To illustrate a typical usage of the extrapolative ability of the models in material design applications, we implemented a genetic algorithm to discover stable structures using the scores of the MLP and Chemprop models as the corresponding fitness functions. To make the task more challenging, we did not use the models trained on the full dataset, instead we used the models trained on split molecules to be propagated to the next generation were randomly selected from this group of children using probabilities weighted by the predicted Stability Scores.