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rt_structure_with_lookuptable.py
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rt_structure_with_lookuptable.py
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import numpy as np
import os
from solcore.structure import Layer
from solcore import material, si
from rayflare.textures import planar_surface
from rayflare.ray_tracing import rt_structure
from rayflare.textures import regular_pyramids
from rayflare.options import default_options
import matplotlib.pyplot as plt
import seaborn as sns
from cycler import cycler
pal = sns.cubehelix_palette()
cols = cycler("color", pal)
params = {
"legend.fontsize": "small",
"axes.labelsize": "small",
"axes.titlesize": "small",
"xtick.labelsize": "small",
"ytick.labelsize": "small",
"axes.prop_cycle": cols,
}
plt.rcParams.update(params)
cur_path = os.path.dirname(os.path.abspath(__file__))
# new materials from data (only need to add once, uncomment following lines to do so:
# from solcore.material_system import create_new_material
# create_new_material('Perovskite_CsBr_1p6eV', os.path.join(cur_path, 'data/CsBr10p_1to2_n_shifted.txt'), os.path.join(cur_path, 'data/CsBr10p_1to2_k_shifted.txt'))
# create_new_material('ITO_lowdoping', os.path.join(cur_path, 'data/model_back_ito_n.txt'), os.path.join(cur_path, 'data/model_back_ito_k.txt'))
# create_new_material('Ag_Jiang', os.path.join(cur_path, 'data/Ag_UNSW_n.txt'), os.path.join(cur_path, 'data/Ag_UNSW_k.txt'))
# create_new_material('aSi_i', os.path.join(cur_path, 'data/model_i_a_silicon_n.txt'),os.path.join(cur_path, 'data/model_i_a_silicon_k.txt'))
# create_new_material('aSi_p', os.path.join(cur_path, 'data/model_p_a_silicon_n.txt'), os.path.join(cur_path, 'data/model_p_a_silicon_k.txt'))
# create_new_material('aSi_n', os.path.join(cur_path, 'data/model_n_a_silicon_n.txt'), os.path.join(cur_path, 'data/model_n_a_silicon_k.txt'))
# create_new_material('MgF2_RdeM', os.path.join(cur_path, 'data/MgF2_RdeM_n.txt'), os.path.join(cur_path, 'data/MgF2_RdeM_k.txt'))
# create_new_material('C60', os.path.join(cur_path, 'data/C60_Ren_n.txt'), os.path.join(cur_path, 'data/C60_Ren_k.txt'))
# create_new_material('IZO', os.path.join(cur_path, 'data/IZO_Ballif_rO2_10pcnt_n.txt'), os.path.join(cur_path, 'data/IZO_Ballif_rO2_10pcnt_k.txt'))
# matrix multiplication
wavelengths = np.linspace(300, 1200, 40) * 1e-9
options = default_options()
options.wavelengths = wavelengths
options.project_name = "perovskite_Si_example"
options.phi_symmetry = np.pi / 2
Si = material("Si")()
Air = material("Air")()
MgF2 = material("MgF2_RdeM")()
ITO_back = material("ITO_lowdoping")()
Perovskite = material("Perovskite_CsBr_1p6eV")()
Ag = material("Ag_Jiang")()
aSi_i = material("aSi_i")()
aSi_p = material("aSi_p")()
aSi_n = material("aSi_n")()
LiF = material("LiF")()
IZO = material("IZO")()
C60 = material("C60")()
nxy = 25
calc = True
# setting options
options.wavelengths = wavelengths
options.nx = nxy
options.ny = nxy
options.n_rays = 2 * nxy**2
options.depth_spacing = si("1um")
options.parallel = True
Spiro = [1.65, 0]
SnO2 = [2, 0]
front_layers = [
Layer(100e-9, MgF2),
Layer(110e-9, IZO),
Layer(15e-9, C60),
Layer(1e-9, LiF),
Layer(440e-9, Perovskite),
Layer(6.5e-9, aSi_n),
Layer(6.5e-9, aSi_i),
]
triangle_surf = regular_pyramids(
elevation_angle=55, upright=True, size=1, interface_layers=front_layers
)
triangle_surf_inc = regular_pyramids(
elevation_angle=55,
upright=True,
size=1,
interface_layers=front_layers,
coherency_list=["i"] * len(front_layers),
)
triangle_surf_back = regular_pyramids(
elevation_angle=55, upright=False, size=1, interface_layers=[Layer(200e-9, Ag)]
)
planar_surf = planar_surface(size=1)
# set up ray-tracing options
rtstr = rt_structure(
textures=[triangle_surf, planar_surf, triangle_surf_back],
materials=[Si, Si],
widths=[130e-6, 130e-6],
incidence=Air,
transmission=Ag,
use_TMM=True,
options=options,
save_location="current",
)
result = rtstr.calculate(options)
options.project_name = "inc"
rtstr_inc = rt_structure(
textures=[triangle_surf_inc, planar_surf, triangle_surf_back],
materials=[Si, Si],
widths=[130e-6, 130e-6],
incidence=Air,
transmission=Ag,
use_TMM=True,
options=options,
save_location="current",
)
