Three-dimensional polymer phenylethnylcopper/nitrogen doped graphene aerogel electrode coupled with Fe3O4 NPs nanozyme: Toward sensitive and robust photoelectrochemical detection of glyphosate in agricultural matrix.

BACKGROUND: Presently, glyphosate (Gly) is the most extensively used herbicide globally, Nevertheless, its excessive usage has increased its accumulation in off-target locations, and aroused concerns for food and environmental safety. Commonly used detection methods, such as high-performance liquid chromatography and gas chromatography, have limitations due to expensive instruments, complex pre-processing steps, and inadequate sensitivity. Therefore, a facile, sensitive, and reliable Gly detection method should be developed. RESULTS: A photoelectrochemical (PEC) sensor consisting of a three-dimensional polymer phenylethnylcopper/nitrogen-doped graphene aerogel (PPhECu/3DNGA) electrode coupled with Fe3O4 NPs nanozyme was constructed for sensitive detection of Gly. The microscopic 3D network of electrodes offered fast transfer routes for photo-generated electrons and a large surface area for nanozyme loading, allowing high signal output and analytical sensitivity. Furthermore, the use of peroxidase-mimicking Fe3O4 NPs instead of natural enzyme improved the stability of the sensor against ambient temperature changes. Based on the inhibitory effect of Gly on the catalytic activity Fe3O4 NPs, the protocol achieved Gly detection in the range of 5 × 10-10 to 1 × 10-4 mol L-1. Additionally, feasibility of the detection was confirmed in real agricultural matrix including tea, maize seedlings, maize seeds and soil. SIGNIFICANCE: This work achieved facile, sensitive and reliable analysis towards Gly, and it was expected to inspire the design and utilization of 3D architectures in monitoring agricultural chemicals in food and environmental matrix.

Facile and sensitive photoelectrochemical detection of kojic acid in food products: a general strategy for immobilization-free analysis of enzyme inhibitors.

As one of the representative secondary metabolites in fermentation processes and common additives in modern industry, kojic acid (KA) has been mired in controversy in recent years due to its potential toxicity and carcinogenicity. Hence, it is of high importance to develop novel analysis strategies for KA to surveil its rational utilization and ensure public health. Based on enzyme modulated sensitization of TiO2 NPs and the inhibition effect of KA towards tyrosinase (Tyr), we report a facile and sensitive photoelectrochemical (PEC) sensor for KA in food samples. On an operational level, this protocol excluded the tedious immobilization process of traditional PEC enzyme sensors, allowing the crucial catalysis and sensitization process to take place in a small centrifuge tube, making the experimental process concise and fast. Under optimized conditions, a linear detection range of 10-7 M to 10-3 M was achieved, with a detection limit of 3.2 × 10-8 M. Furthermore, the feasibility of the strategy in food samples was validated in vinegar and wheat flour. This protocol would hold great promise for real application in diverse food products, and offer a general prototype for future immobilization-free and quick analysis of other enzyme inhibitors.

Dual-Modal Photoelectrochemical and Visualized Detection of Copper Ions.

Copper is one of the extensively utilized heavy metals in modern industry and can be easily released into the environment due to high solubility of copper ions (Cu2+). Its percolation in water and accumulation along the food chain pose a serious threat to human health. Hence, it is of great significance to explore a novel, facile, and sensitive detection method for Cu2+. Based on the intriguing photo-to-electricity conversion process of CdS QDs, as well as desirable electrochromic property of WO3 NFs, a dual-modal photoelectrochemical (PEC) and visualized detection platform for Cu2+ is fabricated. The electrochromic WO3 NFs act as a display for the Cu2+ concentration, of which the color change could be observed directly by the naked eye, while the PEC signal provides accurate data for further analysis. In this work, a sensitive detection of Cu2+ in the range of 1 × 10-5 to 5 × 10-4 M is achieved, with a detection limit of 3.2 × 10-6 M. The dual-modal analysis gives more choices for signal readouts with enhanced quantification reliability, which is adaptive for diverse application scenarios, especially for on-site investigation. This protocol offers a prototype for quick and reliable detection of the Cu2+ concentrations, and is promising for other environmental pollutants.