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_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_process_junction_pn():
from solcore.analytic_solar_cells.depletion_approximation import identify_layers, identify_parameters
from solcore import material
from solcore.structure import Layer, Junction
from solcore.state import State
Na = np.power(10, np.random.uniform(22, 25))
Nd = np.power(10, np.random.uniform(23, 26))
options = State()
options.T = np.random.uniform(250, 350)
Lp = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
Ln = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
GaAs_n = material("GaAs")(Nd=Nd, hole_diffusion_length=Ln)
GaAs_p = material("GaAs")(Na=Na, electron_diffusion_length=Lp)
p_width = np.random.uniform(500, 1000)*1e-9
n_width = np.random.uniform(3000, 5000)*1e-9
test_junc = Junction([Layer(p_width, GaAs_p, role="emitter"), Layer(n_width, GaAs_n, role="base")])
id_top, id_bottom, pRegion, nRegion, iRegion, pn_or_np = identify_layers(test_junc)
xn, xp, xi, sn, sp, ln, lp, dn, dp, Nd_c, Na_c, ni, es = identify_parameters(test_junc, options.T, pRegion, nRegion, iRegion)
ni_expect = GaAs_n.ni
assert [id_top, id_bottom] == approx([0, 1])
assert pn_or_np == 'pn'
assert [xn, xp, xi, sn, sp, ln, lp, dn, dp, Nd_c, Na_c, ni, es] == approx([n_width, p_width, 0, 0, 0, Lp, Ln, GaAs_n.hole_mobility * kb * options.T / q,
GaAs_p.electron_mobility * kb * options.T / q, Nd, Na, ni_expect, GaAs_n.permittivity])
def test_process_junction_set_in_junction():
from solcore.analytic_solar_cells.depletion_approximation import identify_layers, identify_parameters
from solcore import material
from solcore.structure import Layer, Junction
from solcore.state import State
options = State()
options.T = np.random.uniform(250, 350)
Lp = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
Ln = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
sn = np.power(10, np.random.uniform(0, 3))
sp = np.power(10, np.random.uniform(0, 3))
se = np.random.uniform(1, 20) * vacuum_permittivity
GaAs_n = material("GaAs")()
GaAs_p = material("GaAs")()
GaAs_i = material("GaAs")()
p_width = np.random.uniform(500, 1000)
n_width = np.random.uniform(3000, 5000)
i_width = np.random.uniform(100, 300) * 1e-9
mun = np.power(10, np.random.uniform(-5, 0))
mup = np.power(10, np.random.uniform(-5, 0))
Vbi = np.random.uniform(0, 3)
test_junc = Junction([
Layer(p_width, GaAs_p, role="emitter"),
Layer(i_width, GaAs_i, role="intrinsic"),
Layer(n_width, GaAs_n, role="base")
],
sn=sn,
sp=sp,
permittivity=se,
ln=Ln,
lp=Lp,
mup=mup,
mun=mun,
Vbi=Vbi)
id_top, id_bottom, pRegion, nRegion, iRegion, pn_or_np = identify_layers(
test_junc)
xn, xp, xi, sn_c, sp_c, ln, lp, dn, dp, Nd_c, Na_c, ni, es = identify_parameters(
test_junc, options.T, pRegion, nRegion, iRegion)
ni_expect = GaAs_n.ni
assert [id_top, id_bottom] == approx([0, 2])
assert pn_or_np == 'pn'
assert [xn, xp, xi, sn_c, sp_c, ln, lp, dn, dp, Nd_c, Na_c, ni,
es] == approx([
n_width, p_width, i_width, sn, sp, Ln, Lp,
mun * kb * options.T / q, mup * kb * options.T / q, 1, 1,
ni_expect, se
])
def test_tmm_rcwa_structure_comparison(pol, angle):
import numpy as np
from solcore import si, material
from solcore.structure import Layer
from solcore.solar_cell import SolarCell
from solcore.optics.tmm import calculate_rat, OptiStack
from solcore.optics.rcwa import calculate_rat_rcwa
InGaP = material('GaInP')(In=0.5)
GaAs = material('GaAs')()
Ge = material('Ge')()
Ag = material('Ag')()
Air = material('Air')()
Al2O3 = material('Al2O3')()
wavelengths = np.linspace(250, 1900, 500)
size = ((100, 0), (0, 100))
ARC = [Layer(si('80nm'), Al2O3)]
solar_cell = SolarCell(ARC + [
Layer(material=InGaP, width=si('400nm')),
Layer(material=GaAs, width=si('4000nm')),
Layer(material=Ge, width=si('3000nm'))
],
substrate=Ag)
