Schnabel

Data for Main / Tin / Schnabel

import os
import matplotlib.pyplot as plt
import numpy as np
import refidx as ri

plt.style.use("../../doc/refidx.mplstyle")
db = ri.DataBase()
matid = ['main', 'TiN', 'Schnabel']
mat = db.get_item(matid)
wr = mat.wavelength_range
lamb = np.linspace(*wr, 1000)
index = mat.get_index(lamb)
fig, ax = plt.subplots(2, 1, figsize=(3, 3))
ax[0].plot(lamb, index.real, "-", color="#aa0044")
ax[1].plot(lamb, index.imag, "-", color="#6886b3")
ax[0].set_xlabel(r"Wavelength ($\rm μm$)")
ax[1].set_xlabel(r"Wavelength ($\rm μm$)")
ax[0].set_ylabel(r"$n^{\prime}$")
ax[1].set_ylabel(r"$n^{\prime\prime}$")
plt.suptitle(mat)
mat.print_info(
    html=True,
    tmp_dir=os.path.join("..","..", "doc", "auto_gallery","TiN"),
    filename="out_main_TiN_Schnabel.html",
)

Comments

Reactive magnetron sputtering; Ar/N₂ gas mixture of 10/1; negative bias potential: 100 V; substrate temperature: 400°C

References

V. Schnabel, R. Spolenak, M. Döbeli, H. Galinski. Structural color sensors with thermal memory: Measuring functional properties of Ti-based nitrides by eye, Adv. Opt. Mater. 6, 1800656 (2018)

Estimated memory usage: 225 MB