Regression model, artificial neural network, and cost estimation for biosorption of Ni(II)-ions from aqueous solutions by Potamogeton pectinatus

Manal Fawzy, Mahmoud Nasr, Samar Adel, Shacker Helmi

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This study investigated the application of Potamogeton pectinatus for Ni(II)-ions biosorption from aqueous solutions. FTIR spectra showed that the functional groups of –OH, C–H, –C = O, and –COO– could form an organometallic complex with Ni(II)-ions on the biomaterial surface. SEM/EDX analysis indicated that the voids on the biosorbent surface were blocked due to Ni(II)-ions uptake via an ion exchange mechanism. For Ni(II)-ions of 50 mg/L, the adsorption efficiency recorded 63.4% at pH: 5, biosorbent dosage: 10 g/L, and particle-diameter: 0.125–0.25 mm within 180 minutes. A quadratic model depicted that the plot of removal efficiency against pH or contact time caused quadratic-linear concave up curves, whereas the curve of initial Ni(II)-ions was quadratic-linear convex down. Artificial neural network with a structure of 5–6–1 was able to predict the adsorption efficiency (R2: 0.967). The relative importance of inputs was: initial Ni(II)-ions > pH > contact time > biosorbent dosage > particle-size. Freundlich isotherm described well the adsorption mechanism (R2: 0.974), which indicated a multilayer adsorption onto energetically heterogeneous surfaces. The net cost of using P. pectinatus for the removal of Ni(II)-ions (4.25 ± 1.26 mg/L) from real industrial effluents within 30 minutes was 3.4 $USD/m3.

Original languageEnglish
Pages (from-to)321-329
Number of pages9
JournalInternational Journal of Phytoremediation
Volume20
Issue number4
DOIs
Publication statusPublished - 21 Mar 2018

Fingerprint

Stuckenia pectinata
biosorption
Biosorption
artificial neural network
neural networks
aqueous solutions
aqueous solution
Ions
ions
Neural networks
ion
adsorption
cost
Costs
Adsorption
industrial effluents
biocompatible materials
ion transport
ion exchange
dosage

Keywords

  • Agro-based sorbent
  • Ni(II)-ions biosorption
  • Statistical and intelligence models

ASJC Scopus subject areas

  • Environmental Chemistry
  • Pollution
  • Plant Science

Cite this

Regression model, artificial neural network, and cost estimation for biosorption of Ni(II)-ions from aqueous solutions by Potamogeton pectinatus. / Fawzy, Manal; Nasr, Mahmoud; Adel, Samar; Helmi, Shacker.

In: International Journal of Phytoremediation, Vol. 20, No. 4, 21.03.2018, p. 321-329.

Research output: Contribution to journalArticle

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