Novel adsorbent for malachite green from okra stalks waste: synthesis, kinetics and equilibrium studies.

In this study, malachite green (MG) removal was performed with activated carbon synthesized from okra stalks by microwave assisted chemical activation method. In the synthesis of activated carbon, the effects of gas in the microwave, activation, and impregnation rate were investigated. The synthesized activated carbon characterization was investigated using BET, FT-IR, and SEM analyses. The activated carbon surface area achieved was 759.453 m2 g-1. In addition, the surface area of activated carbon synthesized using the conventional method was17.766 m2 g-1. The effect of the initial solution concentration on MG adsorption was investigated. According to the kinetic and equilibrium data, it was found that the adsorption process best fitted the pseudo-second order kinetic model and the Langmuir isotherm. According to the equilibrium data, the maximum adsorption capacity (qmax) of the monolayer was 119.05 mg g-1. In addition, MG adsorption was investigated by the experimental design method. The adsorption capacity at the determined optimum conditions was 99.63 mg g-1. All results show that activated carbon synthesized from waste biomass by combining the conventional method with microwave-assisted impregnation is a cheap and environmentally friendly adsorbent.

The synthesis of activated carbon from waste biomass using the conventional activation method is quite common. Activated carbon synthesis studies have increased in recent years with microwave-assisted impregnation, which has been integrated into the conventional activation method. Using this new method, the synthesis of activated carbon from okra stalk waste was carried out for the first time in this study. In addition, with this novel adsorbent, malachite green was removed from the aqueous solutions for the first time.

Biohydrogen Production from Waste Black Cumin (Nigella Sativa) Extract Liquid.

Hydrogen creates water during combustion. Therefore, it is expected to be the most promising environmentally friendly energy alternative in the coming years. This study used extract liquid obtained from the waste nigella sativa generated by the black cumin oil industry. The performance of biological hydrogen manufacturing via dark fermentation was investigated in the fluidized bed reactor (FBR) and completely stirred tank reactor (CSTR) under the operation conditions of pH 5.0, 4.0, and 6.0 and a hydraulic retention time (HRT) of 36 and 24 h. The performance of hydrogen manufacturing was determined to be good under an organic loading ratio (OLR) of 6.66 g.nigella sativa extract/L and pH 4.0. According to these conditions, the maximum amount of hydrogen in CSTR and FBR was found to be 20.8 and 7.6 mL H2/day, respectively. The operating process of the reactors displayed that a reduction in HRT augmented biohydrogen manufacturing. The work that used mixed culture found that the dominant microbial population at pH 4.0 involved Hydrogenimonas thermophila, Sulfurospirillum carboxydovorans, Sulfurospirillum cavolei, Sulfurospirillum alkalitolerans, and Thiofractor thiocaminus. No research on waste black cumin extract was found in biohydrogen studies, and it was determined that this substrate source is applicable for biological hydrogen manufacturing.

Bioethanol production from pistachio (pistacia vera L.) shells applying ozone pretreatment and subsequent enzymatic hydrolysis.

Pistachio (pistacia vera L.) is a lignocellulosic raw material. One of the most pistachio produced three countries in the World is Turkey and Sanliurfa is the city that most pistachio production in Turkey. As a result of this production, a large amount of pistachio waste is generated. Therefore, this study was conducted considering the abundant pistachio waste and furthermore, the effects of ozone and combined (ozone and hot water) pretreatments for bioethanol production from pistachio shells were investigated. Initially, the ozone and combined pretreatments were applied to the pistachio shells. It has been observed that applying the combined pretreatment provides better lignin removal than only ozone pretreatment and on the other hand, the ozone pretreatment provides better lignin removal than the hot water pretreatment. Scanning electron microscopy (SEM) images of pretreated and untreated pistachio shells were compared. Enzyme activity was measured, and 30-60 FPU enzyme loading was applied in an enzymatic hydrolysis. The enzymatic hydrolysis was applied to obtain fermentable sugar from the pistachio shells after pretreatments. As a result of enzymatic hydrolysis, 2.34-8.24 g/L reducing sugar was obtained. On the other hand, 1.21-2.33 g/L ethanol concentration was obtained end of the fermentation process. Fermentation efficiency was calculated between 42% and 55%. As a result, this study showed that combined pretreatment was more effective than the single pretreatment in the ethanol production process.

Influence of media characteristics on energy dissipation in filter backwashing.

Effective cleaning of granular filters during backwashing processes needs maximum turbulence and maximum shear in the fluid particle field. The energy dissipation in a backwashed filter as a particulate fluidized bed arises due to the suspending and random motions of particles and turbulent fluctuations in the bed. Size, density, and sphericity of the filter materials greatly influence the fluidization behavior of the media. In this study, a new model is proposed for predicting the energy dissipation parameters namely the hydrodynamic shear stress (tau(a)), the velocity gradient (G(a)), the turbulence dissipation coefficient (C(a)), and the turbulence parameter (C(a)0.5/Re) in backwashing of filters for different types of filter materials (sand, anthracite, and glass ball). The hydrodynamic shear stress is the dominant mechanism of filter cleaning and appears to increase with increasing the density and size of the filter media particles. Using the basic set of data, a step by step procedure is developed to compute the velocity gradient G(a), the turbulence dissipation coefficient C(a), the hydrodynamic shear stress tau(a), and the turbulent parameter (C(a)0.5/ Re).