Recent Advances in Heterogeneous Photocatalytic Decolorization of Synthetic Dyes

Abstract

During the process and operation of the dyes, the wastes produced were commonly found to contain organic and inorganic impurities leading to risks in the ecosystem and biodiversity with the resultant impact on the environment. Improper effluent disposal in aqueous ecosystems leads to reduction of sunlight penetration which in turn diminishes photosynthetic activity, resulting in acute toxic effects on the aquatic flora/fauna and dissolved oxygen concentration. Recently, photodegradation of various synthetic dyes has been studied in terms of their absorbance and the reduction of oxygen content by changes in the concentration of the dye. The advantages that make photocatalytic techniques superior to traditional methods are the ability to remove contaminates in the range of ppb, no generation of polycyclic compounds, higher speed, and lower cost. Semiconductor metal oxides, typically TiO2, ZnO, SnO, NiO, Cu2O, Fe3O4, and also CdS have been utilized as photocatalyst for their nontoxic nature, high photosensitivity, wide band gap and high stability. Various process parameters like photocatalyst dose, pH and initial dye concentrations have been varied and highlighted. Research focused on surface modification of semiconductors and mixed oxide semiconductors by doping them with noble metals (Pt, Pd, Au, and Ag) and organic matter (C, N, Cl, and F) showed enhanced dye degradation compared to corresponding native semiconductors. This paper reviews recent advances in heterogeneous photocatalytic decolorization for the removal of synthetic dyes from water and wastewater. Thus, the main core highlighted in this paper is the critical selection of semiconductors for photocatalysis based on the chemical, physical, and selective nature of the poisoning dyes.

Photocatalytic activity of enlarged microrods of α-Bi2O3 produced using ethylenediamine-solvent

“…8(A) shows the profile of relative concentration (C/C 0 ) and the kinetic curve plot of the IC dye during its photodegradation by using α-Bi 2 O 3 microrod (0.4 g/L of BE40 sample) under UV light. The relative concentration of the IC dye decreased with the reaction time, reaching 90% of conversion at 1 h. Plotting ln(C 0 /C) versus the reaction time (t) yields a straight line, suggesting that the photodegradation reaction is adjusted to pseudo first order reaction (1st order) [1,16]. Similar results were obtained for the other samples and the estimated apparent kinetic rates (k app ) are shown in Fig.…”

“…Semiconductor materials have attracted increasing attention and interest in the past decades, mainly because they can directly convert photon energy into chemical energy upon excitation; they have wide range of applications for degradation of environmental pollutants and energy yield by photocatalytic processes [1,2]. Most of the semiconductor oxides have a narrow band gap capable to absorb visible light, so they are active to promote photocatalytic reactions, which increase their industrial applications [3].…”

Titanium Dioxide as a Catalyst Support in Heterogeneous Catalysis

“…The influences of TiO 2 support on heterogeneous catalysts affect electronic effects and bifunctional mechanism [41]. TiO 2 , as a catalyst support, enforces an electronic effect where the hypo-d-electronic Ti 3+ promotes electrocatalytic features of hyper-d-electronic noble catalyst surface atoms [42]. This, in turn, decreases the adsorption energy of CO intermediates, while enhancing the mobility of CO groups.…”

Heterogeneous sono-Fenton-like process using martite nanocatalyst prepared by high energy planetary ball milling for treatment of a textile dye

“…As a consequence, the ANN modeling as an effective method have been applied to develop a nonlinear model in various AOPs including heterogeneous and homogenous nanocatalytic processes in comparison to conventional mathematical methods owing to its simplicity for the modeling, prediction and simulation [19][20][21]. In addition, the main benefits of the neural networks are the minimum requirement for time and statistical training, ability to conduct less experiment and saving costs [22].…”