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Biosorption of methyl orange from aqueous solution with hemp waste, investigation of isotherm, kinetic and thermodynamic studies and modeling using multigene genetic programming

Nurşah Kütük and Sibel Arslan

Faculty of Engineering, Department of Chemical Engineering, Sivas Cumhuriyet University, Sivas, Turkey

 

E-mail: nkutuk@cumhuriyet.edu.tr

Received: 7 April 2022  Accepted: 3 August 2022

Abstract:

Water resources around the world are getting polluted day by day due to the rapidly developing industry. Industrial wastes have caused serious damage to the environment in recent years. Especially, dyes are waste products that mix with waters such as lakes, rivers and seas and have toxic and carcinogenic effects. In this study, the removal of methyl orange (MO) dye, which was chosen as a model dye compound, from aqueous solution by biosorption using hemp waste was investigated. The biosorption process was optimized by the parameters of pH, initial dye concentration and amount of biosorbent. Biosorption of MO to hemp waste was investigated by isotherms, kinetics and thermodynamic studies. It was determined that the biosorption equilibrium fitted to the Langmuir isotherm (\({R}^{2}\)=0.9739). As a result of the experimental studies, 83% biosorption value and 1428 mg/g maximum biosorption capacity were reached with 250 mg/L dye concentration and 0.5 g/L biosorbent amount at pH = 2. It was determined that the reaction kinetics were in accordance with the pseudo-second-order kinetics (\({R}^{2}\)=0.9911). In addition to, the study aims to evaluate to what extent the modeling of the biosorption process is successful. For this purpose, we used multigene genetic programming (MGGP), which has been renewed with the latest developments in the field of model extraction. The results show that MGGP is efficient for modeling the biosorption process in real environments. The analysis of MGGP models also showed that pH is the most important parameter affecting the biosorption process.

Keywords: Biosorption; Hemp wastes; Methyl orange; Genetic programming; Multi-gene genetic programming

Full paper is available at www.springerlink.com.

DOI: 10.1007/s11696-022-02411-w

 

Chemical Papers 76 (12) 7357–7372 (2022)

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