Ultrasensitive detection of cytotoxic food preservative tert-butylhydroquinone using 3D cupric oxide nanoflowers embedded functionalized carbon nanotubes

Accurate detection of cytotoxic food preservative tert-butylhydroquinone (TBHQ) has significant importance in maintaining food quality and safety. TBHQ is a chronic hazard to aquatic life and its use in applications involving direct human exposure and frequent release to environment makes its quantification critical to maintain safety. Hence, we report development of a sensitive electrochemical sensor for TBHQ determination at nanomolar level in commonly used edible oils and water sample. Novel cupric oxide (CuO) decorated amine functionalized carbon nanotubes (NH2-CNTs) were prepared for development of TBHQ sensor. 3D CuO nanoflowers and NH2-CNTs were synthesized using hydrothermal and ultrasound-assisted method respectively. Techniques such as SEM, elemental mapping, XRD, FTIR, micro Raman, XPS, EIS, and UV-Visible spectroscopy were taken to affirm significant characterizations of synthesized materials. We have observed outstanding electrocatalytic activity towards TBHQ detection using the sonochemically prepared nanocomposite modified screen printed carbon electrode (SPCE). The proposed sensor exhibited ultra-low detection limit at 3 nM and exceptional sensitivity at 37.7 mu A mu M-1 cm(-2). Furthermore, TBHQ sensor showcased outstanding anti-interference, stability, reproducibility, and repeatability. The practical feasibility of TBHQ detection was validated using real sample analysis resulting in excellent recovery in the range 95.90-104.87% and a maximum RSD of mere 2.71%.

Automated summary

A sensitive electrochemical sensor for the detection of cytotoxic food preservative TBHQ was developed using cupric oxide decorated amine functionalized carbon nanotubes, showing excellent detection limit, sensitivity, anti-interference, and stability. The sensor exhibited outstanding electrocatalytic activity for TBHQ detection and practical feasibility was confirmed through real sample analysis with excellent recovery and low relative standard deviation.