Text-Embedding-Assisted Design of Rigid Molecular Cations for Suppressing Ion Migration in Hybrid Single-Crystal X-ray Detectors.

Hybrid single crystals exhibit remarkable optoelectronic properties that make them highly promising for photovoltaic devices and radiation detectors. However, ion migration-induced instability represents a critical barrier to their commercial viability. By integrating large language models (LLMs) with k-Nearest Neighbor (kNN) algorithms, we develop a machine-learning model that identifies rigid organic cations as effective modulators for perovskite crystal stiffness, thereby suppressing ion migration. Guided by the analysis, we replaced the flexible alkyl chains in (HDA)BiI5 (HDA = 1,6-hexanediamine) with rigid carbon rings to synthesize a highly stable (CHDA)BiI5 single crystal (CHDA = trans-1,4-diaminocyclohexane). Density functional theory (DFT) calculations revealed that the rigid CHDA molecule exhibits ordered vibrations and stronger interactions with the inorganic framework compared to the disordered vibrations of HDA. Solid-state nuclear magnetic resonance (SSNMR) spin-lattice relaxation measurements further confirmed enhanced lattice rigidity, with the relaxation rate decreasing from 1.29 s-1 to 0.15 s-1, enhancing lattice rigidity. Consequently, the ion migration activation energy increased substantially from 0.42 to 0.61 eV. The resulting (CHDA)BiI5 X-ray detector achieved an exceptional sensitivity of 8209 μC·Gyair-1·cm-2 at 175 V/mm and a low detection limit of 4.7 nGy s-1. This study underscores the pivotal role of organic cation rigidity in optimizing the structural stability and functional performance of low-dimensional hybrid semiconductors.