Controlling aggregation-induced emission of iridium(Ⅲ) complexes via molecular hydrophilic-lipophilic interactions and in-situ electrostatic self-assembly.

Exploring the internal relationship between the structure and properties of AIE-active iridium complexes and their applications have been great significance. It is imperative to acknowledge that the precise control of nanoparticle morphology and particle size of organic molecules in solutions remains elusive, while comprehending the luminescent mechanisms of self-assembled aggregates continues to present a challenge. The previously work proposed that solvent-induced amphiphilic molecules could enhance the self-assembly properties of iridium complexes, but the influence of ligands' hydrophilic-lipophilic interactions on the AIE characteristics of iridium complexes remained unclear. Herein, we designed and synthesized a series of cationic iridium complexes featuring cyclometalated ligands with aldehyde groups and auxiliary ligands with chains of varying lengths. The synergistic interaction between the hydrophilic aldehyde groups and the lipophilic N^N ligand promotes the formation of self-assembled J-aggregates, which is vital for the AIE performance. In the presence of EDTA ions, the Ir-C6-BCz complex evolves from AIE-active nanotoroids to AIEE-active nanofibers through an in-situ electrostatic self-assembly process. Based on these properties, Ir-C6-BCz was used for fingerprint recognition with excellent imaging results. We could control the AIE properties of iridium complexes from single molecule to 3D aggregates and reveal their self-assembly mechanism. A novel two-step fingerprint recognition method using the in-situ electrostatic self-assembly was developed. The method significantly enhances fluorescence intensity and image contrast, showing great analytical potential for latent fingerprint detection. This work not only offers a comprehensive design strategy for novel self-assembly materials but also highlights the adaptability of iridium complex in fingerprint recognition.