solar_cell_OS = OptiStack(solar_cell,
no_back_reflection=False,
substrate=solar_cell.substrate)
rcwa_result = calculate_rat_rcwa(solar_cell,
size,
2,
wavelengths,
Air,
Ag,
theta=angle,
phi=angle,
pol=pol,
parallel=True)
tmm_result = calculate_rat(solar_cell_OS,
wavelengths,
angle,
pol,
no_back_reflection=False)
assert tmm_result['A_per_layer'][1:-1] == approx(
rcwa_result['A_per_layer'].T)
assert tmm_result['R'] == approx(rcwa_result['R'])
assert tmm_result['T'] == approx(rcwa_result['T'])
assert np.sum(tmm_result['A_per_layer'][1:-1].T,
1) + tmm_result['R'] + tmm_result['T'] == approx(1)
assert np.sum(rcwa_result['A_per_layer'],
1) + rcwa_result['R'] + rcwa_result['T'] == approx(1)
def junction(nd_top, na_top, nd_bottom, na_bottom):
from solcore.structure import Junction, Layer
from solcore import si, material
from solcore.solar_cell import SolarCell
from solcore.constants import vacuum_permittivity
from solcore.solar_cell_solver import prepare_solar_cell
from solcore.optics import solve_beer_lambert
Lp = np.power(10, np.random.uniform(-8, -6))
Ln = np.power(10, np.random.uniform(-8, -6))
AlInP = material("AlInP")
InGaP = material("GaInP")
window_material = AlInP(Al=0.52)
top_cell_n_material = InGaP(
In=0.48,
Nd=nd_top,
Na=na_top,
hole_diffusion_length=Lp,
electron_diffusion_length=Ln,
)
top_cell_p_material = InGaP(
In=0.48,
Nd=nd_bottom,
Na=na_bottom,
hole_diffusion_length=Lp,
electron_diffusion_length=Ln,
)
rel_perm = np.random.uniform(1, 20)
for mat in [top_cell_n_material, top_cell_p_material]:
mat.permittivity = rel_perm * vacuum_permittivity
n_width = np.random.uniform(500, 1000) * 1e-9
p_width = np.random.uniform(3000, 5000) * 1e-9
test_junc = SolarCell([
Junction(
[
Layer(si("25nm"), material=window_material, role="window"),
Layer(n_width, material=top_cell_n_material, role="emitter"),
Layer(p_width, material=top_cell_p_material, role="base"),
],
sn=1,
sp=1,
kind="DA",
)
])
options = da_options()
options.light_source = da_light_source()
prepare_solar_cell(test_junc, options)
solve_beer_lambert(test_junc, options)
return test_junc, options
def test_BL_correction():
wl = np.linspace(800, 950, 4) * 1e-9
GaAs = material("GaAs")()
thick_cell = SolarCell([Layer(material=GaAs, width=si("20um"))])
opts = State()
opts.position = None
prepare_solar_cell(thick_cell, opts)
position = np.arange(0, thick_cell.width, 1e-9)
opts.position = position
opts.recalculate_absorption = True
opts.no_back_reflexion = False
opts.BL_correction = False
opts.wavelength = wl
solve_tmm(thick_cell, opts)
no_corr = thick_cell.absorbed
opts.BL_correction = True
solve_tmm(thick_cell, opts)
with_corr = thick_cell.absorbed
assert with_corr == approx(
np.array([6.71457872e-01, 6.75496354e-01, 2.09738887e-01, 0]))
assert no_corr == approx(
np.array([6.71457872e-01, 6.75496071e-01, 2.82306407e-01, 0]))
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_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 evaluate(self, x):
GaAs = material('GaAs_WVASE')()
Air = material('Air')()
InAlP = material('InAlP_WVASE')()
InGaP = material('InGaP_WVASE')()
Ag = material('Ag_Jiang')()
# MgF2 = material('MgF2')()
# Ta2O5 = material('410', nk_db=True)()
SiN = material('SiN_SE')()
# print('SiN thickness', x[2]*x[1], 'Ag th', (1-x[1])*x[2])
grating1 = [Layer(si(x[2] * x[1], 'nm'), SiN)]
grating2 = [
Layer(si((1 - x[1]) * x[2], 'nm'),
SiN,
geometry=[{
'type': 'circle',
'mat': Ag,
'center': (0, 0),
'radius': x[3],
'angle': 0
}])
]
solar_cell = SolarCell([
Layer(material=InGaP, width=si('19nm')),
Layer(material=GaAs, width=si(x[0], 'nm')),
Layer(material=InAlP, width=si('18nm'))
] + grating1 + grating2,
substrate=Ag)
S4_setup = rcwa_structure(solar_cell, self.size, self.orders,
self.options, Air, Ag)
RAT = S4_setup.calculate()
EQE_sim = 0.9 * 100 * (RAT['A_layer'][:, 0] + RAT['A_layer'][:, 1])
