Diesel soot
3 datasets, together covering 0.26–55.56 µm. Default: Querry 1987: Sample 1; n,k 0.260–55.6 µm.
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Datasets
Use it in Lightsmith
Load this data in Python, simulate in one more line
pip install lightsmith
import lightsmith as ls
# Diesel soot: Querry 1987: Sample 1; n,k 0.260–55.6 µm
diesel_soot = ls.fetch_refractiveindex("other", "diesel_soot", "Querry-NMSU", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(diesel_soot.range_nm) # (260, 55555.6) nm
eps = diesel_soot.eps([633]) # complex permittivityDownloads 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_d2a239b6049d/lightsmith"
diesel_soot = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(diesel_soot.source) # citation and provenance travel with the dataAny dataset here, as the library's Tabulated material (diesel-soot/querry-1987-nmsu).
# ... load diesel_soot as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=diesel_soot)],
medium_index=1.0,
wavelengths=ls.WavelengthRange(start_nm=400, stop_nm=1000, num=81),
)
res = ls.solve(sim) # exact Mie for a sphere
print(res.q_ext) # extinction efficiency at each wavelengthSame 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 Diesel soot
Other names: diesel_soot
Also listed in
API: /v1/materials/mat_4bb6c090741e · slug diesel-soot