Next Article in Journal
Classifying Step and Spin Turns Using Wireless Gyroscopes and Implications for Fall Risk Assessments
Previous Article in Journal
Collaborative Localization and Location Verification in WSNs
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(5), 10650-10675; doi:10.3390/s150510650

Intelligent Simultaneous Quantitative Online Analysis of Environmental Trace Heavy Metals with Total-Reflection X-Ray Fluorescence

1
,
1,2,†
,
1,†,* , 3
and
3
1
School of Water Resources & Environment, China University of Geosciences (Beijing), Beijing 100083, China
2
China National Environmental Monitoring Centre, Beijing 100012, China
3
Yiwen Environmental Science Technology Co., Ltd, Guangzhou 510730, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 16 March 2015 / Revised: 20 April 2015 / Accepted: 30 April 2015 / Published: 6 May 2015
(This article belongs to the Section Chemical Sensors)
View Full-Text   |   Download PDF [1606 KB, uploaded 6 May 2015]   |  

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. View Full-Text
Keywords: total-reflection X-ray fluorescence; on-line analysis; quantitative determination; particle swarm optimization; radial basis function network; simulated annealing total-reflection X-ray fluorescence; on-line analysis; quantitative determination; particle swarm optimization; radial basis function network; simulated annealing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ma, J.; Wang, Y.; Yang, Q.; Liu, Y.; Shi, P. Intelligent Simultaneous Quantitative Online Analysis of Environmental Trace Heavy Metals with Total-Reflection X-Ray Fluorescence. Sensors 2015, 15, 10650-10675.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top