Development of a fluorescence sensor array for the discrimination of metal ions and brands of packaged water based on gallate-modified polymer dots

2019 ◽  
Vol 11 (25) ◽  
pp. 3168-3174 ◽  
Author(s):  
Jiao Li ◽  
Hui Huang ◽  
Xue Sun ◽  
Donghui Song ◽  
Jingqi Zhao ◽  
...  

An efficient method has been found to discriminate different brands of packaged water which achieves to detect counterfeit products in the packaged water market.

2018 ◽  
Vol 10 (32) ◽  
pp. 3939-3944 ◽  
Author(s):  
Yayan Wu ◽  
Bing Wang ◽  
Kai Wang ◽  
Peng Yan

We report a simple fluorescence sensor array based on metal ions–gold nanoclusters (AuNCs) for the identification of proteins. The proposed method can also be used for bacteria sensing.


2022 ◽  
Author(s):  
Zijun Xu ◽  
Yuying Liu ◽  
Jiao Chen ◽  
Xiyuan Wang ◽  
Hao Liu ◽  
...  

Abstract As a large amount of heavy metals leaches into water sources from industrial effluents, heavy metal pollution has become an important factor affecting water quality. To enable the detection of multiple heavy metals, we constructed a pH-regulation fluorescence sensor array. Firstly, by adding a metal chelating agent as receptor, metal ions and carbon quantum dots (CDs) were connected to distinguish between Cr6+, Fe3+, Fe2+, and Hg2+ ions. Thus, the lack of affinity between the indicator functional groups and the analyte was solved. Secondly, by adjusting the pH environment of the solution system, an economical and simple array sensing platform is established, which effectively simplified the array construction. In this study, the SX-model was used in the field of fluorescence sensor array detection for metal ion recognition. Based on the strategy of stepwise prediction, combined with the classification and concentration models, the bottleneck of the unified model in previous studies was broken. This sensor array demonstrated sensitive detection of four heavy metal ions within a concentration range from 1 to 50 µM, with an accuracy of 95.45%. Moreover, it displayed the ability to efficiently identify binary mixed samples with an accuracy of 95.45%. Furthermore, metal ions in 15 real samples (lake water) were effectively discriminated with 100% accuracy. A chelating agent was used to improve the sensitivity of heavy metal ion detection and eventually led to high-precision prediction using the SX-model.


2017 ◽  
Vol 985 ◽  
pp. 175-182 ◽  
Author(s):  
Wenjie Jing ◽  
Yuexiang Lu ◽  
Guangcai Yang ◽  
Feiyang Wang ◽  
Liuying He ◽  
...  

2017 ◽  
Vol 241 ◽  
pp. 1324-1330 ◽  
Author(s):  
Zhe Wang ◽  
Chao Xu ◽  
Yuexiang Lu ◽  
Xiaotong Chen ◽  
Hang Yuan ◽  
...  

2019 ◽  
Vol 17 (3) ◽  
pp. 189-192
Author(s):  
A. Nurgain

This article presents results according to purification of water based on diatomite sorbents.The results of the study of diatomite samples from two different regions shows thatadsorption capacity, specific surface and the degree of extraction of the sorbent of Republicof Kazakhstan higher than Iranian diatomite.


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