result_inc = rtstr_inc.calculate(options)
# result = result_new
# result = np.vstack((options['wavelengths']*1e9, result['R'], result['R0'], result['T'], result['A_per_layer'][:,0])).T
checking = result["A_per_interface"]
#
fig = plt.figure(figsize=(9, 3.7))
plt.subplot(1, 1, 1)
plt.plot(
wavelengths * 1e9,
result["R"],
"-o",
color=pal[0],
label=r"R$_{total}$",
fillstyle="none",
)
plt.plot(
wavelengths * 1e9,
result["R0"],
"-o",
color=pal[1],
label=r"R$_0$",
fillstyle="none",
)
plt.plot(
wavelengths * 1e9, result["T"], "-o", color=pal[2], label=r"T", fillstyle="none"
)
plt.plot(
wavelengths * 1e9,
np.sum(result["A_per_layer"], 1),
"-o",
color=pal[3],
label=r"A",
fillstyle="none",
)
plt.plot(wavelengths * 1e9, result["A_per_interface"][0], "-o")
plt.plot(wavelengths * 1e9, result["A_per_interface"][1], "-o")
plt.plot(
wavelengths * 1e9,
result_inc["R"],
"--o",
color=pal[0],
label=r"R$_{total}$",
fillstyle="none",
)
plt.plot(
wavelengths * 1e9,
result_inc["R0"],
"--o",
color=pal[1],
label=r"R$_0$",
fillstyle="none",
)
plt.plot(
wavelengths * 1e9,
result_inc["T"],
"--o",
color=pal[2],
label=r"T",
fillstyle="none",
)
plt.plot(
wavelengths * 1e9,
np.sum(result_inc["A_per_layer"], 1),
"--o",
color=pal[3],
label=r"A",
fillstyle="none",
)
plt.plot(wavelengths * 1e9, result_inc["A_per_interface"][0], "--o")
plt.plot(wavelengths * 1e9, result_inc["A_per_interface"][1], "--o")
plt.title("a)", loc="left")
plt.plot(-1, -1, "-ok", label="RayFlare")
plt.plot(-1, -1, "--k", label="PVLighthouse")
plt.xlabel("Wavelength (nm)")
plt.ylabel("R / A / T")
plt.ylim(0, 1)
plt.xlim(300, 1200)
plt.legend()
plt.show()
import xarray as xr
lookuptable = xr.open_dataset(os.path.join(rtstr_inc.save_location, "int_0" + ".nc"))
data = lookuptable.loc[dict(side=1, pol="u")].interp(angle=0.2, wl=1100)
a = lookuptable["Alayer"].loc[dict(side=-1, pol="u")]
print(a.where(a == a.max(), drop=True))
b = a.sum(dim="layer")
from rayflare.transfer_matrix_method import tmm_structure
ost = front_layers[::-1]
options.pol = "u"
options.coherent = False
options.coherency_list = ["i"] * len(front_layers)
options.theta_in = 1.2
a = tmm_structure(ost, incidence=Si, transmission=Air, no_back_reflection=False)
a_sharp = tmm_structure(
[Layer(440e-9, Perovskite)],
incidence=Si,
transmission=Air,
no_back_reflection=False,
)
res = a.calculate(options)
options.coherent = False
options.coherency_list = ["i"]
# res_sharp = a_sharp.calculate(options)
# total A seems fine? Because scaled....
plt.figure()
plt.plot(wavelengths * 1e9, res["A_per_layer"])
plt.plot(wavelengths * 1e9, res["R"], "--k")
plt.plot(wavelengths * 1e9, res["T"], "--r")
# plt.plot(wavelengths*1e9, res_sharp["R"], 'r--')
# plt.plot(wavelengths*1e9, res_sharp["A_per_layer"], 'b--')
# plt.plot(wavelengths*1e9, res_sharp["A_per_layer"], 'r--')
plt.legend(["aSi_n", "Perovskite", "MgF2"])
plt.ylim(-1, 2)
plt.show()
from solcore.absorption_calculator.tmm_core_vec import inc_tmm, inc_absorp_in_each_layer
n_list = [
np.array([4.976, 3.94, 3.614, 3.52]),
np.array(
[3.0027 + 3.2014j, 3.9528 + 0.32338j, 3.5126 + 0.039199j, 3.3643 + 0.023508j]
),
# np.array([3.0031+3.2018j , 3.9528+0.32444j , 3.5126+0.041007j,
# 3.3643+0.026026j]),
np.array(
[1.74 + 0.96j, 2.47963404 + 0.18781702j, 2.21130799 + 0.0j, 2.1370813 + 0.0j]
),
# np.array([1.40881337+0.j, 1.39190178+0.j, 1.3878255 +0.j, 1.38526595+0.j]),
# np.array([2.10211415+0.59159079j, 2.02373836+0.03972636j,
# 1.9585232 +0.0187167j , 1.93801332+0.01336343j]),
# np.array([2.49880534+0.13326956j, 2.00757794+0.00918188j,
# 1.80529446+0.j , 1.56865962+0.j ]),
np.array(
[
1.439164 + 0.001162j,
1.421732 + 0.000569j,
1.418722 + 0.000379j,
1.417674 + 0.000282j,
]
),
np.array([1.0 + 0.0j, 1.0 + 0.0j, 1.0 + 0.0j, 1.0 + 0.0j]),
]
d_list = [
np.inf,
6.5,
# 6.5,
440.0,
# 1.0, 14.999999999999998, 110.0,
99.99999999999999,
np.inf,
]
c_list = ["i", "i", "i", "i", "i", "i", "i", "i", "i"]
c_list = ["i"] * 5
th_0 = 1
lam_vac = [300, 600, 900, 1200]
out = inc_tmm("s", n_list, d_list, c_list, th_0, lam_vac)
A_per_layer = np.array(inc_absorp_in_each_layer(out))
# plt.figure()
# plt.plot(lam_vac, out["R"], '-k')
# plt.plot(lam_vac, A_per_layer[0,:], '--r')
# plt.plot(lam_vac, out["T"], '--r')
# plt.plot(lam_vac, A_per_layer[1:-1].T)
# plt.show()