Simulation Research about Signals Processing of Optic Fiber Sensor Array Sensitive to Heavy Metal Ions

2014 ◽  
Vol 915-916 ◽  
pp. 1225-1228
Author(s):  
Wei Jun Hu

Considering the approximation between Gaussian function and spectrum, Gaussian function is utilized to simulate the spectrum of optical fiber sensor array sensitive to four heavy metal ions. The division of superimposed spectrum in measurement by optical fiber sensor array and the analysis of relative error are simulated by Matlab software. From the simulation, it is known that the superposition error of spectrum caused by interference between four ions in films sensitive to heavy metal ions can be reduced with corresponding arithmetic, which provides good theoretical foundation for preparation of optical fiber sensor array and signals processing of spectrum.

2019 ◽  
Vol 11 (1) ◽  
pp. 17-20 ◽  
Author(s):  
Li Li ◽  
Bing Liu ◽  
Zhengbo Chen

In this work, we developed a facile and extensible colorimetric sensor array based on different interactions between methylene blue (MB) and single-stranded DNA (ssDNA) for the discrimination of heavy metal ions.


2018 ◽  
Vol 26 (19) ◽  
pp. 25293 ◽  
Author(s):  
Jingyi Wang ◽  
Fan Ai ◽  
Qizhen Sun ◽  
Tao Liu ◽  
Hao Li ◽  
...  

2019 ◽  
Vol 295 ◽  
pp. 110-116 ◽  
Author(s):  
Zhe Jiao ◽  
Pengfei Zhang ◽  
Hongwei Chen ◽  
Cong Li ◽  
Lina Chen ◽  
...  

2021 ◽  
Vol 11 (3) ◽  
pp. 3822-3825

We report the findings of preliminary investigation corresponding to an optical detection technique implementing smartphone as our receiver towards quantitative assessment of heavy metal ions, namely, Cu, Zn, and Ni. Using intensity modulation, the optical responses are attained through a user-friendly app. The sensing region is made up of optical fiber whose cladding portion has been etched. Subject to varying concentrations of these metal ions, the modulated responses are attained, which reveal a declining trend. The absence of traditional parts such as a spectrophotometer makes the reported scheme cost-effective as well as field-portable.


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.


2013 ◽  
Vol 780 ◽  
pp. 74-80 ◽  
Author(s):  
Liang Feng ◽  
Xiao Li ◽  
Hui Li ◽  
Wei Yang ◽  
Liang Chen ◽  
...  

Talanta ◽  
2013 ◽  
Vol 108 ◽  
pp. 103-108 ◽  
Author(s):  
Liang Feng ◽  
Hui Li ◽  
Li-Ya Niu ◽  
Ying-Shi Guan ◽  
Chun-Feng Duan ◽  
...  

2011 ◽  
Vol 11 (4) ◽  
pp. 1051-1052 ◽  
Author(s):  
Tong Chen ◽  
Mokhtar Maklad ◽  
Philip R. Swinehart ◽  
Kevin P. Chen

2016 ◽  
Author(s):  
Cong Niu ◽  
Shuqing Ma ◽  
Shuidong Xiong ◽  
Wenjie Zhang ◽  
Te Peng

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