Optical and photocatalytic properties of the Fe-doped TiO2 nanoparticles loaded on the activated carbon

In this work, Fe-doped (1?wt%) TiO₂ loaded on the activated carbon nano-composite was prepared using a sol-gel method. A prepared nano-composite was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), BET surface area, Fourier transform infrared spectroscopy (FTIR), photoluminescence (PL) spectroscopy and UV–Vis diffuse reflectance spectroscopy (DRS). The photocatalytic activity of the nano-composite was evaluated through degradation of synthetic textile wastewater, reactive red 198, under visible light irradiations. The XRD result indicated that the TiO₂ nano-composite contained only anatase phase. The surface area of the TiO₂ increased from 48?m²/g to 100?m²/g through the fabrication of the nano-composite. The FE-SEM results indicate that the TiO₂ particles with an average particle size of 35–70?nm can be deposited homogeneously on the activated carbon surface. DRS showed that the Fe doping in the TiO₂ -activated carbon nano-composite induced a significant red shift of the absorption edge and then the band gap energy decreased from 3.3 to 2.9?eV. Photocatalytic results indicated that the photocatalytic activity of the Fe doped TiO₂ increased under visible light irradiation in the presence of the activated carbon.     

Fe2MoO4 magnetic nanocomposite modified screen printed graphite electrode as a voltammetric sensor for simultaneous determination of nalbuphine and diclofenac

Journal of Materials Science: Materials in Electronics - This study applied screen printed graphite electrode (SPGE) modified with the Fe2MoO4 magnetic nanocomposite for simultaneously determining...     

Oxidation of Methylene via Sn-adsorbed Boron Nitride Nanocage (B30N30): DFT Investigation

Silicon - In this study, by using of density functional theory calculations, the oxidation of methylene on surface of Tin-doped boron nitride nanocage via Langmuir Hinshelwood and Eley Rideal...     

Exergy analysis and multiobjective optimization of a biomass gasification based multigeneration system

Biomass gasification is a process of converting biomass to a combustible gas suitable for use in boilers, engines and turbines to produce combined cooling, heat and power. This paper presents a detailed model of a biomass gasification system and designs a multigeneration energy system which uses the biomass gasification process for generating combined cooling, heat and electricity. Energy and exergy analyses are first applied to evaluate the performance of the designed system. Next, minimizing total cost rate and maximizing exergy efficiency of the system are considered as two objective functions and a multiobjective optimization approach based on differential evolution algorithm and local unimodal sampling technique is developed to calculate the optimal values of the multigeneration system parameters. A parametric study is then carried out and Pareto front curve is used to determine the trend of objective functions and assess the performance of the system. Furthermore, a sensitivity analysis is employed to evaluate effects of design parameters on the objective functions. Simulation results are compared with two other multiobjective optimization algorithms and effectiveness of the proposed method is verified using various performance indicators.