Design Rules for Two-Dimensional Organic Semiconductor-Incorporated Perovskites (OSiP) Gleaned from Thousands of Simulated Structures

Abstract

Organic-inorganic hybrid perovskite semiconductors are under investigation for many applications owing to their excellent optoelectronic properties and relatively simple processing. Two-dimensional (2D) halide perovskites are an attractive class of hybrid perovskites that have additional optoelectronic tunability due to their accommodation of relatively large organic ligands. Nevertheless, contemporary ligand design depends on either expensive trial-and-error testing of whether a ligand can be integrated within the lattice or conservative heuristics that unduly limit the scope of ligand chemistries. Here, the structural determinants of ligand incorporation and perovskite stability are established by molecular dynamics (MD) simulations of over ten thousand perovskites, including an algorithmically generated set of prospective ligand chemistries and all previously reported experimental primary ammonium ligands based on C, H, O, S, and N. The simulation results show near-perfect predictions of positive and negative literature examples, predict trade-offs between several ligand features and perovskite stability, and ultimately predict an inexhaustibly large 2D-compatible ligand design space. This dataset is used to train machine learning classifiers capable of predicting the geometric stability of perovskite structures based solely on generalizable ligand features, thus providing an inexpensive tool for screening putative ligands. As a demonstration, the model was used to down-select five new ligands that were successfully synthesized and incorporated into 2D perovskites. This work provides a new paradigm for future low-dimensional perovskite design.