Reinforcement Learning for Adsorbate–Substrate Modeling in Silico – the Genesis of RLMaterial software

Modeling functional materials requires understanding the substrate@adsorbate interactions. In this work, a reinforcement learning method for adsorbate@substrate structural determination was developed and implemented in the RLMaterial code. The software was used to study the glycine interactions with boron nitride (BN) and phenylboronic acid in cyclodextrin.