Regression model, artificial intelligence, and cost estimation for phosphate adsorption using encapsulated nanoscale zero-valent iron

Ahmed S. Mahmoud, Mohamed K. Mostafa, Mahmoud Nasr

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This study investigated the adsorption of PO4 3− onto encapsulated nanoscale zero-valent iron (nZVI). At initial PO4 3–: 10 mg · L−1, the optimum condition was initial pH: 6.5, nZVI dosage: 20 g · L−1, stirring-rate: 100 rpm, and time: 30 min, achieving PO4 3− removal of 42%. The effect of pH and time on the PO4 3− removal efficiency was quadratic-linear concave up, whereas the curve of nZVI dosage was quadratic-convex. Artificial neural network with a structure of 5−7−1 adequately predicted PO4 3− removal (R2: 97.6%), and the sensitivity analysis demonstrated that pH was the most influential input. The cost of the adsorption unit was 3.15 $USD · m−3.

Original languageEnglish
JournalSeparation Science and Technology (Philadelphia)
DOIs
Publication statusAccepted/In press - 1 Jan 2018

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Keywords

  • Artificial neural network
  • cost analysis
  • nZVI/Ca-beads
  • phosphate adsorption
  • response surface methodology

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Process Chemistry and Technology
  • Filtration and Separation

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