Curcumin Is an Iconic Ligand for Detecting Environmental Pollutants
BIOINORGANIC CHEMISTRY AND APPLICATIONS(2022)
摘要
The rapid increase in industrial revolution and the consequent environmental contamination demands continuous monitoring and sensitive detection of the pollutants. Nanomaterial-based sensing system has proved to be proficient in sensing environmental pollutants. The development of novel ligands for enhancing the sensing efficiency of nanomaterials has always been a challenge. However, the amendment of nanostructure with molecular ligand increases the sensitivity, selectivity, and analytical performance of the resulting novel sensing platform. Organic ligands are capable of increasing the adsorption efficacy, optical properties, and electrochemical properties of nanomaterials by reducing or splitting of band gap. Curcumin (diferuloylmethane) is a natural organic ligand that exhibits inherent fluorescence and electrocatalytic property. Due to keto-enol tautomerism, it is capable of giving sensitive signals such as fluorescence, luminescence, ultraviolet absorption shifts, and electrochemical data. Curcumin probes were also reported to give enhanced meterological performances, such as low detection limit, repeatability, reproducibility, high selectivity, and high storage stability when used with nanosystem. Therefore, research on curcumin-modified nanomaterials in the detection of environmental pollution needs a special focus for prototype and product development to enable practical use. Hence, this article reviews the role of curcumin as a natural fluorophore in optical and electrochemical sensing of environmentally significant pollutants. This review clearly shows that curcumin is an ideal candidate for developing and validating nanomaterials-based sensors for the detection of environmental pollutants such as arsenic, lead, mercury, boron, cyanide, fluoride, nitrophenol, trinitrotoluene, and picric acid and toxic gases such as ammonia and hydrogen chloride. This review will afford references for future studies and enable researchers to translate the lab concepts into industrial products.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要