NIR-II emission wavelength prediction
BTD-EmisPred provides machine-learning estimates of the experimental maximum emission wavelengths of BTD derivatives from molecular structure and solvent conditions.
The platform supports molecular design by allowing users to enter a SMILES string, select a solvent and obtain a predicted emission wavelength in nanometres.
Input
One molecule SMILES and one normalized solvent label.
Model
Machine-learning prediction from molecular structure and solvent conditions.
Output
The predicted emission wavelength in nm for the submitted molecule and solvent.