Design of an Intelligent Profiling Platform for Multiple Antibiotic Discrimination Enabled by Time-Resolved Histidine-Functionalized Cupric Oxide Nanozyme Sensor Array at Neutral pH

Abstract Nanozymes with peroxidase-like (POD) activity have broad applications in biosensing, but their catalytic activity is often optimal under acidic conditions, which severely limits their applications in neutral environments. Here, we constructed a histidine-functionalized cupric oxide (CuO@His) nanozyme via defect engineering. Relative to CuO, CuO@His exhibited enhanced POD activity at neutral pH and was capable of catalyzing 3,3′,5,5′-tetramethylbenzidine (TMB) to generate blue oxidized TMB, which showed absorption peaks at 370 and 652 nm. Subsequently, we employed the recursive feature elimination strategy to screen the optimal wavelength–time combinations as the sensing channels and further established the characteristic “fingerprints” of different antibiotics. Moreover, with the assistance of machine learning algorithms, a concentration- and matrix-independent antibiotic identification model was established under neutral conditions. Finally, a visual intelligent sensing platform based on deep learning was constructed. This work provides a new strategy for the efficient identification of multiple antibiotics at neutral pH.