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...     

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%.