Cation-Deficient Two-Dimensional BiOBr for High-Integration Computational Fingerprint Recognition

Advanced biometric security systems require photodetectors that not only exhibit strong immunity to environmental interference but also possess the capability to perform intelligent information processing directly at the sensing level. Two-dimensional (2D) materials have emerged as promising candidates for next-generation optoelectronic devices; however, the simultaneous realization of high-performance solar-blind ultraviolet (UV) detection and neuromorphic functionality within a single material platform remains a significant challenge. Here, we report a chemical vapor deposition strategy for the synthesis of 2D BiOBr nanosheets enriched with bismuth vacancies (BiOBr-V Bi ). The resulting cation-deficient nanosheets display a pronounced photoresponse in the solar-blind UV region (265 nm) together with well-defined photonic synaptic plasticity. The introduction of Bi vacancies generates defect-mediated carrier trapping states that induce persistent photoconductivity, thereby enabling synapse-like behaviors such as short-term plasticity and learning-forgetting dynamics. Exploiting this dual functionality, we further establish an optoelectronic computing framework capable of performing fingerprint recognition. Through an optoelectronic reservoir computing architecture, the BiOBr-V Bi -based system achieves an identification accuracy of 99.94% even under 20% noise perturbation. This work highlights defect engineering in 2D BiOBr as a powerful strategy for endowing optoelectronic materials with multifunctional capabilities and presents a compact platform for secure biometric authentication, anti-counterfeiting technologies, and intelligent solar-blind imaging.