calculate_rat_rcwa(np_struct_square,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air,
pol=[1, 0])
A_output_sq = rat_np_sq['A_pol']
result_square = calculate_absorption_profile_rcwa(np_struct_square,
size=((400, 0), (0,
400)),
orders=10,
wavelength=wl,
rat_output_A=A_output_sq,
parallel=True,
steps_size=step_size,
pol=[1, 0])
rat_np_pol = calculate_rat_rcwa(np_struct_polygon,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
substrate=GaAs,
incidence=Air,
pol=[1, 0])
A_output_pol = rat_np_pol['A_pol']
result_polygon = calculate_absorption_profile_rcwa(
np_struct_polygon,
size=((400, 0), (0, 400)),
orders=10,
wavelength=wl,
rat_output_A=A_output_pol,
parallel=True,
steps_size=step_size,
pol=[1, 0])
assert approx(A_output_sq == A_output_pol)
assert approx(result_polygon["absorption"] == result_square["absorption"])
import matplotlib.pyplot as plt
import numpy as np
from solcore.absorption_calculator import calculate_ellipsometry
from solcore import material, si
from solcore.structure import Structure, Layer
# First we defined a couple of materials, for example, GaAs and AlGAs
GaAs = material('GaAs')(T=300)
AlGaAs = material('AlGaAs')(T=300, Al=0.3)
# Now, let's build the structure. We don't add a substrate and assume that there is an infinitely thick absorbing
# material in the back.
my_structure = Structure([
Layer(si(40, 'nm'), material=AlGaAs),
Layer(si(3000, 'nm'), material=GaAs),
])
# We want to calculate the ellipsometry of this structure as a function of the wavelength for a few angles
wavelength = np.linspace(400, 1000, 200)
angles = [65, 70, 75]
out = calculate_ellipsometry(my_structure, wavelength, angle=angles)
# This results must be taken with care. As the ellipsometry routine can only deal with coherent light, there might be
# strange oscillations related with intereference in thick layers, something that should not happen.
# Setting no_back_reflection=True (the default) should take care of most of this effects, but might add other unexpected
# ones.
fig, ax1 = plt.subplots(1, 1)
ax2 = ax1.twinx()
ax1.plot(wavelength, out['psi'][:, 0], 'b', label=r'$\Psi$')
n_spline = InterpolatedUnivariateSpline(x=Ge_nk_Exp[::5, 0],
y=Ge_nk_Exp[::5, 1],
k=3)(E_eV)
k_spline = InterpolatedUnivariateSpline(x=Ge_nk_Exp[::5, 2],
y=Ge_nk_Exp[::5, 3],
k=3)(E_eV)
## Step 1 :: n and k modelling...
# First model the Ge02 layer with the Sellmeier model
# Define Oscillator Structure
GeO2 = Structure([
Oscillator(oscillator_type="Sellmeier",
material_parameters=None,
A1=0.80686642,
L1=0.68972606E-1,
A2=0.71815848,
L2=0.15396605,
A3=0.85416831,
L3=0.11841931E2)
])
GeO2_nk = cppb().nk_calc(oscillator_structure=GeO2, energy_array=E_eV)