# least squares?
residual = np.sum((EQE_sim - self.EQE_meas)**2)
return residual
def test_substrate_presence_profile():
wavelength = np.linspace(300, 800, 3) * 1e-9
GaAs = material("GaAs")(T=300)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)],
substrate=GaAs)
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflection": False,
},
)
z_pos = np.linspace(0, my_structure.width, 10)
profile_subs = my_structure[0].absorbed(z_pos)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)])
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflection": False,
},
)
profile_nosubs = my_structure[0].absorbed(z_pos)
profile = np.vstack((profile_subs, profile_nosubs))
data_path = Path(
__file__).parent / "data" / "substrate_presence_profile.csv"
expected = np.loadtxt(data_path, delimiter=",")
assert profile.shape == expected.shape
assert profile == approx(expected)
def default_GaAs(T):
# We create the other materials we need for the device
window = material('AlGaAs')(T=T, Na=5e24, Al=0.8)
p_GaAs = material('GaAs')(T=T, Na=1e24)
n_GaAs = material('GaAs')(T=T, Nd=8e22)
bsf = material('GaAs')(T=T, Nd=2e24)
output = Junction([
Layer(width=si('30nm'), material=window, role="Window"),
Layer(width=si('150nm'), material=p_GaAs, role="Emitter"),
Layer(width=si('3000nm'), material=n_GaAs, role="Base"),
Layer(width=si('200nm'), material=bsf, role="BSF")
],
sn=1e6,
sp=1e6,
T=T,
kind='PDD')
return output
def test_substrate_presence_A():
wavelength = np.linspace(300, 800, 3) * 1e-9
GaAs = material("GaAs")(T=300)
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)],
substrate=GaAs)
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflexion": False,
},
)
z_pos = np.linspace(0, my_structure.width, 10)
A_subs = my_structure[0].layer_absorption
my_structure = SolarCell([Layer(si(700, "nm"), material=GaAs)])
solar_cell_solver(
my_structure,
"optics",
user_options={
"wavelength": wavelength,
"optics_method": "TMM",
"no_back_reflexion": False,
},
)
A_nosubs = my_structure[0].layer_absorption
A = np.vstack((A_subs, A_nosubs))
A_data = np.array([[0.56610281, 0.62692985, 0.41923175],
[0.56610281, 0.62711355, 0.37837737]])
assert all([d == approx(o) for d, o in zip(A, A_data)])
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_inc_coh_tmm():
GaInP = material("GaInP")(In=0.5)
GaAs = material("GaAs")()
Ge = material("Ge")()
optical_struct = SolarCell([
Layer(material=GaInP, width=si("5000nm")),
Layer(material=GaAs, width=si("200nm")),
Layer(material=GaAs, width=si("5um")),
Layer(material=Ge, width=si("50um")),
])
wl = np.linspace(400, 1200, 5) * 1e-9
options = State()
options.wavelength = wl
options.optics_method = "TMM"
options.no_back_reflection = False
options.BL_correction = True
options.recalculate_absorption = True
c_list = [
["c", "c", "c", "c"],
["c", "c", "c", "i"],
["c", "i", "i", "c"],
["i", "i", "i", "i"],
]
results = []
for i1, cl in enumerate(c_list):
options.coherency_list = cl
solar_cell_solver(optical_struct, "optics", options)
results.append(optical_struct.absorbed)
A_calc = np.stack(results)
A_data = np.array(
