Simultaneous multi-objective optimization of a new promoted ethylene dimerization catalyst using grey relational analysis and entropy measurement

A hybrid approach between the Taguchi method and grey relational analysis (GRA) with entropy measurement was applied to determine a single optimum setting for reaction factors of the proposed ethylene dimerization catalyst having overall selectivity to 1-butene (S_1-btn (%)) and turnover frequency (TOF (h^-1)) as multiple quality characteristics. Titanium tetrabutoxide (Ti(OC₄H₉)₄) catalyst precursor in combination with triethyl aluminum (TEA) activator, 1,4-dioxane as a suitable modifier, and ethylene dichloride (EDC) as a novel promoter were used in the catalysis. Control factors of temperature, pressure, Al/Ti, 1,4-dioxane/Ti, and EDC/Ti mol ratios were investigated on three levels and their main effects were discussed. The effect of the binary interaction between temperature, pressure, and Al/Ti mol ratio was also examined. Weight of the responses was determined using entropy. Analysis of variance (ANOVA) for data obtained from GRA indicated that EDC/Ti mol ratio with 27.64% contribution had the most profound effect on the multiple quality characteristics. Development of the weighted Grey-Taguchi method used the Taguchi method as its basic structure, adopted GRA to deal with multiple responses, and entropy to enhance the reasonability of the comprehensive index produced by GRA to make the results more objective and accurate. Overall, these combined mathematical techniques improved catalytic performance for 1-butene production.     

A modified thermodynamic insight to deliquescence of a void‐containing nanocrystal confirmed by MD simulation

Existence of voids in crystalline structures can affect their physical and chemical properties considerably. When the size of the crystal reaches to nanoscale, experimental determination of its void fraction is difficult. In this work, a molecular dynamics approach is introduced to find equilibrium void fractions of a simple cubic (CsCl) and fcc (KCl) nanocrystals by determination of their deliquescence relative humidity (DRH) for different sizes and void fractions and extrapolation of the results to the bulk limit. To confirm the simulation results, the size dependency of DRH to the nanoparticle size was studied thermodynamically by inclusion of size‐dependent density of water nanodroplet which leads to a simple homographic equation. This method proposes the equilibrium void percents of CsCl and KCl nanoparticles to be 10 and 15%, respectively, which are obtained by extrapolation of the results to the bulk limit. The success of obtained Möbius function was also confirmed by fitting it to experimental data for deliquescence of NaCl nanoparticles which implies the importance of considering density of water nanodroplet as a size dependent quantity. Also, using the mentioned thermodynamic approach, void dependency of deliquescence for the nanoparticles was found to be as a quasi‐linear trend which is compatible with the simulation results. It is noticeable that the approach used this work for determination of equilibrium void fraction is only valid if the utilized force fields are accurate. © 2016 American Institute of Chemical Engineers AIChE J, 62: 4066–4077, 2016     

Graphene nanoplatelets dispersion in poly(<Emphasis Type="SmallCaps">l</Emphasis>-lactic acid): preparation method and its influence on electrical,crystallinity and thermomechanical properties

Poly(l-lactic acid) (PLLA)/graphene nanoplatelets (GnP) nanocomposites were prepared through solvent casting and coagulation methods. The better dispersion of graphene was achieved by ultrasounds and its effect on crystallinity, thermomechanical and electrical properties of PLLA were studied and compared in both methods. Differential scanning calorimetry (DSC) was used to investigate the crystallinity of PLLA and its composites. Field emission gun scanning electron microscope (FEG-SEM) and wide-angle X-ray scattering (WAXS) were employed to characterize the microstructure of PLLA crystallites. Dynamic mechanical thermal analysis (DMTA) was performed to study the thermomechanical properties of the nanocomposites. FEG-SEM images illustrated finer dispersion of GnP in samples obtained by coagulation method with respect to solvent casting method. Graphene imparted higher electrical conductivity to nanocomposites obtained by solvent casting under ultrasound due to better formation of graphene network. DSC thermograms and their resulting data showed positive effects of GnP on crystallization kinetics of PLLA in both methods enhanced by the nucleating effect of graphene particles. Meanwhile, the effect of GnP, as nucleating agent, was more prominent in samples produced by coagulation method without utilization of ultrasounds. WAXS patterns represented the same characteristic peaks of PLLA in nanocomposite specimens suggesting similar crystalline structure of PLLA in presence of graphene, and the intensified peaks of nanocomposites compared to neat PLLA confirmed the DSC results regarding its improved crystallinity. Graphene increased storage modulus in rubbery region and glass transition temperature of nanocomposites in the coagulation method due to restricted mobility of PLLA chains.     

