Fish-scale-derived carbon quantum dots coupled with ZnO/Co3O4 for adsorption-assisted visible-light decolorization of reactive black 5.

Visible-light-responsive photocatalysts prepared from low-cost waste resources are attractive for the sustainable treatment of dye-contaminated wastewater. In this work, carbon quantum dots (CQDs) derived from fish scales were integrated with ZnO/Co3O4 to construct a ternary CQD-ZnO/Co3O4 nanocomposite for adsorption-assisted decolorization of reactive black 5 (RB5). ZnO and Co3O4 were prepared by wet-chemical precipitation and co-precipitation, respectively, while CQDs were obtained via hydrothermal carbonization of fish scales. The optimized ternary catalyst, denoted CZC (0.5CQDs-3ZnO/Co3O4), exhibited broadened visible-light absorption, an effective optical band gap of 2.62 eV, and markedly suppressed photoluminescence relative to the individual components, indicating improved interfacial charge separation. XRD, FTIR, SEM-EDX, TEM/SAED, and DLS analyses verified the coexistence of wurtzite ZnO, spinel Co3O4, and CQD-derived carbonaceous domains within a polycrystalline heterostructure, as well as their stable dispersion. Electrochemical impedance spectroscopy (EIS) revealed a lower charge-transfer resistance (R ct) in CZC, thereby facilitating efficient photocatalytic charge separation. RB5 removal depended strongly on pH, initial dye concentration, catalyst dose, and contact time. Fast dark adsorption contributed approximately 80% removal within 30 min, followed by visible-light-assisted decolorization to approximately 88% under optimized conditions; a maximum decolorization of 94% was obtained at pH 2. Adsorption followed pseudo-second-order kinetics and was better described by the Langmuir model, with an estimated maximum capacity of 72.5 mg g-1. Scavenger experiments indicated that hole (h+) and hydroxyl radical (˙OH) related pathways were important, and band-position analysis supported a CQD-mediated Z-scheme-like pathway. The catalyst retained 74% decolorization after three cycles. Exploratory machine-learning analysis further identified initial pollutant concentration as the dominant descriptor controlling removal efficiency. Overall, this study demonstrates that fish-scale-derived CQDs effectively enhance ZnO/Co3O4 performance, making the material a sustainable and promising candidate for industrial wastewater treatment.