[[0.5742503, 0.67956899, 0.73481184, 0.725372, 0.76792856],
[0.5742503, 0.67956899, 0.73481184, 0.725372, 0.76792856],
[0.5742503, 0.67956899, 0.73474943, 0.70493469, 0.70361194],
[0.5742503, 0.67956899, 0.70927724, 0.71509221, 0.71592772]])
assert A_calc == approx(A_data)
def AlGaAs(T):
# We create the other materials we need for the device
window = material("AlGaAs")(T=T, Na=5e24, Al=0.8)
p_AlGaAs = material("AlGaAs")(T=T, Na=1e24, Al=0.4)
n_AlGaAs = material("AlGaAs")(T=T, Nd=8e22, Al=0.4)
bsf = material("AlGaAs")(T=T, Nd=2e24, Al=0.6)
output = Junction(
[
Layer(width=si("30nm"), material=window, role="Window"),
Layer(width=si("150nm"), material=p_AlGaAs, role="Emitter"),
Layer(width=si("1000nm"), material=n_AlGaAs, role="Base"),
Layer(width=si("200nm"), material=bsf, role="BSF"),
],
sn=1e6,
sp=1e6,
T=T,
kind="PDD",
)
return output
def plot_R(obj, x, icol):
cols = sns.cubehelix_palette(len(use_orders),
start=.5,
rot=-.9,
reverse=True)
GaAs = material('GaAs_WVASE')()
Air = material('Air')()
InAlP = material('InAlP_WVASE')()
InGaP = material('InGaP_WVASE')()
Ag = material('Ag_Jiang')()
# MgF2 = material('MgF2')()
# Ta2O5 = material('410', nk_db=True)()
SiN = material('SiN_SE')()
R_data = np.loadtxt('Talbot_precursor_R.csv', delimiter=',')
grating1 = [Layer(si(x[2] * x[1], 'nm'), SiN)]
grating2 = [
Layer(si((1 - x[1]) * x[2], 'nm'),
SiN,
geometry=[{
'type': 'circle',
'mat': Ag,
'center': (0, 0),
'radius': x[3],
'angle': 0
}])
]
solar_cell = SolarCell([
Layer(material=GaAs, width=si('25nm')),
Layer(material=InGaP, width=si('19nm')),
Layer(material=GaAs, width=si(x[0], 'nm')),
Layer(material=InAlP, width=si('18nm'))
] + grating1 + grating2,
substrate=Ag)
S4_setup = rcwa_structure(solar_cell, obj.size, obj.orders, obj.options,
Air, Ag)
RAT = S4_setup.calculate()
total_A = np.sum(RAT['A_layer'], axis=1)
# plt.figure()
plt.plot(S4_setup.wavelengths * 1e9,
RAT['R'],
label=str(obj.orders),
color=cols[icol])
return S4_setup.wavelengths * 1e9, interp1d(R_data[:, 0], R_data[:, 1])(
S4_setup.wavelengths * 1e9)
def AlGaAs():
from solcore import material
from solcore.structure import Layer, Junction
from solcore import si
T = 298
# We create the other materials we need for the device
window = material("AlGaAs")(T=T, Na=5e24, Al=0.8)
p_AlGaAs = material("AlGaAs")(T=T, Na=1e24, Al=0.4)
n_AlGaAs = material("AlGaAs")(T=T, Nd=8e22, Al=0.4)
bsf = material("AlGaAs")(T=T, Nd=2e24, Al=0.6)
return Junction(
[
Layer(width=si("30nm"), material=window, role="Window"),
Layer(width=si("150nm"), material=p_AlGaAs, role="Emitter"),
Layer(width=si("1000nm"), material=n_AlGaAs, role="Base"),
Layer(width=si("200nm"), material=bsf, role="BSF"),
],
sn=1e6,
sp=1e6,
T=T,
kind="PDD",
)
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 prepare_test_cell():
from solcore import material, si
from solcore.structure import Junction, Layer, TunnelJunction
from solcore.solar_cell import SolarCell
GaAs = material("GaAs")()
MgF2 = material("MgF2")()
TiO2 = material("TiO2")()
Ge = material("Ge")()
widths = np.random.rand(9) * 200
