The effect of operating parameters on the batch scale separation of hydrocarbon mixture (benzene and hexane) using
emulsion liquid membrane technique is reported. Sparkleen detergent was used as surfactant and heavy mineral oil as
solvent to receive the permeates.
From the experimental results, the parameters that influenced the permeation are, composition of feed, contact time
with solvent, ratio of volume of solvent to volume of hydrocarbon feed, ratio of volume of surfactant solution to volume
of hydrocarbon feed, surfactant concentration, mixing intensity and glycerol as polar additive in the surfactant solution
to eliminate drop breakup.
The best conditions for the separation in this study were found to be: comp
Oil/water emulsions are one of the major threats to environment nowadays, occurs at many stages in the production and treatment of crude oil. The oil recovery process adopted will depend on how the oil is present in the water stream. Oil can be found as free oil, as an unstable oil/water emulsion and also as a highly stable oil/water emulsion. The current study was dedicated to the application of microbubble air flotation process for the removal of such oily emulsions for its characters of cost-effective, simple structure, high efficiency and no secondary pollution. The influence of several key parameters on the process removal efficiency was examined, namely, initial oil concentration, pH value of t
Theobromine, theophylline, and caffeine retention times in a C18 HPLC column (stationary phase) were investigated as a function of mobile phase flow rate, mobile phase composition, and column temperature. When the mobile phase flow rate increased from 0.1 to 1 mL/min and the methanol concentration increased from 5 to 30%, the retention time and peak width of these three compounds were found to be reduced. While there was a small influence of increasing the mobile phase flow rate on the resolution, decreasing the methanol concentration in the mobile phase considerably reduced the resolution. In addition, the mobile phase flow rate and composition were determined to have a more significant impact than the column temperature. Acco
... Show MoreThe pretreatment process can be considered one of the important processes in wastewater treatment, especially coagulation process to decrease the strength of many pollutants. This paper focused on using powdered date seeds as natural coagulant in addition to chemical coagulants (alum and ferric chloride) to find the optimum dosage of each coagulant that makes efficient removal of turbidity and chemical oxygen demand (COD) from domestic wastewater as a pretreatment process, then finding the optimum combined dosages of date seeds with alum, date seeds with ferric chloride that make efficient removal for both pollutants. Concerning turbidity, the optimum dosage for date seeds, alum and ferric chloride were 40 mg/l (79%), 70
... Show MoreThis study deals with 3rd-order difference equations with alternating coefficients (NDEAC) with a focus on studying the oscillatory properties of their solutions. An additional sufficient condition can be derived to ensure continuity for the oscillatory solution in equations. An applied example is presented to illustrate the theoretical result obtained.
. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
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