Sonochemical/hydration-dehydration synthesis of Pt-TiO2 NPs/decorated carbon nanotubes with enhanced photocatalytic hydrogen production activity

Modified Pt-TiO2 NPs/decorated carbon nanotubes were synthesized utilizing sonochemical/hydration-dehydration techniques. Pt was loaded on TiO2 by a photodeposition method keeping in mind the end goal to achieve electron-hole pair separation and promote the surface reaction. The morphological and basic properties of Pt-TiO2/fCNTs were investigated by field emission scanning electron microscopy (FESEM), high resolution transmission electron microscopy (HRTEM), powder X-ray diffraction (XRD), UV-vis diffuse reflectance spectroscopy (DRS), photoluminescence (PL) and Raman spectroscopy. The selected area electron diffraction (SAED) patterns of Pt-TiO2/fCNTs were obtained utilizing TEM-based energy dispersive X-ray spectroscopy (EDXS) analysis. It was found that the TiO2 nanoparticles were uniformly distributed on the fCNTs, and the Pt particles were decorated on the surface of TiO2/fCNTs. The photocatalytic hydrogen production activity of the Pt(0.5%)-TiO2/fCNTs(0.5%) nanoparticle composites was investigated using a sacrificial agent methanol solution. Pt-loaded TiO2 demonstrated a hydrogen evolution rate around 20 times that of TiO2/fCNTs(0.5%) (fSWCNTs, fMWCNTs). When compared with platinized TiO2 in methanol, which was utilized as a control material, Pt-TiO2/fCNTs demonstrated an almost 2-fold increment in hydrogen generation

Synthesis, Characterization and Photodegradation Studies of Copper Oxide–Graphene Nanocomposites

In this work, a simple hydrothermal method was employed to prepare a pristine sample of copper oxide (CuO) and three samples of copper oxide–graphene nanocomposites (CuO-xG) with x = 2.5, 5, and 10 mg of graphene. The synthesized samples were characterized using X-ray powder diffractometry (XRD), field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR) and ultraviolet–visible (UV-Vis) spectroscopy. The XRD patterns of CuO-xG nanocomposites exhibited the diffraction peaks related to the crystal planes of monoclinic CuO and hexagonal graphite. The surface morphology of the prepared samples was investigated using FESEM images. EDX analysis was used to investigate the chemical composition of the synthesized samples. FTIR spectroscopy identified the vibrational modes of the covalent bonds present in the samples. The allowed direct optical bandgap energy was calculated for all prepared samples using UV-Vis absorption spectra. The small bandgap of CuO-xG nanocomposites indicates their potential use as an effective photocatalyst in the presence of visible light. Photocatalytic activity of the samples was explored for the degradation of methylene blue (MB) dye contaminant under visible light irradiation. The results showed that the CuO-5G sample has the highest photodegradation efficiency (~56%)

Systematic investigation of two-phase flow in special channels

A systematic study of two-phase (water-air) currents in open channels (water-air) has been conducted by means of experiments and numerical simulations. A dedicated device has been designed and manufactured on purpose. The numerical simulations have been based on the solution of a system of mass, momentum and energy balance equations for a two-phase fluid. The effect of different influential parameters has been explored, namely, velocity and dimensions of the channel, surface pressure and tensio

Preperation of sodium alginate-based SA-g-poly(ITA-co-VBS)/RC hydrogel nanocomposites: And their application towards dye adsorption

A superabsorbent polymer, Sodium Alginate-g-Poly (Itaconic acid-co-Sodium 4-vinyl benzenesulfonate)/ Ricinus communis (SA-g-P(ITA-co-VBS)/ RC) hydrogel, was prepared by free-radical graft co-polymerization for sequestration of toxic malachite green (MG) dye as a cationic dye model. The surface morphological of shape and composition of the prepared hydrogel used have been characterized by FESEM, EDX, TEM, FTIR, X-ray diffraction XRD, and TGA. Optimizing the synthesis conditions for prepared a hydrogel with the highest swelling ratio have been studied, the results show that employing 0.08 g KPS and 0.09 g MBA, 1.0 g ITA, 2.0 g VBS, 1.0 g SA, and 1.0 g RC, the composites greatest swelling capacity in distilled water was 3400 %. It was discovered that the dye adsorption capacity of the polymer was greatly impacted by the monomer VBS level in the hydrogel, which gives it a better ability to swell. The porosity of the hydrogel spheres, thus significantly enhancing the MG adsorption capacity with the rate-limiting controlled by chemical adsorption, intraparticle diffusion, and film diffusion. Study the influence of different reaction conditions on the removal of MG dye from aqueous solution are adsorbent dose, pH, zero-point charge, temperature, thermodynamic adsorption, adsorption isotherm, and kinetic models have been done. Additionally, (SA-g-P(ITA-co-VBS)/RC) demonstrated strong MG dye adsorption capabilities and reusability in at least four adsorption-desorption cycles this process indicating its considerable potential for use as the adsorbent for dye removals from aqueous solution

Developed teamwork optimizer for model parameter estimation of the proton exchange membrane fuel cell

This paper proposes a new optimal methodology for model parameters estimation of the Proton Exchange Membrane Fuel Cell. The main purpose here is to design a newly developed metaheuristic technique to deliver a model with higher accuracy. In this study, we utilized two modifications for the Teamwork Optimizer to get higher accuracy. The two modifiers are opposition-based learning and chaotic mechanism. The results show that using the opposition-based learning, the population diversity has been kept, owing to the greater population size due to the solution space, and using the Chaos theory, the population diversity has been increased. This is proved by applying the Improved Teamwork Optimizer to minimize the Root Mean Square Error and Integral Absolute Error between the suggested model and empirical data. The validation has been done by applying the proposed Improved Teamwork Optimizer to two studied cases, which are Nexa Proton Exchange Membrane Fuel Cell and NedSstack PS6 Proton Exchange Membrane Fuel Cell, and comparing it with other published works. Simulation results showed that the proposed method with 1.14 Integral Absolute Error and 0.21 Root Mean Square Error for NedSstack PS6 Proton Exchange Membrane Fuel Cells and with 12 Integral Absolute Error and 0.17 Root Mean Square Error for Nexa Proton Exchange Membrane Fuel Cells provides the minimum error value among the other optimization techniques. This shows the higher potential of the proposed method for use as the parameter estimator for Proton Exchange Membrane Fuel Cells