solar_cell = SolarCell([
Layer(si(widths[0], "nm"), material=MgF2),
Layer(si(widths[1], "nm"), material=TiO2),
Junction(
[
Layer(si(widths[2], "nm"), material=GaAs, role="window"),
Layer(si(widths[3], "nm"), material=GaAs, role="emitter"),
Layer(si(widths[4], "nm"), material=GaAs, role="base"),
],
kind="DA",
),
TunnelJunction([
Layer(si(widths[5], "nm"), material=GaAs),
Layer(si(widths[6], "nm"), material=GaAs),
]),
Junction(
[
Layer(si(widths[7], "nm"), material=Ge, role="emitter"),
Layer(si(widths[8], "nm"), material=Ge, role="base"),
],
kind="PDD",
),
])
return solar_cell, widths
def test_identify_layers_exceptions():
from solcore.analytic_solar_cells.depletion_approximation import identify_layers
from solcore import material
from solcore.structure import Layer, Junction
Na = np.power(10, np.random.uniform(22, 25))
Nd = np.power(10, np.random.uniform(22, 25))
Lp = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
Ln = np.power(10, np.random.uniform(-9, -6)) # Diffusion length
GaAs_n = material("GaAs")(Nd=Nd, hole_diffusion_length=Ln)
GaAs_p = material("GaAs")(Na=Na, electron_diffusion_length=Lp)
GaAs_i = material("GaAs")()
Ge_n = material("Ge")(Nd=Nd, hole_diffusion_length=Ln)
n_width = np.random.uniform(500, 1000) * 1e-9
p_width = np.random.uniform(3000, 5000) * 1e-9
i_width = np.random.uniform(300, 500) * 1e-9
test_junc = Junction([
Layer(n_width, GaAs_n, role="emitter"),
Layer(p_width, GaAs_p, role="neither")
])
with raises(RuntimeError):
identify_layers(test_junc)
test_junc = Junction([
Layer(n_width, GaAs_n, role="emitter"),
Layer(i_width, GaAs_i, role="intrinsic"),
Layer(p_width, GaAs_p, role="nothing")
])
with raises(RuntimeError):
identify_layers(test_junc)
test_junc = Junction([
Layer(n_width, Ge_n, role="emitter"),
Layer(p_width, GaAs_p, role="base")
])
with raises(AssertionError):
identify_layers(test_junc)
def assemble_qw_structure(repeats, well, bulk_l_top, bulk_l_bottom, barrier, well_interlayer=None,
structure_label="QW Structure", shift_wells=0):
half_barrier = Layer(barrier.width / 2, barrier.material)
qw_structure = Structure()
# qw_structure.append(bulk, layer_label="bulk")
qw_structure.append_multiple([bulk_l_top], layer_labels=["bulk"])
qw_structure.append_multiple([half_barrier], layer_labels=["half barrier"])
if well_interlayer:
qw_structure.append_multiple([well_interlayer, well, well_interlayer, barrier], layer_labels=["interlayer",
"well",
"interlayer",
"barrier"],
repeats=repeats - 1)
qw_structure.append_multiple([well_interlayer, well, well_interlayer, half_barrier, bulk_l_bottom],
layer_labels=[
"interlayer", "well", "interlayer", "half barrier", "bulk"])
else:
qw_structure.append_multiple([well, barrier], layer_labels=["well", "barrier"], repeats=repeats - 1)
qw_structure.append_multiple([well, half_barrier, bulk_l_bottom], layer_labels=["well", "half barrier", "bulk"])
return qw_structure
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)
d_vectors = ((x, 0), (0, x))
area_fill_factor = 0.36
hw = np.sqrt(area_fill_factor) * 500
front_materials = []
back_materials = []
