Using the TMM solver to calculate the reflextion of a multilayered ARC

../_images/RAT_of_ARC.png
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
import numpy as np

from solcore.structure import Structure
from solcore.absorption_calculator import calculate_rat

E_eV = np.linspace(0.65, 4, 1000)


def nk_convert(fname, energy):
    """ Designed to handle nk data files"""

    # Import data...
    E_n, n, E_k, k = np.loadtxt(fname, delimiter=",", unpack=True)
    print("File :: " + fname + " :: Imported Successfully!")

    # Interpolate data...
    n_interp = interp1d(E_n, n, bounds_error=False, fill_value=(n[0], n[-1]))(energy)
    k_interp = interp1d(E_k, k, bounds_error=False, fill_value=(k[0], k[-1]))(energy)

    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...
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)))

fig, ax2 = plt.subplots(1, 1)

for i, RAT in enumerate(RAT_angles):
    ax2.plot(1240 / E_eV, RAT[1] * 100, ls="-", color=colors[i], label="%4.1f$^\circ$" % RAT[0])
    ax2.plot(1240 / E_eV, RAT[2] * 100, ls="--", color=colors[i])

ax2.set_ylim([0, 100])
ax2.set_xlim([300, 1800])
ax2.set_xlabel("Wavelength (nm)")
ax2.set_ylabel("Reflection and Transmission (%)")
ax2.legend(loc=5)
ax2.text(0.05, 0.45, '(a)', transform=ax2.transAxes, fontsize=12)

plt.tight_layout(w_pad=4)
plt.show()