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Intelligent simultaneous quantitative online analysis of environmental trace heavy metals with total-reflection X-ray fluorescence.

Ma J, Wang Y, Yang Q, Liu Y, Shi P - Sensors (Basel) (2015)

Bottom Line: Total-reflection X-ray fluorescence (TXRF) has achieved remarkable success with the advantages of simultaneous multi-element analysis capability, decreased background noise, no matrix effects, wide dynamic range, ease of operation, and potential of trace analysis.Besides, spectral overlapping and background effects may lead to loss of accuracy or even faulty results during practical quantitative TXRF analysis.Experimental results verify that simultaneous quantification of trace heavy metals, including Cr, Mn, Fe, Co, Ni, Cu and Zn, is realized on the online TXRF analysis platform, and both high measurement precision and computational efficiency are obtained.

View Article: PubMed Central - PubMed

Affiliation: School of Water Resources & Environment, China University of Geosciences (Beijing), Beijing 100083, China. majunjie85@gmail.com.

ABSTRACT
Total-reflection X-ray fluorescence (TXRF) has achieved remarkable success with the advantages of simultaneous multi-element analysis capability, decreased background noise, no matrix effects, wide dynamic range, ease of operation, and potential of trace analysis. Simultaneous quantitative online analysis of trace heavy metals is urgently required by dynamic environmental monitoring and management, and TXRF has potential in this application domain. However, it calls for an online analysis scheme based on TXRF as well as a robust and rapid quantification method, which have not been well explored yet. Besides, spectral overlapping and background effects may lead to loss of accuracy or even faulty results during practical quantitative TXRF analysis. This paper proposes an intelligent, multi-element quantification method according to the established online TXRF analysis platform. In the intelligent quantification method, collected characteristic curves of all existing elements and a pre-estimated background curve in the whole spectrum scope are used to approximate the measured spectrum. A novel hybrid algorithm, PSO-RBFN-SA, is designed to solve the curve-fitting problem, with offline global optimization and fast online computing. Experimental results verify that simultaneous quantification of trace heavy metals, including Cr, Mn, Fe, Co, Ni, Cu and Zn, is realized on the online TXRF analysis platform, and both high measurement precision and computational efficiency are obtained.

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Convergence curves of GA, PSO and PSO-RBFN-SA during online phase.
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sensors-15-10650-f007: Convergence curves of GA, PSO and PSO-RBFN-SA during online phase.

Mentions: Optimization capability of GA, PSO and PSO-RBFN-SA is compared in Figure 7. These algorithms are employed in the online TXRF analysis, testing the water sample referred in Figure 6. It shows that the convergence of PSO is faster than that of GA. Since the global optimization is done in the offline phase, and the local optimization is aided by SA, PSO-RBFN-SA has the best initial solution and the best final results during the online phase. It is demonstrated that the PSO-RBFN-SA algorithm promotes the optimization efficiency.


Intelligent simultaneous quantitative online analysis of environmental trace heavy metals with total-reflection X-ray fluorescence.

Ma J, Wang Y, Yang Q, Liu Y, Shi P - Sensors (Basel) (2015)

Convergence curves of GA, PSO and PSO-RBFN-SA during online phase.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481981&req=5

sensors-15-10650-f007: Convergence curves of GA, PSO and PSO-RBFN-SA during online phase.
Mentions: Optimization capability of GA, PSO and PSO-RBFN-SA is compared in Figure 7. These algorithms are employed in the online TXRF analysis, testing the water sample referred in Figure 6. It shows that the convergence of PSO is faster than that of GA. Since the global optimization is done in the offline phase, and the local optimization is aided by SA, PSO-RBFN-SA has the best initial solution and the best final results during the online phase. It is demonstrated that the PSO-RBFN-SA algorithm promotes the optimization efficiency.

Bottom Line: Total-reflection X-ray fluorescence (TXRF) has achieved remarkable success with the advantages of simultaneous multi-element analysis capability, decreased background noise, no matrix effects, wide dynamic range, ease of operation, and potential of trace analysis.Besides, spectral overlapping and background effects may lead to loss of accuracy or even faulty results during practical quantitative TXRF analysis.Experimental results verify that simultaneous quantification of trace heavy metals, including Cr, Mn, Fe, Co, Ni, Cu and Zn, is realized on the online TXRF analysis platform, and both high measurement precision and computational efficiency are obtained.

View Article: PubMed Central - PubMed

Affiliation: School of Water Resources & Environment, China University of Geosciences (Beijing), Beijing 100083, China. majunjie85@gmail.com.

ABSTRACT
Total-reflection X-ray fluorescence (TXRF) has achieved remarkable success with the advantages of simultaneous multi-element analysis capability, decreased background noise, no matrix effects, wide dynamic range, ease of operation, and potential of trace analysis. Simultaneous quantitative online analysis of trace heavy metals is urgently required by dynamic environmental monitoring and management, and TXRF has potential in this application domain. However, it calls for an online analysis scheme based on TXRF as well as a robust and rapid quantification method, which have not been well explored yet. Besides, spectral overlapping and background effects may lead to loss of accuracy or even faulty results during practical quantitative TXRF analysis. This paper proposes an intelligent, multi-element quantification method according to the established online TXRF analysis platform. In the intelligent quantification method, collected characteristic curves of all existing elements and a pre-estimated background curve in the whole spectrum scope are used to approximate the measured spectrum. A novel hybrid algorithm, PSO-RBFN-SA, is designed to solve the curve-fitting problem, with offline global optimization and fast online computing. Experimental results verify that simultaneous quantification of trace heavy metals, including Cr, Mn, Fe, Co, Ni, Cu and Zn, is realized on the online TXRF analysis platform, and both high measurement precision and computational efficiency are obtained.

Show MeSH
Related in: MedlinePlus