2001
DOI: 10.1021/ci000337k
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Optimization and Empirical Modeling of HG-ICP-AES Analytical Technique through Artificial Neural Networks

Abstract: An artificial neural network technique has been applied to the optimization of a hydride generation-inductively coupled plasma-atomic emission spectrometry (HG-ICP-AES) coupling for the determination of Ge at trace levels. The back propagation of errors net architecture was used. Experimental parameters and their relationship have been studied, obtaining a surface response of the system. The results and optimization aspects achieved with the neural network approach have been compared to the "one variable at ti… Show more

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Cited by 15 publications
(6 citation statements)
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“…SIMPLEX optimization was successfully applied to find optimal conditions for CVG coupled with atomic absorption spectrometry. 26,27 Optimization and empirical modeling of CVG-ICP-OES was achieved also by Magallanes et al, 28 through Artificial Neural Networks. However, all these works were dedicated to single element optimization.…”
Section: Introductionmentioning
confidence: 97%
“…SIMPLEX optimization was successfully applied to find optimal conditions for CVG coupled with atomic absorption spectrometry. 26,27 Optimization and empirical modeling of CVG-ICP-OES was achieved also by Magallanes et al, 28 through Artificial Neural Networks. However, all these works were dedicated to single element optimization.…”
Section: Introductionmentioning
confidence: 97%
“…In spite of being multielemental techniques, there are not many papers showing the use of chemometrics that have taken into account parameters involved in analysis using ICP-MS, 28 ICP-OES 29,30 or VG-ICP-OES. [31][32][33][34] Experimental Instrumentation An Optima 3300 DV TM ICP-OES spectrometer (PerkinElmer, Norwalk, CT, USA) was used to determine noble and transition metal concentrations. The spectrometer system includes a three channel, software controlled peristaltic pump.…”
Section: Introductionmentioning
confidence: 99%
“…So detection and removal of arsenic from drinking water is very important for human health. Laboratory techniques used to detect arsenic are atomic fluorescence spectroscopy (AFS) [6], graphite furnace atomic absorption (GFAA) [7], inductively coupled plasma emission spectrophotometry (ICP-AES) [8], inductively coupled plasma mass spectroscopy (ICP-MS) [9], hydride generation atomic adsorption (HGAA) [10]. Atomic absorption spectrometry (AAS) [11], neutron activation analysis [12] etc.…”
Section: Introductionmentioning
confidence: 99%