Optimization of Reactive Black 5 removal by adsorption process using Box–Behnken design
Suman Dutta
Abstract
Suman Dutta
Abstract
Optimization of process parameters is an important part of any process development. Maximum efficiency of any process is achievable when it runs at optimum condition. In this paper, optimization of Reactive Black 5 adsorption on TiO2 surface was carried out. Adsorption of dye depends on many process parameters like pH, adsorbent dose, initial dye concentration, and adsorption time. In this study, adsorption efficiency has been optimized based on those process parameters. Response surface methodology has been used for optimization as it has many advantages over classical optimization methods. Box–Behnken design was employed to design the experiment. For regression analysis and ANOVA study, software MINITAB 15 was used. All factors in regression equation are not equally important. Pareto analysis has been employed to find the most influential process parameters. The analysis shows that pH is the dominating factor during dye adsorption. This study confirms that more than 98% dye removal is possible at the optimum condition.
OpenAlex reports 22 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Optimization of process parameters is an important part of any process development. Maximum efficiency of any process is achievable when it runs at optimum condition. In this paper, optimization of Reactive Black 5 adsorption on TiO2 surface was carried out. Adsorption of dye depends on many process parameters like pH, adsorbent dose, initial dye concentration, and adsorption time. In this study, adsorption efficiency has been optimized based on those process parameters. Response surface methodology has been used for optimization as it has many advantages over classical optimization methods. Box–Behnken design was employed to design the experiment. For regression analysis and ANOVA study, software MINITAB 15 was used. All factors in regression equation are not equally important. Pareto analysis has been employed to find the most influential process parameters. The analysis shows that pH is the dominating factor during dye adsorption. This study confirms that more than 98% dye removal is possible at the optimum condition.
Key concepts: Box–Behnken design, Adsorption, Response surface methodology, Process (computing), Process engineering, Process optimization, Chemical engineering, Mathematics