Bioinspired Perovskite Nanostructures for Artificial Intelligence‐Based Anti‐Counterfeiting and Amplified Spontaneous Emission

Abstract Halide perovskites (CsPbX ₃ , X = Cl, Br, I) have emerged as transformative optoelectronic materials due to their tunable bandgap, exceptional photoluminescence quantum yield (PLQY > 90%), and solution processability. Although nanostructure engineering offers avenues for boosting light extraction efficiency and enabling dynamic optical functionalities, the inherent environmental instability of perovskites and fundamental incompatibility with conventional photolithography—which involves multi‐step etching processes that degrade ionic lattices—seriously hinder their practical application. To address these challenges, the study proposes an innovative strategy combining in situ crystallization with nanoimprint lithography (NIL), which realizes the fabrication of large‐area (>6 cm ² ), high‐resolution perovskite nanostructures. The designed hexagonally arranged ‘yurt’‐shaped nanoarray, inspired by the nanoscale structure on cicada wings, exhibits amplified spontaneous emission (ASE) in the near‐infrared region at a photoexcitation flux of 134 µJ cm ⁻² , achieved through the modulation of electric and magnetic dipole resonances. Additionally, perovskite nanostructures can generate two types of colors: extrinsic structural color and intrinsic emission color. By fine‐tuning the excitation intensity, the resultant color can be dynamically adjusted, thereby producing a substantial dataset necessary for deep learning‐based color recognition tasks. Ultimately, this study presents a convenient, accurate, and rapid color anti‐counterfeiting label recognition strategy grounded in deep learning methodologies. The findings not only offer novel insights for advanced anti‐counterfeiting technologies but also provide an innovative pathway for the cost‐effective fabrication of high‐performance optoelectronic devices characterized by high resolution and expansive perovskite nanostructures.