Novel Gemini Cationic Surfactants: Thermodynamic,Antimicrobial Susceptibility,and Corrosion Inhibition Behavior against Acidithiobacillus ferrooxidans

The Egyptian oil and gas industry is suffering from severe metal corrosion problems, particularly microbial-induced corrosion. There is limited knowledge on the corrosion inhibition of carbon steels in the presence of an acidophilic, iron-oxidizing bacterial species Acidithiobacillus ferrooxidans. Therefore, in this study, novel Gemini cationic surfactants, in three forms depending on variation in alkyl chains of 8, 12, and 16 carbon atoms named FHPAO, FHPAD, and FHPAH, respectively, were synthesized and characterized by Fourier transform infrared and nuclear magnetic resonance spectroscopy. The surface parameters and the thermodynamic of the synthesized surfactants were evaluated at three different temperatures, 20, 40, and 60 °C. The synthesized Gemini cationic surfactants were tested as broad-spectrum antimicrobial, antibacterial and anticandida agents. They evaluated as biocides and corrosion inhibitors against Acidithiobacillus ferrooxidans. FHPAD showed higher adsorption ability at the solution interface and higher affinity to construct micelles than FHPAO and FHPAH. Both adsorption and micellization processes were hydrophobic and temperature dependent. FHPAO, FHPAD and FHPAH exhibited wide-spectrum antimicrobial activities, and the highest activity and the lowest minimum bactericidal/fungicidal inhibitory concentrations were attributed to FHPAD. Furthermore, synthesized FHPAD demonstrated the highest metal corrosion inhibition efficiency of 95.5% at 5 mM in comparison to 87.5% and 81.7% for FHPAO and FHPAH, respectively. In conclusion, this study provides novel synthesized cationic surfactants with many applications in the oil and gas industry, such as broad-spectrum antimicrobial, biocides, and corrosion inhibitors for acidophilic, iron-oxidizing bacterial species Acidithiobacillus ferrooxidans.     

A geostatistical approach for groundwater head monitoring network optimisation: case of the Sfax superficial aquifer (Tunisia)

In many developing countries, the groundwater monitoring network is randomly designed, and consequently needs to be revised and optimised to reduce operation time and cost, remove redundant piezometric data, and strengthen sparseness data zone with supplementary observation well. The geostatistical approach used in this work is based on the universal kriging variance combined with cross‐validation test. Hence, a rational interpolation of water table elevations was performed to evaluate the accuracy of data employed in the piezometric head modelling. In this study, the groundwater monitoring network of the Sfax superficial aquifer in the south east of Tunisia was optimised. The elimination of five observation wells induces the invariability in the variance of estimate due to their less contribution in interpretations of the groundwater level behaviour. However, 38 wells were added at areas of high variance of the kriging in order to ameliorate the spatial coverage of the monitoring network.     

Modeling the oxidative coupling of methane using artificial neural network and optimizing of its operational conditions using genetic algorithm

The effect of some operating conditions such as temperature, gas hourly space velocity (GHSV), CH₄/O₂ ratio and diluents gas (mol% N₂) on ethylene production by oxidative coupling of methane (OCM) in a fixed bed reactor at atmospheric pressure was studied over Mn/Na₂WO₄/SiO₂ catalyst. Based on the properties of neural networks, an artificial neural network was used for model developing from experimental data. To prevent network complexity and effective data input to the network, principal component analysis method was used and the number of output parameters was reduced from 4 to 2. A feed-forward back-propagation network was used for simulating the relations between process operating conditions and those aspects of catalytic performance including conversion of methane, C₂ products selectivity, C2 yielding and C₂H₄/C₂H₆ ratio. Levenberg-Marquardt method is presented to train the network. For the first output, an optimum network with 4-9-1 topology and for the second output, an optimum network with 4-6-1 topology was prepared. After simulating the process as well as using ANNs, the operating conditions were optimized and a genetic algorithm based on maximum yield of C₂ was used. The average error in comparing the experimental and simulated values for methane conversion, C₂ products selectivity, yield of C₂ and C₂H₄/C₂H₆ ratio, was estimated as 2.73%, 10.66%, 5.48% and 10.28%, respectively.     

Evolution in Structural and Optical Properties of Stannic Oxide Xerogel upon Heat Treatment

Upon consecutive heat treatments at increasing temperatures, the microstructure of solution–sol–gel-derived stannic oxide (SnO₂) xerogel evolves in three stages: (I) below 300°C, characterized by extensive dehydroxylation and gel shrinkage with little grain growth and surface loss; (II) between 300° and 500°C, by extensive crystallization, leading to dramatic surface loss (by 70%); and (III) above 500°C, by grain growth. Concurrently, the UV-absorption edge shows red shifts during stages I and II and blue shifts during stage III, resulting in distinct color variations. The edge displacement bears a close correlation with a Raman "defect band" at ∼305–328 cm⁻¹.     

