Adsorption experiments were carried out using two different low-cost sorbent materials, date seeds and olive seeds. These sorbents used as a single phase (not as mixture) to remove cadmium ions from simulated wastewater by adsorption process. The equilibrium time was found at 2 hr. The experiments include different parameters such sorbent type and weight and contact time. It was found that both of olive seed and date seed have approximately the same adsorption capacity (qm) with 15.644 mg/g and 15.2112 mg/g, respectively. Equilibrium isotherms and kinetic studies have been carried out. Langmuir isotherm model better fits the experimental data compared with the Freundlich isotherm for olive seed, while Freundlich isotherm fits for date se

   In this study, the circulating fluidized bed was used to remove the Tetracycline from wastewater utilizing a pistachio shell coated with ZnO nanoparticles. Several parameters including, Tetracycline solution flowrate, initial static bed height, Tetracycline initial concentration and airflow rate were systematically examined to show their effect on the breakthrough curve and the required time to reach the adsorption capacity and thus draw the fully saturated curve of the adsorbent. Results showed that using ZnO nanoparticles will increase the adsorbent surface area and pores and as a result the adsorption increased, also the required time for adsorbent saturation increased and thus the removal efficiency may be achieved at mi

Cadmium is one of the heavy metal found in the wastewater of many industries. The electrocoagulation offers many advantages for the removal of cadmium over other methods. So the removal of cadmium from wastewater by using electrocoagulation was studied to investigate the effect of operating parameters on the removal efficiency. The studied parameters were the initial pH, initial concentration, and applied voltage. The study experiments were conducted in a batch reactor with  with two pairs of aluminum electrodes with dimension  and 2mm in thick with 1.5 cm space between them. The optimum removal was obtained at pH =7, initial concentration = 50 mg/L, and applied voltage = 20 V and it was 90%.

New technologies have risen into popularity causing the Liquid membrane techniques to evolve over other separation techniques due to its high selectivity and recovery, increased fluxes, and reduced investment and operating cost. This work focuses on extracting Methylene Blue (MB), a cationic dye using a simple BLM separation technique from its aqueous phase. It combines extraction and stripping in a single unit operation. The feed phase was an aqueous solution of MB, the solvent chosen was soybean oil for the liquid/organic membrane phase, and tri-octyl amine acted as a carrier. The strip phase was a hydrochloric acid solution for this study. A two-phase equilibrium study was done to choose the correct solvent, carrier,

This investigation was carried out to study the treatment and recycling of wastewater in the Battery industry for an effluent containing lead ion. The reuse of such effluent can only be made possible by appropriate treatment method such as electro coagulation.
The electrochemical process, which uses a cell comprised aluminum electrode as anode and stainless steel electrode as cathode was applied to simulated wastewater containing lead ion in concentration 30 – 120 mg/l, at different operational conditions such as current density 0.4-1.2 mA/cm2, pH 6 -10 , and time 10 - 180 minute.
The results showed that the best operating conditions for complete lead removal (100%) at maximum concentration 120 mg/l was found to be 1.2 mA/cm2 cur

BOOK REVIEW

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant