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Since knowing the effect of salt type is a vital parameter during smart-water injection for enhanced oil recovery (EOR) purposes, surface-free energies on the carbonate surface contacted by crude o...

We reported the solubility values for an active pharmaceutical ingredient (API) at different operational conditions. Tenoxicam was considered as the API model in this work, and the values of API so...

Understanding the roles of asphaltene and resin as natural surfactants existed in crude oil can enlighten contradicting reported results regarding interfacial tension (IFT) of crude oil/aqueous solution as a function of salinity and ion type. In this way, this study is aimed to investigate the effect of these natural surface active agents on IFT of with special focus on SO42− anion and Mg2+ cation. Two different synthetic oil solutions of 8 wt% of the extracted asphaltene and resin dissolved in toluene are prepared, and then IFT values are measured. After that, the obtained results are compared with the IFT of intact crude oil in contact with the same saline solutions examined in the previous stage. The obtained results showed a synergistic effect of Na2SO4 + MgCl2 solution unlike the MgSO4 + MgCl2 and CaSO4 + MgCl2 solutions on IFT reduction of resin at MgCl2 concentration of 15000 mg·kg−1. In summary, it is found that the affinity of asphaltene molecules towards the interface of oleic phase/ionic solution leads to higher IFT variation.

Pebax®1657 and [Omim][PF6] ionic liquid (IL) were used to fabricate a blend membrane and applied for CO2 separation. The changes upon adding ionic liquid into the polymer matrix as well as the membrane characteristics were studied through SEM, FTIR, DSC and TGA analysis. The obtained gas permeation results indicated that the CO2 permeability in all membranes was much higher than the other studied gases. CO2 permeability of Pebax containing 8 wt% IL increased from 82.3 Barrer up to 125.6 Barrer at a pressure of 2 bar, which showed a 53% increment compared to the neat Pebax membrane. Furthermore, as the [Omim][PF6] loading within the polymer matrix was increased, the CO2/CH4 and CO2/N2 selectivities improved. In addition, the permeability and selectivity of gases was enhanced as the feed pressure increased. Upon increasing feed pressure to 10 bar, the CO2 permeability of Pebax containing 8 wt% IL reached 185.3 Barrer, which was approximately 48% higher than the permeability at a pressure of 2 bar. Moreover, the selectivity of CO2/CH4 and CO2/N2 for the Pebax/8wt% IL membrane at pressure of 2 bar was 15.3 and 46.5, respectively, which improved to 19.7 and 59.8 as the pressure increased to 10 bar.

Sulfate anion is well-known for being one of the most active agents to be injected into the oil reservoirs and being capable of not only altering the interfacial properties of crude oil but...

Ionic liquids (ILs) can be tailored as chemical surfactants and surface active agents to reduce the interfacial tension (IFT) of crude oil/aqueous solutions for enhanced oil recovery processes. The current investigation was aimed to explore the nature of ingenious active agents in crude oil, including asphaltene and resin, and their possible interactions with two families of ILs, namely pyridinium and imidazolium, on the IFT of crude oil/aqueous solutions, both in the presence and absence of MgCl2. To the best of our knowledge, the effect of crude oil type on the IFT of crude oil/aqueous solution containing salts and IL has not been ever investigated. Accordingly, IFTs of light, medium and heavy crude oils (labeled as LCO, MCO and HCO, respectively) and two ILs, i.e. [C8mim] [Cl] and [C8Py] [Cl] were measured. In addition, the effects of the total acid number of crude oils, the amount of ingenious active agents in the crude oils as well as their major structural, molecular parameters such as hydrogen/carbon ratio and type and amount of heteroatoms (i.e. nitrogen, sulfur and oxygen) were investigated. The obtained results indicated that the performance of ILs was influenced by the crude oil and IL types. In details, the aromatic section of cationic part and their interactions with heteroatoms of crude oil showed the most influential role on the IFT variation.

Accurate knowledge and prediction of the liquid–liquid transition phase consisting of ionic liquids and organic solvents are key points in different industrial processes. In this way, the effects o...

