Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 6Citation - Scopus: 6Arsenic Removal From Aqueous Solutions by Ultrafiltration Assisted With Polyacrylamide: An Application of Response Surface Methodology(Taylor & Francis inc, 2015-10) Varol, Bekir; Uzal, NigmetThe present work deals with removal of arsenic from aqueous solutions by ultrafiltration assisted with polyacrylamide as an environmental friendly complexing polymer. The system performance was evaluated in relation to quality of permeate in terms of operating variables as feed concentration of arsenic ions (C-o, gL(-1)), ratio of polymer to arsenic (r, w/w), and pH of feed solution. The effect of the operating variables and maximum arsenic removal efficiency was determined by adopting design of experiments and response surface methodology under different conditions for this polymer. The experimental data were analyzed with a second order polynomial model validated by statistical analysis. Based on the response model developed, the maximum removal efficiency, close to 100%, of arsenic ions has been obtained at optimum operating parameters as C-o: 150 gL(-1), r: 2, and pH 10.Article Citation - WoS: 16Citation - Scopus: 16Arsenic Removal by the Micellar-Enhanced Ultrafiltration Using Response Surface Methodology(Iwa Publishing, 2019-12-27) Gokcek, Oznur Begum; Uzal, NigmetThe present research investigates the removal of arsenic (As) from aqueous solutions using micellar-enhanced ultrafiltration (MEUF) by utilizing two different surfactants: benzethonium chloride and dodecyl pyridinium chloride (BCl and DPCl). The impact of the operating variables and maximum removal efficiency were found under different conditions for BCl and DPCl surfactants. The maximum As rejection efficiency for MEUF with BCl and DPCl surfactants is 92.8% and 84.1%, respectively. In addition to this, a statistics-based experimental design with response surface methodology was used for the purpose of examining the impact of operating conditions, including initial pH, initial As concentration (ppb), and surfactant concentration (BCl, mM) in As-removal from aqueous solutions. In the analysis of the experimental data, a second-order polynomial model that was validated by statistical analysis for the BCl surfactant was used. On the basis of the response model created, the removal of As ions was acquired at optimum operating parameters, including the initial As concentration of 150 ppb, surfactant concentration of 5 mM and pH 10 for the BCl surfactant with 92.8% As-removal efficiency.