ZnO nanoparticles are prepared through hydrolysis and condensation of zinc acetate dihydrate by potassium hydroxide in alcoholic medium at low temperatures. Thermal gravimetric analysis (TGA) of the precursor is made in order to specify the temperature range over which the weight loss and thermal effect are significant. X-ray diffraction of the as-prepared specimens shows that the hexagonal (a=3.2459 Å,c=5.1999 Å) structure is the predominant crystallographic structure. According to Scherer’s formula, the average size of the nanoparticles is 22.4 ± 0.6 nm. The structural properties of the synthesized ZnO nanoparticles have been confirmed using the TEM micrographs. The optical energy gap of the ZnO nanoparticles, as obtained from applying Tauc’s equation, is equal to 3.52 eV, which is higher than that of the bulk material. Absorption peak of the as-prepared sample is 298 nm which is highly blue shifted as compared to the bulk (360 nm). Large optical energy gap and highly blue shifted absorption edge confirm that the prepared ZnO nanoparticle exhibits strong quantum confinement effect.

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A huge amount of water is consumed in the textile industry, and the result is the production of a large amount of wastewater. The treatment of such wastewater significantly reduces the pollution load. Oxidation by nano-Fenton reactions (Fe 3+ / H 2 O 2) is a reasonable and cost-efficient process for the remediation of harmful pollutants in wastewater. In the present study, nano-hematite was applied as a source of iron in Fenton's reagent for methylene blue dye removal from wastewater. The effects of different parameters, presence of nano-hematite, hydrogen peroxide concentrations and pH, were optimized using the response surface methodology technique. A Box-Behnken design was applied, and the response (dye removal) was maximized. A maximal dye removal (81.6%) was attained when wastewater was treated at pH 2.5 in the presence of nanohematite and hydrogen peroxide in the amounts of 41 and 388 mg/L, respectively. The model is well fitted and described using the second-order polynomial equation. Moreover, the model validation showed a 97% fit between the theoretical and experimental ones.

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