Interfacial Self-Assembly Ag-Ag₂S Asymmetric Ordered Nanowires for Photoelectrochemical Intelligent Detection of Dual...

The random stacking and intrinsic high symmetry of substrate materials seriously affect the photoelectrochemical (PEC) detection performance. Herein, taking silver nanowires as templates, the silver-silver sulfide (Ag-Ag₂S) asymmetric ordered nanowires (AONs) are prepared by the interfacial self-assembly and interface-confined sulfurization strategies. Based on the anisotropic characteristics of Ag-Ag₂S AONs on two sides, a novel PEC platform is reported for dual long non-coding RNAs (lncRNAs) co-detection in plasma exosomes, with machine learning-assisted data analysis for cancer intelligent diagnosis. The photocurrent response of Ag-Ag₂S AONs is 16 times that of disordered Ag-Ag₂S, while finite-difference time-domain and density functional theory simulations confirm the optical anisotropy of Ag-Ag₂S AONs. Employing magnetic separation to differentiate signals, this developed PEC biosensor achieves selective recognition for lncRNAs MALAT1 and HOTAIR with low detection limits of 1.5 and 1.7 fM, respectively. Importantly, machine learning-assisted Ag-Ag₂S AONs in distinguishing lung cancer patients from healthy individuals can reach 90% accuracy. The study combined the integration of advanced sensing materials and machine learning model, providing a new approach for intelligent monitoring of biomarkers.