Descriptor Design for Perovskite Material with Compatible Molecules via Language Model and First-Principles

Directly applying big language models for material and molecular design is not straightforward, particularly for real-scenario cases, where experimental validation accuracy is required. In this study, we propose a multimode descriptor design method for materials prediction and analysis, leveraging the advantages of the natural language processing literature model and density functional theory (DFT) calculations with the assistance of the genetic algorithm (GA). A case study on prediction of aqueous photocurrents of multisolvent engineered halide perovskite CH