# Step 2 :: use this modelled n and k to calculate the ellipsometry data...
# Define a structure for the optical stack...
stack = Structure([
[4.4, 1240 / E_eV, GeO2_nk["n"],
GeO2_nk["k"]], # Layer 1 :: GeO2 native oxide layer
[350000, 1240 / E_eV, n_spline, k_spline] # Layer 2/ Substrate :: Bulk Ge
])
def test_quantum_mechanics_schrodinger():
""" Testing schrodinger equation solver
"""
bulk = material("GaAs")(T=293)
barrier = material("GaAsP")(T=293, P=0.1)
bulk.strained = False
barrier.strained = True
top_layer = Layer(width=si("30nm"), material=bulk)
inter = Layer(width=si("3nm"), material=bulk)
barrier_layer = Layer(width=si("15nm"), material=barrier)
bottom_layer = top_layer
E = np.linspace(1.15, 1.5, 300) * q
alfas = np.zeros((len(E), 6))
alfas[:, 0] = E / q
alpha_params = {
"well_width": si("7.2nm"),
"theta": 0,
"eps": 12.9 * vacuum_permittivity,
"espace": E,
"hwhm": si("6meV"),
"dimensionality": 0.16,
"line_shape": "Gauss",
}
QW = material("InGaAs")(T=293, In=0.2)
QW.strained = True
well_layer = Layer(width=si("7.2nm"), material=QW)
my_structure = Structure(
[
top_layer,
barrier_layer,
inter,
well_layer,
inter,
barrier_layer,
inter,
bottom_layer,
],
substrate=bulk,
)
band_edge, bands = QM.schrodinger(
my_structure,
quasiconfined=0,
num_eigenvalues=20,
alpha_params=alpha_params,
calculate_absorption=True,
)
for key in band_edge["E"]:
for i in range(len(band_edge["E"][key])):
band_edge["E"][key][i] = solcore.asUnit(band_edge["E"][key][i],
"eV") * 1000
band_edge["E"][key][i] = round(band_edge["E"][key][i])
Ehh = np.all(np.equal(band_edge["E"]["Ehh"], my_energies["Ehh"]))
Elh = np.all(np.equal(band_edge["E"]["Elh"], my_energies["Elh"]))
Ee = np.all(np.equal(band_edge["E"]["Ee"], my_energies["Ee"]))
idx = 100
out = [band_edge["alpha"][0][idx] / q, band_edge["alpha"][1][idx]]
# Test over the energies
assert Ehh and Elh and Ee
# Test over the absorption coefficent at a given energy
for i, data in enumerate(out):
assert out[i] == approx(my_absorption[i], rel=1e-4)
output['absorption'] = 0.5 * (data_s + data_p)
return output
if __name__ == '__main__':
import matplotlib.pyplot as plt
from solcore import material, si
from solcore.structure import Layer, Structure
GaAs = material('GaAs')(T=300)
InGaAs = material('InGaAs')(T=300, In=0.1)
my_structure = Structure([
Layer(si(3000, 'nm'), material=InGaAs),
Layer(si(30, 'um'), material=GaAs),
])
wavelength = np.linspace(450, 1100, 300)
out = calculate_rat(my_structure,
wavelength,
coherent=True,
no_back_reflection=False)
# #
# plt.plot(wavelength, out['R'], 'b', label='Reflexion')
# plt.plot(wavelength, out['A'], 'r', label='Absorption')
# plt.plot(wavelength, out['T'], 'g', label='Transmission')
# plt.legend()
# plt.show()
MatParams["B1s"] = 1.0
MatParams["Gamma_Eg_ID"] = 0.3
MatParams["Alpha_Eg_ID"] = 0.0
MatParams["E1"] = 2.8
MatParams["E1_d1"] = 2.9
MatParams["Gamma_E1"] = 0.1
MatParams["E2"] = 4.72
MatParams["C"] = 3.0
MatParams["Alpha_E2"] = 0.04
MatParams["Gamma_E2"] = 0.19
# Must define a structure object containing the required oscillator functions. The oscillator type and material
# parameters are both passed to individual 'Oscillators' in the structure...
Adachi_GaAs = Structure([
Oscillator(oscillator_type="E0andE0_d0", material_parameters=MatParams),
Oscillator(oscillator_type="E1andE1_d1", material_parameters=MatParams),
Oscillator(oscillator_type="E_ID", material_parameters=MatParams),
Oscillator(oscillator_type="E2", material_parameters=MatParams)
])
Output = CPPB_Model.eps_calc(Adachi_GaAs, E)
# PLOT OUTPUT...
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(7, 4.5))
