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    An approach for prediction of optimum reaction conditions for laccase-catalyzed bio-transformation of 1-naphthol by response surface methodology (RSM)
    (Elsevier, 2008) Ceylan, Hasan; Kubilay, Şenol; Aktaş, Nahit; Şahiner, Nurettin; Ceylan, Hasan
    Response surface methodology (RSM) was successfully applied to enzymatic bio-transformation of 1-naphthol. The experiments were conducted in a closed system containing acetone and sodium acetate buffer, with laccase enzyme. Laccase enzyme used as catalyst was derived from Trametes versicolor (ATCC 200801). The enzymatic bio-transformation rate of 1-naphthol, based on measurements of initial dissolved oxygen (DO) consumption rate in the closed system, was optimized by the application of RSM. The independent variables, which had been found as the most effective variables on the initial DO consumption rate by screening experiments, were determined as medium temperature, pH and acetone content. A quadratic model was developed through RSM in terms of related independent variables to describe the DO consumption rate as the response. Based on contour plots and variance analysis, optimum operational conditions for maximizing initial DO consumption rate, while keeping acetone content at its minimum value, were 301 K of temperature, pH 6 and acetone content of 7% to obtain 9.17 · 10 3 mM DO/min for initial oxidation rate.
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    Optimization of removal conditions of copper ions from aqueous solutions by Trametes versicolor
    (Elsevier, 2010) Şahan, Tekin; Ceylan, Hasan; Şahiner, Nurettin; Aktaş, Nahit; Ceylan, Hasan
    A multi-step response surface methodology was successfully applied to optimize the biosorption conditions for the maximum removal of Cu(II) ions from aqueous solutions using Trametes versicolor fungi as a biosorbent. In the first step, the most effective medium factors, which are pH, temperature and initial Cu(II) concentration, on biosorption of Cu(II), were determined through Plackett–Burman Design. Then steepest accent followed by central composite design steps were utilized to evaluate the optimum biosorption conditions for the maximum Cu(II) ions removal. Based on the statistic analysis; the optimum conditions were obtained 5.51, 20.13 C and 60.98 mg/L as medium pH, medium temperature and initial Cu(II) concentration, respectively. Finally the analysis of variance (ANOVA) of central composite design showed the proposed quadratic model fitted experimental data very well.