Removal of cationic dyes from aqueous solutions using microspherical particles of fly ash.

Batch sorption experiments were carried out for the removal of cationic dyes (methylene blue and malachite green) from their aqueous solutions using sorbent made from fly ash-a waste material. Effects of various experimental parameters: initial dye concentration, contact time, pH, adsorbent dosage, solution temperature, surfactant addition and ionic strength on the fly ash sorption of dyes were evaluated. The isothermal data for sorption followed the Langmuir model. The maximum sorption capacity obtained for methylene blue and malachite green was 36.05 mg/g and 40.65 mg/g, respectively. Kinetic studies indicate that sorption on fly ash follows the pseudo-second order kinetics. Present research suggests that fly ash could be an appropriate adsorbent for the removal of basic dyes from aqueous solutions.

Application of response surface methodology and artificial neural network methods in modelling and optimization of biosorption process.

A review on the application of response surface methodology (RSM) and artificial neural networks (ANN) in biosorption modelling and optimization is presented. The theoretical background of the discussed methods with the application procedure is explained. The paper describes most frequently used experimental designs, concerning their limitations and typical applications. The paper also presents ways to determine the accuracy and the significance of model fitting for both methodologies described herein. Furthermore, recent references on biosorption modelling and optimization with the use of RSM and the ANN approach are shown. Special attention was paid to the selection of factors and responses, as well as to statistical analysis of the modelling results.