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Wastewater containing dye is usually treated by physical, chemical or biological treatment processes. Adsorption process is one of the effective and efficient techniques that have been successfully employed for colour removal from wastewater. The aim of the present study is to remove methylene mlue (MB) dye from its aqueous solution using Grevillea robusta silver nanoparticles (GR-Ag-NPs) as adsorbent. The variables covered were contact time, solution pH, adsorbent dosage, initial dye concentration and temperature. The adsorbents were characterised by using scanning electron microscopy (SEM), for its surface functional groups using Fourier Transform Infrared Spectroscopy (FTIR); furthermore response surface methodology (RSM) was adopted to study the correlations among the process variables affecting the process and to optimise the process to give higher % dye removal. [ABSTRACT FROM AUTHOR]

The goal of this research was to employ copper-doped zinc oxide nanoparticles (Cu/ZnONPs) as an adsorbent to remove the potentially toxic azo dye Congo red (CR). The Cu/ZnONPs were made using a chemical coprecipitation method, and their characteristics were examined using XRD, SEM, EDS, and FTIR methods. The response surface methodology (RSM) central composite design (CCD) is used to optimize the operational parameters' agitation time, adsorbent dosage, solution pH, and initial concentration of CR solution during the adsorption process. The agitation period of 29.48 min, the Cu/ZnONP dosage of 0.301 g/L, the solution pH of 6.96, and the CR initial concentration of 90 mg/L resulted in a maximum CR adsorption of 94.14% and a desirability of 0.976. The kinetic findings fit the pseudo-second-order kinetic equation, and the equilibrium data agreed with the Langmuir isotherm (maximum uptake capacity qmax = 250 mg/g). During the thermodynamic experiments, endothermic, spontaneous, and physical adsorptions were observed. [ABSTRACT FROM AUTHOR]

Cadmium biosorption capacity of the biosorbent prepared from Gelidiella acerosa (brown algae) from synthetic cadmium solutions at optimum process conditions was investigated. The surface functional groups of the biosorbent responsible for biosorption were identified using FTIR analysis and the surface texture and porosity of the biosorbent was analyzed by SEM analysis. Response surface methodology (RSM) and artificial neural network (ANN) combined with central composite design (CCD) were used for modeling and optimization of biosorption and to study interaction effects of the three effective process variables such as solution pH, initial cadmium ion concentration and biosorbent dosage. Prediction capacities of RSM and ANN were compared and found that RSM showed better prediction performance than ANN. Kinetic data were well fitted to second order rate equation showing maximum biosorption capacity of 21.73 mg/g for 100 mg/l metal solution concentration. It was further confirmed by fitting the data to Elovich model. Biosorption mechanism was investigated using Intra-particle diffusion and Boyd models. The optimum cadmium removal efficiency of the biosorbent was found as 90.25%. [ABSTRACT FROM AUTHOR]