Chiang Mai Journal of Science

Print ISSN: 0125-2526 | eISSN : 2465-3845

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Utilization of (Modified-) Ground Hazelnut Shells for Adsorption of Azo-metal Toxic Dyes: Empirical and ANFIS Modeling and Optimization

Musa Buyukada, Sibel Uzuner and Fatih Evrendilek
* Author for corresponding; e-mail address: musabuyukada@ibu.edu.tr
Volume: Vol.45 No.1 (January 2018)
Research Article
DOI:
Received: 27 December 2016, Revised: -, Accepted: 21 Febuary 2017, Published: -

Citation: Buyukada M., Uzuner S. and Evrendilek F., Utilization of (Modified-) Ground Hazelnut Shells for Adsorption of Azo-metal Toxic Dyes: Empirical and ANFIS Modeling and Optimization, Chiang Mai Journal of Science, 2018; 45(1): 342-354.

Abstract

Identification of both significantly influential predictors by Plackett-Burman and their interaction terms by Box-Behnken was carried out to quantify color removal efficiency of chemically modified ground hazelnut shells as a novel adsorbent for two common  textile dyes of Procion blue H-EGN 125 (PB) and Sandolan brilliant red N-BG 125 (SBR). Color removal efficiency mechanism was characterized using a Fourier transform infra-red spectrometer, an X-ray diffractometer, a scanning electron microscopy-energy dispersive spectroscopy. Multiple (non-)linear regression (M(N)LR) models and adaptive neuro fuzzy inference systems (ANFIS) were comparatively used to model color removal efficiency.  The dilute acid treatment led to the maximum biosorption capacities (qmax) of 59.67 mgืg-1 for PB and 63.62 mgืg-1 for SBR. Additionally, the maximum color removal efficiency of 98.6% for PB and 99.7% for SBR was achieved under 50 ฐC, 10 mgืL-1  IDC, 5 g BA, and  90 min RT. Futhermore, the minimum color removal efficiency of 13.5% for PB and 15.2% for SBR was obtained under 25 ฐC, 50 mgืL-1  IDC, 1 g BA, and 30 min RT. Independent validation results showed that the best-fit MNLR and ANFIS models performed similarly. Adsorption mechanism of both dyes were described by Freundlich isotherm better than the other models. 

Keywords: Hazelnut shell, ANFIS, Box-Behnken design, Data-driven modeling, Plackett-Burman design

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