Pre-Reduction-Activated Carbon-Based Zinc Vanadate Nanosheet Composite with Zn-O-V Performance Synergy for Machine Learning-Enabled Multiplex Pesticide Detection.

The simultaneous and accurate detection of multiple pesticide residues remains a critical challenge in electrochemical sensing. Herein, a strategy is proposed for the in situ growth of interconnected Zn3(OH)2V2O7·2H2O (ZVO) nanosheets on carbon cloth (CC), forming ZVO/CC electrodes for the simultaneous detection of thiophanate-methyl and diuron. A negative-potential pre-reduction treatment is employed to regulate the interfacial electronic structure and activate sensing sites of ZVO/CC electrodes. During pre-reduction, partial V5+ is reduced to V4+, accompanied by the formation of oxygen vacancies, which reconstruct local electronic states and decrease charge-transfer resistance. Meanwhile, the chemically integrated Zn-O-V framework exhibits a performance synergy, resulting in significantly enhanced and well-distinguished electrochemical responses toward the target pesticides. The ZVO/CC electrode achieves linear detection ranges of 0.1-25 μM for thiophanate-methyl and 0.1-40 μM for diuron, with low detection limits of 12.4 nM and 28.5 nM, respectively. Furthermore, machine learning algorithms are introduced to resolve partial overlapping signals, enabling simultaneous pesticide classification and concentration prediction. The integration of interfacial engineering with machine learning provides an effective strategy for achieving simultaneous multi-pesticide detection at the nanomolar level.