Predict structures from PXRD pattern

What's the difference between sinc10 and sinc100?

@mmoderwell They're two separately trained checkpoints of the same model — the number is the crystallite-size scale of the peak broadening in the training patterns:

• sinc10 — trained on patterns broadened for ~10 Å (~1 nm) crystallites: few, wide, heavily overlapping peaks. This is the nanocrystalline end the paper targets (it verifies solutions down to 10 Å crystallites), and the route default.

• sinc100 — trained on patterns broadened for ~100 Å (~10 nm) crystallites: sharp, well-resolved reflections.

Practically the regime picks two things: which checkpoint generates candidates, and the sinc² broadening kernel applied to re-simulated candidate patterns before R-factor scoring. Your input pattern is not re-broadened when pattern_kind=experimental (it already carries its own crystallite broadening); a sharp pattern_kind=synthetic pattern gets the kernel applied to match the training distribution.

Choose whichever matches your pattern's peak sharpness. A sharp pattern run through sinc10 gets over-broadened candidates and loses R discrimination; a very broad pattern through sinc100 lands outside the training distribution. When in doubt, sinc10 — the 1 nm end is the harder case and this service's target use.

(I noticed this route's parameter tooltip says "~10 nm" where it should say "~10 Å" — my typo, fixing the description now.)