In the light of artificial neural network (ANN) model advantages, a predictive ANN model is proposed to correlate the surface tension of common hydrocarbons including normal alkanes (i.e. n-C4–n-C40), linear alkenes (i.e. 1-C4–1-C40), and cycloalkanes (C4–C20) in a wide range of temperatures. The most important advantage of the current proposed network is its low number of input variables which are only temperature of the system as well as carbon number and critical temperature of components utilized to differentiate among the different components. The obtained results revealed that a model trained by the Levenberg–Marquardt algorithm with hyperbolic tangent and linear transfer functions for the hidden and output layers, respectively, comprised of 27 hidden neurons is the optimum structure. In sum up, the obtained results demonstrated that the proposed ANN model is capable to satisfactorily predict and correlate the 5461 surface tension data points of normal alkanes, linear alkenes, and cycloalkanes as a function of temperature with maximum deviation of 0.47, 0.40 and 0.43 mN/m, respectively, just using three inputs parameters considering testing data subset.

In recent years, the behavior of crude oil interfacial tension (IFT) as a function of salt concentration have been investigated. The results found in literature are highly controversial, thus the current experimental study aimed to clarify the reasons behind this by developing a methodology based on extracting asphaltene and resin from three different crude oils and performing elemental analysis on them. In addition, the effect of salinity on the IFT of three studied crude oil was compared with the synthetic crude oil consisted of different weight percent (wt%) of asphaltene and resin in toluene. The obtained results revealed that the IFT of crude oil as a function of salinity depended not only on the wt% of asphaltene and resin fractions but also on the aromaticity of asphaltene and resin. In fact, as the aromaticity of asphaltene increased, the performance of asphaltene decreased as a function of salinity while the aromaticity of resin led to a revers trend on IFT variation.

Low salinity (LS) and smart water (SW) flooding processes which receive a great interest as cost-effective and environmental friendly techniques are relatively new enhanced oil recovery methods. Although shifting carbonate surfaces towards a water-wet state is the main mechanism behind these methods, effects of controlling factors (for instance: ion type or salinity) are already remained unsettled. In this regard, the effects of sulfate ion types (i.e. Na2SO4, MgSO4 and CaSO4) and their concentrations (i.e. 0–45,000 ppm) on wettability alteration are investigated using contact angle (CA) measurement technique. In addition, work of cohesion, work of adhesion and spreading coefficient of all examined salts are calculated based on the experimental interfacial tension (IFT) and CA measurements. The results reveal that reduction of salinity of the aqueous solution and presence of sulfate anion at high salinity conditions (15,000–45000 ppm) are two important parameters for wettability alteration.

A wide application of ionic liquids in different separation processes, such as multiple reaction, extraction cycles, and azeotropic or close-boiling-mixture distillation processes, has been reporte...

Carbonated water has been recently proposed as an enhanced oil recovery method for crude oil reservoirs. Interfacial tension (IFT) plays a crucial rule on the displacement of trapped oil ganglia in the porous media. This investigation is designed to systematically assess the dynamic interfacial tension (DIFT) of two different types of crude oils with carbonated water (CW). In addition, the measured experimental data were applied into specified models. The DIFT behavior of acidic and non-acidic crude oil samples/CW and deionized water (DW) are also compared to find the effect of dissolved carbon dioxide in water on IFT. At the next stage, DIFT of all the results were used through three different models namely diffusion-controlled, mono-exponential models and an empirical equation. In this way, induction, adsorption (i.e. relaxation or rapid fall), equilibrium and meso equilibrium times, diffusivity of surface active materials in the crude oil to the crude oil/aqueous phase interface (D SA ) and surface excess concentration of surface active components (Г SA ) of CW systems are calculated and compared with those of the crude oil-DW systems. While IFT reduction is considered as an effective mechanism of CW injection for more oil recovery, the obtained results in the current investigation show a contradicting trend. In details, the dissolved CO 2 reduces the pH of the aqueous phase, consequently, increases the basic natural surfactant ionization. The obtained results show that domination of Г SA reduction compared to the ionization of basic natural surfactant leads to IFT enhancement.

