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Intelligent potentiostat for identification of heavy metals in situ
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10.1063/1.2165570
/content/aip/journal/rsi/77/1/10.1063/1.2165570
http://aip.metastore.ingenta.com/content/aip/journal/rsi/77/1/10.1063/1.2165570

Figures

Image of FIG. 1.
FIG. 1.

(a) Preconcentration and stripping phases of the analysis; (b) excitation signal using differential pulse anodic stripping voltammetry.

Image of FIG. 2.
FIG. 2.

Schematic diagram of the electrochemical instrumentation system.

Image of FIG. 3.
FIG. 3.

Two-space scatter diagram representing the amplitude of peak current vs oxidation potential for two heavy metals.

Image of FIG. 4.
FIG. 4.

Neural network with three layers of neurons.

Image of FIG. 5.
FIG. 5.

Flow chart of the operation of the electrochemical instrument for identification of heavy metals.

Image of FIG. 6.
FIG. 6.

Amplitude peak vs oxidation potential for the six different metals.

Image of FIG. 7.
FIG. 7.

Configuration of the neural network.

Image of FIG. 8.
FIG. 8.

Training error during neural network training.

Tables

Generic image for table
Table I.

Probability of classification.

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/content/aip/journal/rsi/77/1/10.1063/1.2165570
2006-01-25
2014-04-23
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Intelligent potentiostat for identification of heavy metals in situ
http://aip.metastore.ingenta.com/content/aip/journal/rsi/77/1/10.1063/1.2165570
10.1063/1.2165570
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