A luminescent Zn(II) metal−organic framework assembled with a thiazolothiazole chromophore for sensing mainly cobalt(II) and nitrofuran antibiotics in aqueous solutions

Yong, Wei; Huang, Qi-Chen; Mu, Hong-Yao; Shi, Wen-Xin; Dai, Bao-Li; Kong, Jiao-Jiao; Chen, Xuan-Rong; Huang, Xing-Cai

doi:10.1016/j.molstruc.2023.137424

Cited by 3 publications

(1 citation statement)

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“…However, abnormal levels of these elements in the human body pose a severe threat, since it may cause distinct diseases. An excessive intake of Co 2+ can lead to serious health issues, including blindness and deafness [3]. So, it is clear the demand for the detection of trace elements.…”

Section: Introductionmentioning

confidence: 99%

Multichannel Sensor for Detection of Molybdenum Ions Based on Nitrogen-Doped Carbon Quantum Dot Ensembles

Cruz,

Souza,

de Souza

et al. 2024

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Trace elements such as cobalt (Co), molybdenum (Mo), and zinc (Zn) play necessary roles in different biological functions. Co is a microelement that influences the vascular system. Mo works as an enzymatic cofactor of three enzymes (aldehyde oxidase, sulfite oxidase, and xanthine oxidase dehydrogenase). However, these elements are difficult to detect, since the analytical methods developed have a high cost, which restrict their applicability. In this sense, fluorescent sensors are an alternative for detecting trace elements, such as Mo4+ ions. Herein, a new multichannel trace elements sensor has been proposed to detect Mo entities. In this sense, two different N-CQDs were synthesized and fully characterized. The N-CQDs presented quantum yield values of 25.93% and 6.02% and excellent solubility in water. Also, a mixture of these two carbon-based nanoparticles was used to identify and to quantify Mo in water between seven different trace elements. The method was found to reach 1.28 and 3.88 ppm for limit of detection (LOD) and quantification (LOQ), respectively. To further verify the potential of the detection platform, the multichannel sensor was applied to identify the different concentrations of metal ions (Fe2+, Co2+, Mn2+, Cu2+, Zn2+, Mg2+, and Mo4+) in water. The data matrix was treated using different algorithms, such as K-Means and Discriminant Analysis (DA). The detection strategy has successfully identified the molybdenum ions at 5 ppm. This result shows the potential application of a multichannel sensor toward the detection of Mo entities, since it is comparable with the molybdenum test already available on the market.

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Section: Introductionmentioning

confidence: 99%