# whether pyramids are upright or inverted is relative to front incidence.
# so if the same etch is applied to both sides of a slab of silicon, one surface
# will have 'upright' pyramids and the other side will have 'not upright' (inverted)
# pyramids in the model
surf = regular_pyramids(elevation_angle=55, size=5, upright=True)
front_surf = Interface('RT_TMM',
texture=surf,
layers=[Layer(si('0.1nm'), Air)],
name='pyramids' + str(options['n_rays']))
back_surf = Interface('Lambertian', layers=[], name='lambertian')
bulk_Si = BulkLayer(201.8e-6, Si, name='Si_bulk') # bulk thickness in m
SC = Structure([front_surf, bulk_Si, back_surf],
incidence=Air,
transmission=Air)
process_structure(SC, options)
results = calculate_RAT(SC, options)
RAT = results[0]
results_per_pass = results[1]
d_vectors = ((x, 0),(0,x))
area_fill_factor = 0.36
hw = np.sqrt(area_fill_factor)*500
front_materials = []
back_materials = []
# whether pyramids are upright or inverted is relative to front incidence.
# so if the same etch is applied to both sides of a slab of silicon, one surface
# will have 'upright' pyramids and the other side will have 'not upright' (inverted)
# pyramids in the model
surf = regular_pyramids(elevation_angle=55, upright=False)
front_surf = Interface('RT_TMM', texture = surf, layers=[Layer(si('0.1nm'), Air)],
name = 'inv_pyramids' + str(options['n_rays']))
back_surf = Interface('RCWA', layers=back_materials, name = 'crossed_grating_60', d_vectors=d_vectors, rcwa_orders=60)
#back_surf = Interface('TMM', layers=[], name = 'planar_back', coherent=True)
bulk_Si = BulkLayer(201.8e-6, Si, name = 'Si_bulk') # bulk thickness in m
SC = Structure([front_surf, bulk_Si, back_surf], incidence=Air, transmission=Air)
process_structure(SC, options)
results = calculate_RAT(SC, options)
RAT = results[0]
results_per_pass = results[1]
options['c_azimuth'])
surf = regular_pyramids(elevation_angle=0, upright=True) # [texture, reverse]
group = RTgroup(textures=[surf])
GaAs = material('GaAs')()
Ge = material('Ge')()
Si = material('Si')()
Air = material('Air')()
#results_front = RT(group, Air, Si, 'test', options, 0, 'front', 0, False)
# lookup table:
layers = [Layer(500e-9, GaAs), Layer(200e-9, Ge)]
make_TMM_lookuptable(layers, Air, Si, 'test', options)
results_front = RT(group,
Air,
Si,
'test',
options,
1,
'front',
len(layers),
save=True)
full = results_front[0].todense()[n_wl - 1]
try:
num = self.junction_indices[junction]
self[num].__dict__.update(kwargs)
except IndexError:
print(
'ERROR updating junction: The junction index must be {} or less.'
.format(len(self.junction_indices)))
def __call__(self, i):
return self[self.junction_indices[i]]
if __name__ == '__main__':
window = material('AlGaAs')(T=298, Na=1e24, Al=0.8)
stack = [Layer(width=si("50nm"), material=window), default_GaAs(298)]
# stack = [default_GaAs(298)]
my_cell = SolarCell(layers=stack)
#
# my_cell.append_multiple([default_GaAs(298), default_GaAs(298), default_GaAs(298)])
# print(my_cell)
from solcore.poisson_drift_diffusion.DriftDiffusionUtilities import solve_pdd, default_photon_flux, \
default_wavelengths
import matplotlib.pyplot as plt
solve_pdd(my_cell, 'QE', vfin=1.2, vstep=0.05, light=True)
QE = my_cell(0).qe
mat.relative_permittivity = 16
all_materials.append(bot_buffer_material)
all_materials.append(bot_nucleation_material)
all_materials.append(bot_cell_n_material)
all_materials.append(bot_cell_p_material)
# We add some other properties to the materials, assumed the same in all cases, for simplicity.
# If different, we should have added them above in the definition of the materials.
for mat in all_materials:
mat.hole_mobility = 3.4e-3
mat.electron_mobility = 5e-2
ARC = [Layer(si('80nm'), material=ARC1), Layer(si('33nm'), material=ARC2)]
top_junction = [
Junction([
Layer(si("18nm"), material=top_window_material, role='window'),
Layer(si("100nm"), material=top_cell_n_material, role='emitter'),
Layer(si("891.248nm"), material=top_cell_p_material, role='base'),
Layer(si("111.445nm"), material=top_cell_TJ_material, role='TJ')
],
sn=1,
sp=1,
kind='DA')
]
middle_junction = [
Junction([
Layer(si("18nm"), material=mid_window_material, role='window'),
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])])