Recently, carbon dioxide (CO2) flooding into depleted reservoirs regardless of miscible or immiscible displacement is widely investigated not only to improve oil recovery but also to reduce the greenhouse effect of this gas produced by numbers of industries in the globe. In the light of this fact, in the first stage of this investigation, the minimum miscibility pressure (MMP) of CO2 and light crude oil (API° = 35) with low asphaltene content was determined at temperatures of 30, 50 and 80 °C using vanishing interfacial tension (VIT) method. The obtained results demonstrated that the MMP of the studied system is almost linear function of temperature with slope of 0.15 MPa/K. The interesting point is that the results revealed a reduction in slope as the composition of light components of crude oil increases.

The concerns for water availability, affordability and environmental consideration have motivated more research on the development of smart water injection for enhanced oil recovery process. Although wettability alteration has been considered as the dominant mechanism, there is an ample space in this area needs to be explored more. Therefore, a systematic series of experiments is designed and performed to examine the effect of salinity and ion type on the wettability of the carbonate rock surface to find the active mechanisms. For this purpose, the concentrations of different salts including NaCl, KCl, CaCl 2 and MgCl 2 are examined during 10 days of soaking for salts concentrations range of 0–45,000 ppm. Based on the measurements of contact angle (CA), it is concluded that the monovalent cation bonded to the chloride anion showed better performance on the wettability alteration of oil wet carbonate rock surface compared to the divalent cations bonded to the chloride anion. In addition, comparing the results of CA measurements of NaCl and KCl solutions as a function of concentration showed completely different wettability behaviors. The presence of KCl shifted the wettability of the carbonate rock surfaces from strongly oil wet to strongly water wet state for all of studied concentrations while as the concentration of NaCl was decreased, the more wettability alteration was observed.

Changing the wettability of reservoir rock towards strongly water-wet state is effective way to enhance oil recovery from fractured carbonate reservoirs which are typically oil-wet. Regarding this fact, the injection of surfactant and the bacterial solution as EOR agents is proposed in the current work as a potential method to alter the wettability of rock surface reservoir. Nevertheless, there is a definite lack of experimental data regarding this method and the synergistic effect of both chemical and bacterial solutions on this process. In this study, the sole and combined effects of the bacterial solution using an Enterobacter cloacae strain as a biosurfactant-producer are compared with sodium dodecylbenzenesulfonate (SDBS) and dodecyltrimethylammonium bromide (C12TAB) as anionic and cationic surfactants, respectively. For this purpose, static contact angle measurement are utilized to investigate the wettability alteration. The obtained results revealed that bacterial solution can alter the wettability of calcite surfaces to the same extent of C12TAB and more than SDBS. In addition, base on the obtained results it can be concluded that the combination of bacterial solution and chemical surfactant are not proposed for in-situ biosurfactant techniques, since the Enterobacter cloacae uses the chemical surfactant as the carbon source concomitantly a reduction in the biosurfactant production occurs.

The current investigation is aimed to investigate the effect of new families of ionic liquid (IL) based surfactants for considering the enhanced oil recovery process. Imidazolium based ILs with chloride anion ([Cn mim][Cl]) with long alkyl chains, (n = 12 and 18) are synthesized and their effectiveness on the interfacial tension (IFT) and emulsification phenomena at the co-presence of NaCl and Na2SO4 salts are examined. Dynamic IFT and critical micelle concentration (CMC) values of different solutions were measured and determined. Moreover, the performance of the considered solutions at the CMC was examined on the wettability alteration of the oil-wet carbonate rock surface. The obtained results revealed that for the shorter alkyl chain length IL (C12), the presence of NaCl was more effective compared with the Na2SO4 while a reverse trend is observed for the longer alkyl chain length IL (C18). The contact angle measurement revealed that IL solutions containing sulfate anion altered the wettability of the oil-wet surface (from about 160°) toward the strongly water-wet state (41° for C12 and 45° for C18) and alkyl chain length introduces no significant effect. Besides, the solution containing chloride anion affected by IL type, that means longer alkyl chain length (C18) was unable to change wettability toward the water-wet state and wettability changed to 113° while C12 changed wettability to 34°. It is also found that although increasing the concentration of both ILs led to the lower IFT values with the minimum value of 0.6 mN/m, raising the temperature from 298 K to 348 K increased the IFT values.

