PTB7:PC71BM
1 dataset, together covering 0.3016–1.685 µm. Default: Stelling et al. 2017: n,k 0.302–1.685 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
# PTB7:PC71BM: Stelling et al. 2017: n,k 0.302–1.685 µm
ptb7_pc71bm = ls.fetch_refractiveindex("other", "PTB7-PC71BM", "Stelling", ref="c5c2f188e848453def5970e347399d653df2ffc2")
print(ptb7_pc71bm.range_nm) # (301.58, 1684.92) nm
eps = ptb7_pc71bm.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_bfea3c71533f/lightsmith"
ptb7_pc71bm = ls.Tabulated.model_validate(json.load(urllib.request.urlopen(url)))
print(ptb7_pc71bm.source) # citation and provenance travel with the data
Any dataset here, as the library's Tabulated material (ptb7-pc71bm/stelling-2017).
# ... load ptb7_pc71bm as above, then:
sim = ls.Simulation(
particles=[ls.Particle(shape=ls.Sphere(radius_nm=50), material=ptb7_pc71bm)],
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 PTB7:PC71BM
Applications: Solar cells PTB7 chemical composition: (C41H53FO4S4)n
Other names: {'PTB7': 'PC71BM'}
API: /v1/materials/mat_e1eae577ba92 · slug ptb7-pc71bm