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Large amount of heavy metal ions disposed in wastewater by various industries causes environmental pollution and toxicity in waste water. Many naturally available materials were used as adsorbents for the removal of heavy metal ions, but they are not effective because of low surface area. Novel nano materials are used as adsorbents in the removal of metal ions to treat potable water. In the present work nano sized large surface area (80.425 m2/g) Zinc Oxide (ZnO) was synthesized by gel combustion method and used as an adsorbent for the removal of cadmium (II) (Cd2+) from aqueous solution. The nano ZnO and Cd adsorbed ZnO were characterized by XRD, the additional Cd peaks in XRD pattern confirms the Cd adsorption. SEM analysis confirmed the adsorption of Cd2+ by change in the morphology of adsorbent. Percentage purity of the element and the presence of the Cd were characterized by EDAX. Adsorption of Cd2+ on ZnO was confirmed by varying parameters like initial concentration, pH and adsorbent dosage. Cadmium concentration in the solution was analyzed using Atomic Absorption Spectrometer (AAS). Increase in the initial concentration of Cd solution, decreases the percentage of adsorption, where as increase in the adsorbent dosage and pH of the solution increases the adsorption of Cd2+ on ZnO. Synthesized nano ZnO shows maximum of 95% Cd adsorption at lower initial concentration. Experimental data fits Langmuir and Freundlich adsorption isotherm models.

The presence of dyes in aqueous system causes aesthetic pollution, hydrolysis or other chemical reactions leading to the formation of products which are non degradable, and accumulate in water. A number of methods have been devised for degradation of dyes in aqueous streams which can cater to the never ending necessities of water worldwide. The methods include biological treatment, chemical oxidation, electrochemical decomposition, photocatalytic and chemical coagulation, physical and physico-chemical treatment. These methods are successful to a certain extent. In the present work, an attempt was made towards the sonochemical degradation of azo dyes such as methylene blue and p-nitro phenol. Further sonication experiments were carried out in combination with advanced oxidation processes. Sonication was performed at 20 and 70 kW power ratings. Percentage degradation was found to increase with increase in power ratings. Degradation of azo dyes was improved in presence UV source. Maximum degradation was observed when sonication was carried out in presence of UV source and hydrogen peroxide which was used as an oxidant. Increase in dye concentration decreased degradation rate and decrease in pH (acid medium) increased the degradation rate.

Optimization of process parameters is of critical task in developing an industrial fermentation process for various reasons. Many techniques are available for experimental design and optimization of fermentation process parameters, i.e., fermentation medium composition and conditions, each having its own advantages and disadvantages. In this work response surface methodology (RSM) with central composite design (CCD) of experiments and artificial neural network (ANN) coupled with global optimization technique (TOMLAB’s Direct Alogoritm—gblSolve) are used for optimization of process parameters for the production of alpha amylase using banana peel as the substrate and bacterial source Bacillus subtilis MTCC 441. A 46 run central composite design was used to plan the experiment with six parameters (banana peel concentration, peptone concentration, pH, temperature, incubation time and inoculum size) with five levels. The maximum amylase activity predicted by CCD and ANN is in good agreement with the experimental values at the optimized levels. The present work shows the better optimization and prediction capacity of ANN techniques compared to RSM technique.