Ryan T. Lingg

DFTB-Based Validation of Molecules Generated by Reversible Junction Tree Reinforcement Learning: A Case Study on Molecular Solar Thermal Fuels

Machine-learning methods are widely used for molecular generation across vast chemical spaces. However, most studies evaluate model performance using empirical descriptors such as logP and molecular weight, which do not indicate whether generated molecules satisfy target properties. Moreover, when generative models pro...