PEDOT:PSS
1 dataset, together covering 0.3019–1.097 µm. Default: Chen et al. 2015: n,k 0.3–1.1 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
# PEDOT:PSS: Chen et al. 2015: n,k 0.3–1.1 µm
pedot_pss = ls.fetch_refractiveindex("other", "PEDOT-PSS", "Chen", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(pedot_pss.range_nm) # (301.9, 1096.8) nm
eps = pedot_pss.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_6d8304d662f6/lightsmith"
pedot_pss = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(pedot_pss.source) # citation and provenance travel with the dataAny dataset here, as the library's Tabulated material (pedot-pss/chen-2015).
# ... load pedot_pss as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=pedot_pss)],
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 PEDOT:PSS
Other names: {'PEDOT': 'PSS'}, Clevios AI 4083, Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate
API: /v1/materials/mat_df43329e59c2 · slug pedot-pss