Although the capability of using sulfate anion as a wettability modiffier is well established, no systematic investigation on the effect of sulfate ions and natural surfactants in the crude oil including asphaltene and resin on the interfacial tension (IFT) of acidic crude oil (ACO)/sulfate were performed. In this regards, the fluid/fluid interactions are tested through the IFT measurements for ACO, asphaltene and resin extracted from ACO in the presence of sulfate salts including Na2SO4, MgSO4 and CaSO4 while the concentration of each salt ranges between 0 and 45000 ppm. The obtained results demonstrate that the capability of asphaltene molecules is higher for IFT reduction compared with the resin molecules which can be related to the higher affinity of asphaltene to be arranged on the surface of ACO/sulfate aqueous solutions.

The impacts of salinity adjustment of displacing fluid have recently gained special attention to enhanced oil recovery (EOR). Different mechanisms have been studied widely in the literature while some of them are still subjugated to more scrutiny. The effects of diluted sea water on the interfacial properties of brine and asphaltenic-acidic crude oil and the wettability alteration of carbonate reservoir rock are investigated in this experimental observational work. The measurements of interfacial tension (IFT) and contact angle (CA) as two main parameters are studied. Besides, the effects of asphaltene and resin in the crude oil on the IFT values between the crude oil and aqueous solution are investigated. The experimental results show that the lowest IFT values are obtained at high salinity conditions, while the surface rock wettability alterations are observed at low salinity conditions. Based on the obtained results, a combined mechanism is proposed to describe the wettability alteration towards more water wet at low salt conditions.

Asphaltene precipitation and deposition within the reservoir formation is one of the main concerns during enhanced oil recovery (EOR) processes especially during the gas injection. In the current study, different aspects of carbon dioxide (CO 2 ) and nitrogen (N 2 ) injection in the reservoir, was thoroughly examined. The feasibility of using these gases as the injection gas was explored using Bayesian network-based screening method. After recombination and preparation of the live crude oil, precipitation of asphaltene using vanishing interfacial tension (VIT) method and core flooding experimentation was examined. Besides, swelling test was utilized to investigate the effect of CO 2 and N 2 injection on the expansion of live crude oil. The obtained results showed that recovery factor (RF) of CO 2 injected method in core flood test is higher than N 2 injection due to higher swelling and better miscibility conditions. Although, VIT measurements showed asphaltene precipitation during CO 2 injection, no sign of asphaltene deposition during core flood test at near bubble point pressure was observed.

It is generally believed that asphaltenes and resins as the polar components in crude oil can get adsorbed at the oil/water interface and act as a surface active agents. However, due to the complex behavior of asphaltenes and resins, the understanding of their surface properties is challenging. In this work, the effects of addition of six electrolytes: NaCl, KCl, Na2SO4, MgSO4, MgCl2, and CaCl2 have been employed to experimentally evaluate their effect on dynamic interfacial tension of asphaltenic and resinous in oil/water interface. All of the electrolytes had the same ionic strength (0.7 M) and the pedant drop shape method was used for analysis. For this purpose, asphaltene and resin fractions of a crude oil sample with 27 API° are extracted and analyzed with elemental and Fourier-transform infrared spectroscopy (FTIR) analyses. Then, two synthetic oils samples prepared based on dissolution of extracted asphaltene and resin in toluene, their dynamic interfacial tension (IFT) values are measured in the presence of different brines. The adsorption/relaxation reorganization times of asphaltene and resin components at the oil samples/aqueous solution interface are evaluated with exponential decay model. Results suggest that divalent cations, Ca2+ and Mg2+, possess higher affinity toward the polar groups of asphaltene and resin components in the presence of Cl− compared to SO42−. Specially, Ca2+ is more preferred over Mg2+, particularly for resinous oil sample. Due to the higher affinity of the polar functional groups toward the interface in the presence of CaCl2, the lowest adsorption time was obtained for CaCl2, which refers to the time required for coverage and packing of active agents at the interface.

