P3HT:PC61BM
1 dataset, together covering 0.2472–1.685 µm. Default: Stelling et al. 2017: n,k 0.247–1.685 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
# P3HT:PC61BM: Stelling et al. 2017: n,k 0.247–1.685 µm
p3ht_pc61bm = ls.fetch_refractiveindex("other", "P3HT-PC61BM", "Stelling", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(p3ht_pc61bm.range_nm) # (247.18, 1684.92) nm
eps = p3ht_pc61bm.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_2c7927c3605b/lightsmith"
p3ht_pc61bm = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(p3ht_pc61bm.source) # citation and provenance travel with the data
Any dataset here, as the library's Tabulated material (p3ht-pc61bm/stelling-2017).
# ... load p3ht_pc61bm as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=p3ht_pc61bm)],
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 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 P3HT:PC61BM
Applications: Solar cells P3HT chemical composition: (C41H53FO4S4)n PC61BM chemical composition: C72H14O2
Other names: {'P3HT': 'PC61BM'}
API: /v1/materials/mat_e87bf1f56c88 · slug p3ht-pc61bm