A bisspiropyran fluorescent probe for the selective and rapid detection of cyanide anion in liqueurs

Zhou, Ziqiang; Hu, Hongzhi; Xia, Ling; Li, Gongke; Xiao, Xiaohua

doi:10.1039/d1nj05773a

Cited by 5 publications

(1 citation statement)

References 40 publications

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“…Although there are several natural sources of cyanide in nature, the primary source of cyanide in water resources is industrial wastewater [24]. Besides, as a lethal contaminant, cyanide is a critical criterion in maintaining water safety [25]. Affordability, ease of access, immediate impact, effectiveness even at low concentrations ([CN − ] > 70 µg L −1 ), no physical traces (like color, odor, or turbidity), and the possibility of contamination by industries, such as metal plating, makes cyanide a potential terroristic threat [26].…”

Section: Millionsmentioning

confidence: 99%

A Sustainable Decision Support System for Drinking Water Systems: Resiliency Improvement against Cyanide Contamination

et al. 2022

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Maintaining drinking water quality is considered important in building sustainable cities and societies. On the other hand, water insecurity is an obstacle to achieving sustainable development goals based on the issues of threatening human health and well-being and global peace. One of the dangers threatening water sources is cyanide contamination due to industrial wastewater leakage or sabotage. The present study investigates and provides potential strategies to remove cyanide contamination by chlorination. In this regard, the main novelty is to propose a sustainable decision support system for the dirking water system in a case study in Iran. First, three scenarios have been defined with low ([CN−] = 2.5 mg L−1), medium ([CN−] = 5 mg L−1), and high ([CN−] = 7.5 mg L−1) levels of contamination. Then, the optimal chlorine dosage has been suggested as 2.9 mg L−1, 4.7 mg L−1, and 6.1 mg L−1, respectively, for these three scenarios. In the next step, the residual cyanide was modelled with mathematical approaches, which revealed that the Gaussian distribution has the best performance accordingly. The main methodology was developing a hybrid approach based on the Gaussian model and the genetic algorithm. The outcomes of statistical evaluations illustrated that both injected chlorine and initial cyanide load have the greatest effects on residual cyanide ions. Finally, the proposed hybrid algorithm is characterized by the multilayer perceptron algorithm, which can forecast residual cyanide anion with a regression coefficient greater than 0.99 as a soft sensor. The output can demonstrate a strong positive relationship between residual cyanide- (RCN−) and injected chlorine. The main finding is that the proposed sustainable decision support system with our hybrid algorithm improves the resiliency levels of the considered drinking water system against cyanide treatments.

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Section: Millionsmentioning

confidence: 99%