Propanee soot
1 dataset, together covering 0.4358–10 µm. Default: Dalzell and Sarofim 1969: n,k 0.4358–10 µm.
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Use it in Lightsmith
Load this data in Python, simulate in one more line
pip install lightsmith
import lightsmith as ls
# Propanee soot: Dalzell and Sarofim 1969: n,k 0.4358–10 µm
propane_soot = ls.fetch_refractiveindex("other", "propane_soot", "Dlazell", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(propane_soot.range_nm) # (435.8, 10000) nm
eps = propane_soot.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_4b3e78eeb916/lightsmith"
propane_soot = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(propane_soot.source) # citation and provenance travel with the data
Any dataset here, as the library's Tabulated material (propane-soot/dalzell-sarofim-1969-dlazell).
# ... load propane_soot as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=propane_soot)],
medium_index=1.0,
wavelengths=ls.WavelengthRange(start_nm=436, stop_nm=1000, 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"]).
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 Propanee soot
Other names: propane_soot
Also listed in
API: /v1/materials/mat_db541ab22d67 · slug propane-soot