Quantitative determination of ammonium ion in aqueous environment using riegler's solution and artificial neural network

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Abstract

A quantitative analysis has been conducted to determine the concentration of ammonium (NH4 +) ion in solution by using Ultraviolet-visible spectrophotometry method and artificial neural network (ANN). Riegler's reagent was used to form Riegler-NH4 + complex. The characterisations of Riegler's reagent in solution such as photostability, pH effect, reagent concentration, dynamic range and reproducibility were conducted. The colour change of the Riegler's reagent after reaction with NH4 + was yellow to red. The Riegler's reagent responds linearly to NH4 + ion concentration in the range of 1-7 ppm with optimum response at pH7. Satisfactory reproducibility (2.0-2.8%) were obtained with this reagent. The effect of interfering ions that may contain in the leachate on the determination of NH4 + ion was also studied. The application of ANN enabled the extension of the useful dynamic concentration range of NH4 + ion to 1-24 ppm. The best ANN architecture for Riegler-NH4 + complex was built from 29 hidden neurons, 21,389 epochs number and 0.001% learning rate which produced sum square error (SSE) value of 0.0483 with an average calibration error of 1.4136.

Original languageEnglish
Pages (from-to)1105-1113
Number of pages9
JournalSains Malaysiana
Volume40
Issue number10
Publication statusPublished - Oct 2011

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Ammonium Compounds
Ions
Neural networks
pH effects
Spectrophotometry
Network architecture
Neurons
Calibration
Color
Chemical analysis

Keywords

  • Ammonium ion
  • Artificial neural network
  • Riegler's reagent
  • Ultraviolet-visible spectrophotometry

ASJC Scopus subject areas

  • General

Cite this

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title = "Quantitative determination of ammonium ion in aqueous environment using riegler's solution and artificial neural network",
abstract = "A quantitative analysis has been conducted to determine the concentration of ammonium (NH4 +) ion in solution by using Ultraviolet-visible spectrophotometry method and artificial neural network (ANN). Riegler's reagent was used to form Riegler-NH4 + complex. The characterisations of Riegler's reagent in solution such as photostability, pH effect, reagent concentration, dynamic range and reproducibility were conducted. The colour change of the Riegler's reagent after reaction with NH4 + was yellow to red. The Riegler's reagent responds linearly to NH4 + ion concentration in the range of 1-7 ppm with optimum response at pH7. Satisfactory reproducibility (2.0-2.8{\%}) were obtained with this reagent. The effect of interfering ions that may contain in the leachate on the determination of NH4 + ion was also studied. The application of ANN enabled the extension of the useful dynamic concentration range of NH4 + ion to 1-24 ppm. The best ANN architecture for Riegler-NH4 + complex was built from 29 hidden neurons, 21,389 epochs number and 0.001{\%} learning rate which produced sum square error (SSE) value of 0.0483 with an average calibration error of 1.4136.",
keywords = "Ammonium ion, Artificial neural network, Riegler's reagent, Ultraviolet-visible spectrophotometry",
author = "{Tan @ Chong}, {Ling Ling} and Musa Ahmad and Lee, {Yook Heng}",
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AU - Ahmad, Musa

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N2 - A quantitative analysis has been conducted to determine the concentration of ammonium (NH4 +) ion in solution by using Ultraviolet-visible spectrophotometry method and artificial neural network (ANN). Riegler's reagent was used to form Riegler-NH4 + complex. The characterisations of Riegler's reagent in solution such as photostability, pH effect, reagent concentration, dynamic range and reproducibility were conducted. The colour change of the Riegler's reagent after reaction with NH4 + was yellow to red. The Riegler's reagent responds linearly to NH4 + ion concentration in the range of 1-7 ppm with optimum response at pH7. Satisfactory reproducibility (2.0-2.8%) were obtained with this reagent. The effect of interfering ions that may contain in the leachate on the determination of NH4 + ion was also studied. The application of ANN enabled the extension of the useful dynamic concentration range of NH4 + ion to 1-24 ppm. The best ANN architecture for Riegler-NH4 + complex was built from 29 hidden neurons, 21,389 epochs number and 0.001% learning rate which produced sum square error (SSE) value of 0.0483 with an average calibration error of 1.4136.

AB - A quantitative analysis has been conducted to determine the concentration of ammonium (NH4 +) ion in solution by using Ultraviolet-visible spectrophotometry method and artificial neural network (ANN). Riegler's reagent was used to form Riegler-NH4 + complex. The characterisations of Riegler's reagent in solution such as photostability, pH effect, reagent concentration, dynamic range and reproducibility were conducted. The colour change of the Riegler's reagent after reaction with NH4 + was yellow to red. The Riegler's reagent responds linearly to NH4 + ion concentration in the range of 1-7 ppm with optimum response at pH7. Satisfactory reproducibility (2.0-2.8%) were obtained with this reagent. The effect of interfering ions that may contain in the leachate on the determination of NH4 + ion was also studied. The application of ANN enabled the extension of the useful dynamic concentration range of NH4 + ion to 1-24 ppm. The best ANN architecture for Riegler-NH4 + complex was built from 29 hidden neurons, 21,389 epochs number and 0.001% learning rate which produced sum square error (SSE) value of 0.0483 with an average calibration error of 1.4136.

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KW - Ultraviolet-visible spectrophotometry

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