Zirconium copper oxide microflowers based non-enzymatic screen-printed electrochemical sensor for the detection of glucose in saliva, urine, and blood serum

Zirconium copper oxide microflowers (Zr/CuO MF) based non-enzymatic sensor was developed for glucose detection in saliva, urine, and blood. An easy urea hydrolysis method was employed for the synthesis of the metal oxide and further calcined to improve the catalytic property. The flower-like morphology of the Zr/CuO was confirmed by SEM analysis and the presence of copper and zirconium was examined using energy dispersive X-ray analysis (EDAX). The Zr/CuO MF modified screen-printed electrodes exhibited excellent glucose sensing performance in 0.15 M NaOH medium and could quantify glucose in the range from 10 & mu;M to 27 mM. A high sensitivity of 1.815 & PLUSMN; 0.003 mA mM-1 cm-2 was obtained for lower glucose concentration from 15 & mu;M to 3 mM and 1.250 & PLUSMN; 0.006 mA mM-1 cm-2 for higher concentration glucose from 3 to 27 mM. The limit of detection of the fabricated sensor was found to be 0.8 & mu;M. The sensor displayed high selectivity and stability towards glucose in different body fluids like saliva, urine, and blood serum at a working potential of 0.6 V (vs. Ag/AgCl). In saliva, urine, and serum samples, the sensor exhibited excellent recovery of 95-108, 92-108, and 93-101% in saliva, urine, and serum, respectively, with a relative standard deviation of less than 10%, demonstrating high accuracy and reliability of the sensor. The developed sensor is promising for developing an invasive and non-invasive point-of-care testing device for glucose detection.

Automated summary

A non-enzymatic sensor based on zirconium copper oxide microflowers was developed for glucose detection in saliva, urine, and blood. The sensor exhibited excellent sensitivity, selectivity, and stability, with high accuracy and reliability in different body fluids. This sensor shows promise for the development of invasive and non-invasive point-of-care testing devices for glucose detection.