Investigation the effect of adding graphene oxide into diesel/higher alcohols blends on a diesel engine performance

ABSTRACT

This article aims to study the influence of the addition of graphene oxide nanoparticles (GO) to diesel/higher alcohols blends on the combustion, emission, and exergy parameters of a CI engine under various engine loads. The higher alcohols mainly n-butanol, n-heptanol, and n-octanol are blended with diesel at a volume fraction of 50%. Then, the 25 and 50 mg/L concentrations of GO are dispersed into diesel/higher alcohols blends using an ultrasonicator. The GO structures are examined using TEM, TGA, XRD and FTIR. The findings show that there is a reduction in p_max. and HRR when adding higher alcohols with diesel fuel. Regarding engine emission, there is a significant improvement in emissions formation with adding higher alcohols. The addition of GO into diesel/higher alcohols blends improves the brake thermal efficiency by 15%. Moreover, the p_max. and HRR are both enhanced by 4%. The CO, UHC and smoke formation are reduced considerably by 40%, 50 and 20%, respectively, while NO_x level is increased by 30% with adding GO. Finally, adding high percentages of n-butanol, n-heptanol, and n-octanol with diesel fuel with the presence of GO has the potential to achieve ultra-low CO, UHC, and smoke formation meanwhile keeping high thermal efficiency level.     

Synthesis of TiO2 nanoparticles in different thermal conditions and modeling its photocatalytic activity with artificial neural network

Titanium dioxide (TiO₂) nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitrophenol (4-NP). All catalysts were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM). An artificial neural network model (ANN) was developed to predict the photocatalytic removal of 4-NP in the presence of TiO₂ nanoparticles prepared under desired conditions. The comparison between the predicted results by designed ANN model and the experimental data proved that modeling of the removal process of 4-NP using artificial neural network was a precise method to predict the extent of 4-NP removal under different conditions.     

Wetting mechanism and morphological adaptation; leaf rolling enhancing atmospheric water acquisition in wheat crop—a review

Environmental Science and Pollution Research - Several plant species such as grasses are dominant in many habitats including arid and semi-arid areas. These species survive in these regions by...     

Gaseous and particulate emissions from thermal power plants operating on different technologies

This paper presents the assessment of gaseous and particulate emissions from thermal power plants operating on different combustion technologies. Four thermal power plants operating on heavy furnace oil were selected for the study, among which three were based on diesel engine technology, while the fourth plant was based on oil-fired steam turbine technology. The stack emissions were monitored for critical air pollutants carbon monoxide, carbon dioxide, oxides of nitrogen, sulfur dioxide, particulate matter, lead, and mercury. The pollutant emissions were measured at optimum load conditions for a period of 6 months with an interval of 1 month. The results of stack emissions were compared with National Environmental Quality Standards of Pakistan and World Bank guidelines for thermal power plants, and few parameters were found higher than the permissible limits of emissions. It was observed that the emissions carbon monoxide, oxides of nitrogen, and particulate matters from diesel engine-based power plants were comparatively higher than the turbine-based power plants. The emissions of sulfur dioxide were high in all the plants, even the plants with different technologies, which was mainly due to high sulfur contents in fuel.     

Bioleaching of heavy metals from sewage sludge,direct action of Acidithiobacillus ferrooxidans or only the impact of pH?

Journal of Material Cycles and Waste Management - The bioleaching process comprises two mechanisms: direct action of the bacteria and indirect effect of low pH. In this work, the effect of bacteria...     

Production and Purification of Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Degrading Enzyme from Streptomyces sp. AF-111

A poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) degrading bacterial strain designated as AF-111 was isolated from sewage sludge sample. The bacterium was identified by 16S rRNA gene sequencing. The results revealed that strain AF-111 showed 99 % similarity with Streptomyces althioticus strain NRRL B-3981 and designated as Streptomyces sp. strain AF-111. An extracellular PHBV depolymerase enzyme was produced under optimized conditions and purified through ammonium sulphate fractionation and column chromatography. The enzyme was purified to homogeneity, indicated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis and molecular weight was found to be approximately 51 kDa. Effect of temperature, pH, metal ions and inhibitors on the PHBV depolymerase activity was determined. The enzyme was stable at wide range of temperature (35–55 °C) and pH (6–8). PHBV depolymerase was stable in the presence of different metal ions except iron and zinc which had inhibitory effect on depolymerase activity. Both ethylenediamine teteracetic acid and phenylmethyl sulphonyl fluoride strongly inhibited enzyme activity which indicates that this enzyme belongs to the serine hydrolase family like other polyhydroxyalkanoate depolymerases. The results show that a depolymerase from strain AF-111 can effectively degrade PHBV, therefore, it can be applied in the process of biochemical monomer recycling.