Chemprop representation uses the D-MPNN framework "as is" to create a fingerprint embedding that is optimized for predicting absorption peak energies. this approach was previously shown to be successful in predicting solvation free energies. All dye-solvent pairs for which any of the above features could not be calculated were dropped from the dataset.