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Electrochemical methods evaluate discharge dynamics in Ni-doped CuO nanoparticles, suggesting enhanced performance through defect engineering.
This study employs a comprehensive electrochemical methodology to evaluate the electrochemical kinetics of Ni-doped CuO nanoparticles synthesized via the solution combustion method. Working electrodes were prepared by coating a composite slurry onto nickel foam and tested in a three-electrode system with a 3 M KOH electrolyte. Cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS) were employed to investigate charge storage mechanisms and interfacial dynamics. A key advancement is the use of the R²-Window Linear Discharge (R2WLD) method to segment GCD curves and extract linear and pseudocapacitive discharge regions with high fidelity. Additionally, nonlinear Kernel Principal Component Analysis (KPCA) was employed to classify electrochemical regimes based on scan rate behavior. To interpret the evolution of discharge symmetry, a 1D Ising model was adapted to model energetic state transitions under increasing perturbation. These findings underscore the critical role of defect and lattice engineering in tuning the functional response of correlated oxide systems.
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Lin et al. (2026) studied this question.
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