Reducing of heat loss of rubber compound using natural zeolite filler: effect of partially substitution of fillers on compound properties

The main objective of this work was reducing the heat loss of styrene butadiene rubber by partial substitution of carbon black with natural zeolite as a filler. Reducing the usage of carbon black in the rubber industry is a good strategy to decrease fossil fuel usage and global warming. There are different mineral fillers like silica and clay to be used instead of carbon black. Effect of application of natural zeolite on reducing the heat loss of rubber compound based on SBR was investigated by melt mixing of natural zeolite in rubber matrix in an internal mixer. Natural zeolite was selected as 5, 10, 15, and 20 phr. Carbon black was partially substituted with zeolite and the effect of natural zeolite content and structure on different aspects of the compound including heat buildup, hardness, elongation, and modulus were evaluated. It was shown that although cross-link density and mechanical properties of the compounds decreased a little, but a significant improvement was observed in the fatigue resistance of the compounds beside a favorable decrease in the heat buildup and abrasion loss with an increase in the natural zeolite loading. The rate of improvement in properties was slowed down at zeolite contents higher than 5 phr.     

A comparison of Zayandehrood River water values for agriculture and the environment

River water management is challenging not only since they are open systems with changing physical structures, but also because the water values are mostly unknown over varied sectors. If policymakers grasp water values, water management will be more efficient. This research intends to examine the values of water in agriculture, which receives the most substantial portion of water resources, with the values of water in the environment in Isfahan located in the Zayandehrood River basin of Iran. The consequences of contingent valuation and production function methods revealed that per cubic metre value of water is 13 times higher in the environment than agriculture. The government should reconsider the higher value of the environment despite it is a non‐market value. The contingent valuation model additionally proved that women exhibited 21% more willingness to pay than men in order to protect the environment; however, they are paid less by 36%.     

An efficient and direct method for out-of-plane buckling analysis of Y-braced steel frames

Dimensionless design-oriented charts are introduced for customising a new and efficient method of computing the out-of-plane critical buckling load of Y-braced steel frame systems. These charts are derived from extensive parametric studies on the basis of an “exact solution”, within the limits of the Eulerian theory, stability analysis, using a wide array of geometric characteristics of practical interest. Demonstrated with numerical examples, these calculations are shown to yield, in a very efficient way, accurate critical load values of these systems. The charts can be used for practical design of Y-brace elements.     

Improvement of Glass Transition and Flowability of Reduced-Fat Coffee Creamer: Effect of Fat Replacer and Fluidized Bed Drying

This study was conducted to investigate the effects of inulin (0, 2.5, 5, and 7.5 %), maltodextrin (0, 15, 20, and 25 %), and different drying processes (one- and two-stage drying) on the morphology and physicochemical properties of regular and instant reduced-fat creamers. The present study showed that the drum-dried creamer containing 0 % maltodextrin and 0 % inulin was fully sticky powder with dark brown color. It was found that the maximum increase in maltodextrin (from 0 to 25 %) and inulin (from 0 to 7.5 %) resulted in the creamer with the highest glass transition temperature and the lowest stickiness among all formulated creamers. The application of two-stage drying involving fluidized bed drying resulted in further improvement of the glass transition temperature and stickiness of the reduced fat instant creamer. The instant creamers obtained from two-stage drying had considerably higher glass transition temperature and lower bulk density than the regular creamers from one-stage drying. Such improvement could be due to the reduction of bulk density induced by fluidized bed drying. This might be because of higher porosity of the creamer particles after agglomeration. The current study revealed that the addition of high amounts of inulin and maltodextrin also played a significant role in the reduction of bulk density and further improvement of glass transition temperature (T_g) and solubility of the reduced fat creamer. The instant reduced fat creamer containing 25 % maltodextrin and 7.5 % inulin had the most desirable characteristics among all formulated creamers.     

Performance evaluation of open-cycle solar regenerator using artificial neural network technique

Theoretical investigation on the performance of lithium chloride (LiCl) absorption cooling system using an artificial neural network (ANN) model is presented. Tabulated data from the literature are used to construct the ANN model. Solar collector desiccant/regenerator is applied to re-concentrate the working solution. Using the proposed model, the effect of system design parameters; namely regenerator length, and air flow rate on the performance of the system is demonstrated. The variation of the thermo-physical parameters along the regenerator length is highlighted.