Nevertheless, even in a single iteration, our workflow succeeded in predicting a significantly large number of molecules with very small HOMO-LUMO gaps < 1.7 eV (384) which is much larger than the fraction of such molecules contained in the entire QM9-based original data set containing 95k molecules . This constitutes proof-of-principle of our combined surrogate/generative model approach, even factoring in that the MLM was not even trained on molecules with particular optical properties.