Finding the high-performance anions and cations in the aqueous solutions are crucially required during the smart water injection make it the main core of many enhanced oil recovery (EOR) studies. Nevertheless the previously published literature revealed a lack of understanding about the synergistic or antagonistic effect of NaCl (as the most abundant salt in the sea water) and other salts with the same ionic strength on the interfacial tension (IFT), wettability alteration and spreading coefficient. Therefore, the main purpose of this study is aimed on this concern. To reach this goal, the dynamic IFT values of crude oil/different aqueous solutions with ionic strength of 0.7 M and contact angle values between these phases on the oil wet carbonate surface soaked under different times in the prepared aqueous solutions are measured. After that, the measured values are used to calculate the spreading coefficient and distribution capability of oil and water phases on the carbonate rock surface. The obtained results revealed that to change the wetting state of carbonate rock toward a more water wet state, a synergistic effect was observed between NaCl and salts containing sulfate anion, i.e. Na2SO4 and MgSO4.

Solubility of solute in supercritical fluids at different pressures and temperatures is one of the most important parameters necessary for design of any supercritical fluid-based processes. Among different supercritical fluids, carbon dioxide is one of the most widely used solvents due to its useful and green characteristics. In this work, with the assist of supercritical carbon dioxide as the solvent, solubility of cyproheptadine in different temperatures (308–338 K) and pressures (160–400 bar) are measured using static method. The obtained results demonstrated that solubility of cyproheptadine ranged between 3.35 × 10−5 and 3.09 × 10−3 based on mole fraction. A closer examination of measured solubility data show that not only solubility of cyproheptadine increases by increasing pressure but also experiences a cross over pressure about 200 bar. At last, the measured solubility data are correlated using four widely used density based correlations namely Mendez Santiago–Teja (MST), Kumar and Johnston (KJ), Bartle et al., and Chrastil models. The obtained results demonstrated that the best correlative capability was observed for KJ model leads to the average absolute relative deviation percent (AARD %) of 6.3%.

In the present study, a new correlation with both correlative and extrapolative capabilities is proposed for thermal conductivity of the pure ionic liquids (ILs) and the optimum values of its fitting parameters were obtained by a genetic algorithm. All of all, 209 data points of 21 ILs were collected from previously published literature. The collected data were divided into two different subsets namely training (143 data points) and testing (66 data points) subsets. Training subset was used to find the optimum values of the fitting parameters of the proposed correlation. After that, the extrapolative and correlative capabilities of the proposed correlation was tested by testing data subset was not utilized during the training stage. The average absolute relative deviation percent (AARD %) during the training stage was 5.22%, while the results revealed AARD % of 10.76% for testing stage. In general, the overall results revealed a rather good accuracy of the proposed correlation especially considering its extrapolative capability. Finally, the obtained results by the proposed correlation were compared with those obtained by different available correlations including group contribution and artificial neural network approach which shows a good functionality of the proposed correlation.

The use of ionic liquids is being increasingly investigated in separation technologies, for example, in special distillation processes such as azeotropic or close-boiling mixtures. Such applications require accurate knowledge of the physical properties of the mixtures involved. In this respect, the correlation or estimation of the bubble points might be difficult due to the complex nature of some ternary systems, especially in the presence of ionic liquids. In the present study, the bubble points of several ternary mixtures containing an ionic liquid were correlated using an artificial neural network modeling approach. The solvents investigated consisted of 1-propanol, 2-propanol, ethyl ethanoate, methyl ethanoate, chloroform, propanone, ethanol, methanol and water and the ionic liquids considered were 1-ethyl-3-methylimidazolium trifluoromethane-sulfonate ([emim][CF3SO3]) and 1-butyl-3-methylimidazolium tetrafluoroborate ([bmim][BF4]). For this purpose, a total of 529 experimental data points from previously published literature were collected to aid in finding the best network architecture and the optimum parameters. To do this, the collected data were divided into two subsets, namely the training and testing subsets. Using the training data set, and based on a trial and error procedure, the optimum network parameters were determined to be three layers including one input, one hidden and one output layer, nine neurons in the hidden layer, the logarithmic-sigmoid transfer function for the hidden layer, and the purline function for the output layer. The optimized weights and biases were also obtained and presented. The feasibility of the proposed network for the correlation of ternary bubble point was then examined using data that were not used in optimizing the network. The overall average absolute relative deviation (AARD %), mean square error (MSE), maximum deviation (Emax), minimum deviation (Emin) and correlation coefficient (R2) were calculated to be 0.20%, 0.9953, −0.97, 0.87 and 0.95, respectively.

