Green Synthesis of CuO/CQD Nanocomposites for Printed Electrochemical Glucose Sensor

Abstract

These datasets contain the data generated during a study on the green synthesis of CuO/CQD nanocomposites using <i>Aloe arborescens</i> extract as the reducing agent, and their application as a printed non-enzymatic electrochemical glucose sensor for diabetes management.The files include:<i>Aloe arborescens</i> extraction optimisation data and total phenolic content (TPC) measurements.CuO/CQD synthesis optimisation of precursor concentration, extract concentration, pH, hydrothermal temperature, and reaction time.Electrode fabrication optimisation data, including annealing temperature and deposited/printed layer-number studies for drop-cast and microplotted films on FTO and screen-printed gold electrodes (SPGEs).Electrochemical characterisation/performance datasets (cyclic voltammetry, scan rate analysis, chronoamperometry, electrochemical impedance spectroscopy).Analytical performance data for glucose detection, including calibration curves, sensitivity, linear range, and limit of detection.Selectivity, reproducibility, repeatability, stability, shelf-life and real-sample validation data.