Introduction: The current study investigated the use of acid-treated rice husks to remove heavy metals and organic pollutants from water containing heavy metals (R2C and Cd2) and organic pollutants (phenol and atrazine). Methods: The adsorption effect of acid-treated rice husks was compared with other adsorbents such as activated carbon, chitosan, and bentonite clay. Result: both acid-treated rice husks and activated carbon were highly efficient materials, and thus, rice husks were established as a cost-effective alternative. It was revealed that acid treatment of rice husks enhanced adsorption capacity by half, and lead removal was nearly doubled. The most effective pH value for optimizing organic pollutants and heavy metals while minimizing conditions was found to be 6.5. Regarding the temperature findings, the data revealed a minor increase in temperature; nevertheless, the result was not statistically significant, even if the temperatures became more efficient. When compared to activated carbon, chitosan, and bentonite clay, acid-treated rice husks demonstrated high removal performance, making them a very cost-effective raw material. Finally, the presence of active functional groups that transfer the action of rice husks to pollutants was established by adsorption processes studied using Fourier transform infrared spectroscopy (FTIR) and BET (Brunauer-Emmett-Teller) surface area. Conclusion: Therefore, it has been demonstrated that this technique, which entails removing at least one acid-treated rice husk, is more effective at treating industrial wastewater than previously documented and widely used technologies like flocculation, coagulation, and reverse osmosis. It also offers a safe and sustainable substitute for conventional water quality methods.
This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions. A st
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
... Show MoreThe objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <
... Show MoreBackground/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to
... Show MoreThis study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase
... Show MorePollutants generation is strongly dependant on the firing temperature and reaction rates of the gaseous reactants in the gas turbine combustion chamber. An experimental study is conducted on a two-shaft T200D micro-gas turbine engine in order to evaluate the impact of injecting ethanol directly into the compressor inlet air on the exhaust emissions. The study is carried out in constant speed and constant load engine tests. Generally, the results showed that when ethanol was added in a concentration of 20% by volume of fuel flow; NOx emission was reduced by the half, while CO and UHC emissions were almost doubled with respect to their levels when burning conventional LPG fuel alone.