In the pharmaceutical industry where the supercritical fluid-based technologies are utilized it is very important and vital to know the accurate value of the equilibrium solubility of solids required for the engineers to determine the size of the equipments. According to this requirement, the purpose of this study was measuring the solubility of fluoxetine hydrochloride with IUPAC name of 3-phenyl-3-[4-(trifluoromethyl)phenoxy]propan-1-amine hydrochloride using a static method coupled with gravimetric method. The measured solubility data at the temperature and pressure range of 308.15–338.15 K and 16–40 MPa was ranged between 2.65 × 10 −5 and 8.12 × 10 −4 based on the mole fraction. The results revealed that the solubility was increased when the pressure was increased while the effect of the temperature was more complex. Finally, the measured solubility data were correlated using three different correlations namely Bartle et al., Mendez-Santiago–Teja and Kumar and Johnston. The results of modeling revealed that the Bartle et al. model leads to the lowest average absolute relative deviation (AARD %) of 9.48.

Ionic liquids (ILs) are amazing fluids introduced as a replacement for conventional solvents due to their unique properties. Unfortunately, they have several unfavorable features such as high viscosity, which makes pumping them difficult on industrial scale. In this regard, several researchers mix the ionic liquids with each other or some conventional solvents, organic and inorganic compounds, to eliminate those unfavorable features. So the binary properties of the ILs mixtures have been increasingly measured and correlated through the past years. One of the most widely used solvents and additives in the different chemical industries is methanol. In the present investigation, the capability of artificial neural networks for correlating the binary density of the ILs systems containing methanol as a common part (total of 426 experimental data points) has been examined. The results revealed that the best network architecture obtained in this study was feasible to correlate the binary densities of the ILs mixtures with average absolute relative deviation percent (AARD%), average relative deviation percent (ARD%) and correlation coefficient (R2) values of 0.85%, −0.05 and 0.9948, respectively.

In the present study, solubility of ketoprofen in the supercritical carbon dioxide was measured experimentally using gravimetric method. In this direction the temperature and pressure was ranged between 308.15–338.15 K and 160–400 bar, respectively. The obtained solubilites revealed that the ketoprofen solubility was in the range of 2.21 × 10−5 to 7.12 × 10−4 mole fraction according to the different temperatures and pressures. Measured solubilites demonstrated that pressure and temperature have a direct effect on the solubility enhancement. Finally, the least square method and curve fitting approaches were utilized to find the fitting parameters of four semi-empirical density based correlations including Mendez-Santiago–Teja, Bartle, Chrastile and Kumar and Johnston methods. The results revealed that Bartle et al. method was able to correlate the ketoprofen solubility with a minimum average absolute relative deviation (AARD %) of 5.95%.

Transportation of waxy crude oil in a cold environment can result in wax depositions, which are solid deposits, on the pipe wall. The formation of paraffin in the bulk of the petroleum is a crystallization process. Deposition in Bangestan crude oil pipelines can cause reduction in flow area and thus decrease in the crude oil feed of Ahvaz-3 production unit. Several techniques have been used to minimize the wax deposition in crude oil flowed through the pipelines, howeverthermal insulation of pipelines is considered as an efficient method. The main objective of this study was to determine the influence of insulation thickness on wax deposition for Bangestan crude oil pipeline of Ahvaz-3 production unit with the OLGA simulator. The results of simulation show that the maximum reduction in wax deposition was obtained by using 3.4 inch of insulation polypropylene.

On the basis of an artificial neural network (ANN), a model is proposed to predict the thermal conductivity of pure ionic liquids. A total of 209 data points from 21 different ionic liquids was used to train and test the proposed network. The optimum number of hidden layers was determined to be 1, with 13 neurons in the hidden layer and logarithmic–sigmoid and purelin functions as the transfer functions in the hidden and output layers, respectively. The results obtained reveal that the proposed network is able to correlate and predict the thermal conductivity of all of the pure ionic liquids with an overall absolute mean relative deviation percent (MARD %) of 0.5% and mean square error (MSE) of 1.2 × 10–6. The optimized network was also compared with literature correlations and a predictive group contribution method. The results indicate the rather good accuracy of the proposed neural network compared to the previously proposed literature methods.