# Subplot I :: Real part of the dielectric function.
ax1.set_yscale("linear")
ax1.set_xlim(0, 5.3)
ax1.set_ylim(-14, 27)
ax1.plot(Palik_Eps1[:, 0], Palik_Eps1[:, 1], label="Exp. Data (Palik)",
marker='o', ls='none', markerfacecolor='none', markeredgecolor=colours("Red"))
"dimensionality": 0.16,
"line_shape": "Gauss"
}
# We create the QW material at the given composition
QW = material("InGaAs")(T=293, In=0.15)
QW.strained = True
# And the layer
well_layer = Layer(width=si("7.2nm"), material=QW)
# The following lines create the QW structure, with different number of QWs and interlayers
# test_structure = Structure([top_layer, barrier_layer, inter] + 10 * [well_layer, inter, barrier_layer, inter] +
# [bottom_layer])
# test_structure = Structure([barrier_layer, inter] + 1 * [well_layer, inter] +
# [barrier_layer])
test_structure = Structure([top_layer, barrier_layer] +
10 * [well_layer, barrier_layer] + [bottom_layer])
test_structure.substrate = bulk
# Finally, the quantum properties are claculated here
output = QM.schrodinger(test_structure,
quasiconfined=0,
graphtype='potentials',
num_eigenvalues=50,
alpha_params=alpha_params,
calculate_absorption=True)
"line_shape": "Gauss"
}
comp = [0.05, 0.1, 0.15, 0.2, 0.25]
colors = plt.cm.jet(np.linspace(0, 1, len(comp)))
plt.figure(figsize=(6, 4.5))
for j, i in enumerate(comp):
QW = material("InGaAs")(T=293, In=i)
QW.strained = True
well_layer = Layer(width=si("7.2nm"), material=QW)
# test_structure = Structure([top_layer, barrier_layer, inter] + 1 * [well_layer, inter, barrier_layer, inter] +
# [bottom_layer])
test_structure = Structure([barrier_layer, inter] +
1 * [well_layer, inter] + [barrier_layer])
# test_structure = Structure([top_layer, barrier_layer] + 10 * [well_layer, barrier_layer] +
# [bottom_layer])
test_structure.substrate = bulk
output = schrodinger(test_structure,
quasiconfined=0,
num_eigenvalues=20,
alpha_params=alpha_params,
calculate_absorption=True)
alfa = output[0]['alphaE'](E)
plt.plot(1240 / (E / q), alfa / 100, label='{}%'.format(int(i * 100)))
alfas[:, j + 1] = alfa / 100
fill_value=(k[0], k[-1]))(energy)
return (energy, n_interp, k_interp)
# Load nk data using nk_convert function...
alinp_nk = nk_convert("data/AlInP_nk.csv", energy=E_eV)
gainp_nk = nk_convert("data/GaInP_nk.csv", energy=E_eV)
mgf_nk = nk_convert("data/MgF_nk.csv", energy=E_eV)
sic_nk = nk_convert("data/SiCx_nk.csv", energy=E_eV)
zns_nk = nk_convert("data/ZnS_nk.csv", energy=E_eV)
# Build the optical stack...
stack = Structure([[117, 1240 / E_eV, mgf_nk[1], mgf_nk[2]],
[80, 1240 / E_eV, sic_nk[1], sic_nk[2]],
[61, 1240 / E_eV, zns_nk[1], zns_nk[2]],
[25, 1240 / E_eV, alinp_nk[1], alinp_nk[2]],
[350000, 1240 / E_eV, gainp_nk[1], gainp_nk[2]]])
angles = np.linspace(0, 80, 10)
RAT_angles = []
print("Calculate RAT ::")
for theta in angles:
print("Calculating at angle :: %4.1f deg" % theta)
# Calculate RAT data...
rat_data = calculate_rat(stack, angle=theta, wavelength=1240 / E_eV)
RAT_angles.append((theta, rat_data["R"], rat_data["A"]))
colors = plt.cm.jet(np.linspace(1, 0, len(RAT_angles)))
"hwhm": si("6meV"),
"dimensionality": 0.16,
"line_shape": "Gauss"
}
# plt.figure(figsize=(4, 4.5))
for j, i in enumerate(comp):
# We create the QW material at the given composition
QW = material("InGaAs")(T=293, In=i, strained=True)
# And the layer
well_layer = Layer(width=si("7.2nm"), material=QW)
# The following lines create the QW structure, with different number of QWs and interlayers
test_structure = Structure(
[barrier_layer, inter, well_layer, inter, barrier_layer],
substrate=bulk)
# Finally, the quantum properties are claculated here
output = QM.schrodinger(test_structure,
quasiconfined=0,
num_eigenvalues=20,
alpha_params=alpha_params,
calculate_absorption=True)
alfa = output[0]['alphaE'](E)
plt.plot(1240 / (E / q), alfa / 100, label='{}%'.format(int(i * 100)))
plt.xlim(826, 1100)
plt.ylim(0, 23000)
plt.xlabel('Wavelength (nm)')