Artificial neural network approach to model Cr(III) and Cr(VI) adsorption by NCS, ACS and BCS

Adsorption properties of Cr(III) and Cr(VI) on natural (NCS), acid-activated (ACS) and base-activated (BCS) cherry stalks (CS) in Isparta were investigated in aqueous solutions. Batch adsorption studies had been completed with different initial chromium concentrations, pH, temperature, time and bios...

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Bibliographic Details
Published in:Applied water science 2024-02, Vol.14 (2), p.28-15, Article 28
Main Authors: Göde, Fethiye, Yılmaz, Asuman, Aktaş, A. Hakan, Pehlivan, Erol
Format: Article
Language:English
Subjects:
Adsorption
Adsorption isotherm
Adsorption kinetics
Aquatic Pollution
Aqueous solutions
Artificial neural networks
Biomass
Cherry stalks
Chromium
Comparative Law
Earth and Environmental Science
Earth Sciences
Endothermic reactions
Hydrogeology
Industrial and Production Engineering
International & Foreign Law
Isotherms
Kinetics
Nanotechnology
Neural networks
Original Article
Private International Law
Trivalent chromium
Waste Water Technology
Water Industry/Water Technologies
Water Management
Water Pollution Control
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Summary:Adsorption properties of Cr(III) and Cr(VI) on natural (NCS), acid-activated (ACS) and base-activated (BCS) cherry stalks (CS) in Isparta were investigated in aqueous solutions. Batch adsorption studies had been completed with different initial chromium concentrations, pH, temperature, time and biosorbent dosage. Adsorption rapidly approached an equilibrium state between 10 and 60 min. The results displayed that the adsorption system was suitable for pseudo-second-order kinetics. Equilibrium isotherms (Langmuir, Freundlich and Dubinin–Radushkevich) were measured experimentally. The retention characteristics of Cr(III) onto NCS, ACS and BCS and Cr(VI) onto ACS were represented by Langmuir adsorption isotherms, while Cr(VI) ions onto NCS and BCS were compatible with Freundlich adsorption isotherms. The adsorption process was endothermic accompanied by a decrease in entropy and Gibbs energy. An artificial neural network (ANN) model was improved to estimate the efficiency of Cr(III) and Cr(VI) ion’s adsorption. The ANN model can predict the behaviour of the Cr(III) and Cr(VI) ion's adsorption under different circumstances. The results have shown that NCS, ACS and BCS biosorbents open up new possibilities and potential commercial uses in the cherry stalks.
ISSN:2190-5487
2190-5495
DOI:10.1007/s13201-023-02054-6