The unique physical properties of ionic liquids play a decisive part in many of their applications. Therefore, the ability to predict the physical properties of ionic liquids is extremely important for the rational design of proper ionic liquids with specific properties. In practice, the processes involving ionic liquids usually contain other components, in addition to the ionic liquids. Therefore, in addition to pure component properties, knowledge of the physical properties of mixtures are also crucial for various applications. In the present study, the feasibility of using a feed-forward multi-layer perceptron neural network (MLPNN) model was investigated to predict the electrical conductivity of the ternary mixtures of 1-butyl-3-methylimidazolium hexafluorophosphate ([bmim][PF 6 ]) + water + ethanol and [bmim][PF 6 ] + water + acetone in the temperature range from 288.15 K to 308.15 K, consisting of 104 data points. Not only were different networks, namely the linear and the hyperbolic tangent sigmoid transfer functions, considered in this study, but also the effects of the number of hidden layers, hidden neurons and the training algorithm were investigated on the accuracy of the results using 78 data points as training data to minimize the average absolute relative deviation percent (AARD%), mean square error (MSE) and correlation coefficient ( R 2 ). Among the various cases studies, statistical analyses indicated the best configuration of the network to include one hidden layer and seven neurons in the hidden layer. The optimum network was then validated using 26 data points (test data) not used in the training stage which indicated the good interpolative ability of the trained network with AARD% = 1.44, MSE = 2.87 × 10 −8 and R 2 = 0.9981.

Several techniques have been used to minimize the wax deposition in crude oil pipelines, among them the continuous addition of wax crystal modifier inhibitors is considered as an attractive technological alternative. The main objective of this study was to determine the influence of the ethylene-covinyl acetate (EVA) copolymer and its combination with chloroform (C), acetone (A), P-xylene (PX), and petroleum ether (PE) on the wax deposition thickness of an Iranian crude oil (Paydar-East Reservoir). A new facility was designed and constructed to conduct the experimental part of this study. In this study, heat transfer method was used to measure the deposition thickness at different experimental conditions. Also, samples of the deposits were analyzed at the end of each test for their wax and asphaltene + resin contents. Comparison of the heat transfer and chemical analysis methods show consistent results. The experiments were performed with and without wax chemical prevention to determine the effects of the...

Ionic liquids (ILs) especially their mixtures are of high interest within the different scientific societies due to their amazing properties. In this regard, a number of attempts have been made to measure, correlate, estimate and calculate the properties of ILs in the neat or mixture forms. Among the different possible predictive methods, artificial neural networks (ANNs) are widely used because of their unique and amazing capabilities for prediction of different parameters. With respect to this paper, a feed-forward ANN model is proposed to model the densities of different binary mixtures of ILs/ethanol. The proposed network is trained and tested with 1078 binary data points gathered by mining into the different published literatures. The data gathered from previously published literatures are separated into two different subsets namely training and testing. The statistical error analysis has shown that the proposed neural network correlated the binary densities with the overall mean absolute percentage error (MAPE), average relative deviation percentage error (ARD%), minimum relative deviation percent (RDmin%), maximum relative deviation Percent (RDmax%) and correlation coefficient ([Formula: see text] of 1.5%, [Formula: see text]0.1%, [Formula: see text]13.0%, 15.0% and 0.9712, respectively.

The feasibility of using cascade neural networks to correlate the bubble points of ternary mixtures containing ionic liquids (ILs) and classical solvents was investigated. The systems investigated consisted of the ILs from the alkylimidazolium family with either the chloride, tetrafluoroborate, methylsulfate, or ethyl sulfate anions. The classical solvents investigated included 1-propanol, 2-propanol, ethanol, ethyl ethanoate, and water. A total of 272 bubble points were used in the training (205 data points) and testing (67 data points) stages. The optimized network comprised of nine neurons in the hidden layer and used the tangent-sigmoid and purelin functions as the activation functions in the hidden and output layers, respectively. This proposed network was able to correlate the ternary bubble points of both the training (AARD % = 0.13% and R2 = 0.9921) and the testing (AARD % = 0.15% and R2 = 0.9873) subsets with good accuracy, revealing the good correlative capability of the network. The statistical error analysis of all the data indicated an overall absolute average relative deviation (AARD %), mean square error (MSE) and correlation coefficient (R2) of 0.13%, 0.44% and 0.9909%, respectively.