Electrochemical sensing device based on Cu/PPy heterostructure: Detection of nitrite at low reduction potentials and machine learning-driven data analysis visualisation.

To achieve highly selective, low-potential nitrite detection, this study developed a self-supporting sensing electrode based on the synergistic effect of copper and polypyrrole. A Cu/PPy/CC composite electrode was constructed on a carbon cloth substrate via an electrodeposition technique. At a low operating potential of -0.05 V vs.Hg/HgO, the electrode delivers outstanding sensing performance: a sensitivity of 7170 μA·mM⁻¹ ·cm⁻², a detection limit of 0.137 μM, a linear range of 10-1000 μM, along with excellent interference resistance and long-term stability. Density functional theory calculations confirm that the interfacial synergy between copper and polypyrrole significantly enhances nitrite adsorption capacity and electron transfer efficiency. Furthermore, this study innovatively proposes a hybrid deep learning framework that integrates automatic convolutional features with expert knowledge, achieving high-precision concentration prediction directly from cyclic voltammetry signals. The model achieves a coefficient of determination of 0.9999, substantially enhancing detection reliability and physical interpretability. This research establishes a new paradigm for synergistic material design and intelligent algorithms in developing high-performance electrochemical sensors, propelling nitrite detection technology toward low-potential, high-sensitivity, and intelligent applications.