Evaluation of soil liquefaction potential using energy approach: experimental and statistical investigation

Bulletin of Engineering Geology and the Environment - Liquefaction has caused many catastrophes during earthquakes in the past . The strain energy-based method is one of the modern methods used to...     

Kinetic study of hydrogen sulfide absorption in aqueous chlorine solution

Hydrogen sulfide (H₂S) is currently removed from gaseous effluents by chemical scrubbing using water. Chlorine is a top-grade oxidant, reacting with H₂S with a fast kinetic rate and enhancing its mass transfer rate. To design, optimize and scale-up scrubbers, knowledge of the reaction kinetics and mechanism is requested. This study investigates the H₂S oxidation rate by reactive absorption in a mechanically agitated gas–liquid reactor. Mass transfer (gas and liquid sides mass transfer coefficients) and hydrodynamic (interfacial area) performances of the gas–liquid reactor were measured using appropriated physical or chemical absorption methods. The accuracy of these parameters was checked by modeling the H₂S absorption in water without oxidant. A sensitivity analysis confirmed the robustness of the model. Finally, reactive absorption of H₂S in chlorine solution for acidic or circumneutral pH allowed to investigate the kinetics of reaction. The overall oxidation mechanism could be described assuming that H₂S is oxidized irreversibly by both hypochlorite anion ClO⁻ (k = 6.75 × 10⁶ L mol⁻¹ s⁻¹) and hypochlorous acid ClOH (k = 1.62 × 10⁵ L mol⁻¹ s⁻¹).     

Mechanochemical sulfidization of a mixed oxide-sulphide copper ore by co-grinding with sulfur and its effect on the flotation efficiency

Mechanochemical sulfidization of a mixed sulfide/oxide copper ore by co-grinding with sulfur and additives including Mg(NO₃)₂ and Fe(NO₃)₃ salts and iron, aluminum and magnesium powders was investigated for the first time. Also, the influence of sulfidization during the wet-milling process was examined on the separation efficiency and recovery of copper in detail. The results demonstrated that co-grinding with sulfur solely had the best flotation performance at the value of 0.5 wt.% and it was attributed to the possible existence of S-O bonding on copper oxides surfaces. In addition, adding magnesium nitrate salt, magnesium powder, iron nitrate salt and aluminum powder as additive associated with 0.5 wt% sulfur into ball milling caused the flotation improvement at the amounts of 0.2 wt%, 0.2 wt%, 0.5 wt% and 0.5 wt%, respectively. Also, the effect of grinding time and sulfidization pH with 0.5 wt% sulfur solely was determined and pHs of 7.5 to 8.5 gave the best results. The highest recovery (75.76%) and separation efficiency (63.44%) were achieved at pH of 7.5 and 8.5, respectively.     

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.     

Liquid‐phase axial dispersion of turbulent gas–liquid co‐current flow through screen‐type static mixers

This article discusses the characteristics of turbulent gas–liquid flow through tubular reactors/contactors equipped with screen‐type static mixers from a macromixing perspective. The effect of changing the reactor configuration, and the operating conditions, were investigated by using four different screen geometries of varying mesh numbers. Residence time distribution experiments were conducted in the turbulent regime (4500 < Re < 29,000). Using a deconvolution technique, the RTD function was extracted to quantify the axial/longitudinal liquid‐phase dispersion coefficient. The findings highlight that axial dispersion increases with an increasing flow rate and/or gas‐phase volume fraction. However, regardless of the number and geometry of the mixing elements, reactor configuration, and/or operating conditions, the recorded liquid‐phase axial dispersion coefficients in the presence of screens was lower than that for an empty pipe. Furthermore, the geometry of the screen was found to directly affect the axial dispersion coefficient in the reactor. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1390–1403, 2017     

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.