GaP-InP (Gallium indium phosphide, GaInP)

5 datasets, together covering 0.2254–124 µm. Default: Schubert et al. 1995: n,k 0.250–0.954 µm.

Compare datasets

Tick datasets in the list to add them to the plot (up to 12).

Datasets

Use it in Lightsmith

Load this data in Python, simulate in one more line

pip install lightsmith

import lightsmith as ls

# GaP-InP (Gallium indium phosphide, GaInP): Schubert et al. 1995: n,k 0.250–0.954 µm
gap_inp = ls.fetch_refractiveindex("other", "GaP-InP", "Schubert", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(gap_inp.range_nm)  # (249.61, 953.95) nm
eps = gap_inp.eps([633])  # complex permittivity

Downloads the original record once (pinned to the imported snapshot) and caches it.

import json, urllib.request
import lightsmith as ls

url = "https://materials.lightsmith.dev/v1/datasets/ds_e731ec3584fc/lightsmith"
gap_inp = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(gap_inp.source)  # citation and provenance travel with the data

Any dataset here, as the library's Tabulated material (gap-inp/schubert-1995).

# ... load gap_inp as above, then:
sim = ls.Simulation(
    particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=gap_inp)],
    medium_index=1.0,
    wavelengths=ls.WavelengthRange(start_nm=400, stop_nm=953, num=81),
)
res = ls.solve(sim)  # exact Mie for a sphere
print(res.q_ext)     # extinction efficiency at each wavelength

Same spec runs with DDA, FDTD, BEM or T-matrix: ls.compare(sim, ["mie", "dda"]).

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Lightsmith is open source (MIT): Mie, T-matrix, BEM, DDA, FDTD, RCWA, TMM, mode solvers and inverse design behind one spec, on CPU or GPU. GitHub.

About GaP-InP (Gallium indium phosphide, GaInP)

Other names: Gallium indium phosphide, GaInP

API: /v1/materials/mat_c9267f044b69 · slug gap-inp