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The solubility of loxoprofen as a nonsteroidal anti-inflammatory drug (NSAID) is measured at various temperatures (308, 318, 328, and 338 K) and pressures (12, 16, 20, 24, 28, 32, 36, and 40 MPa) i...

Among several proposed enhanced oil recovery (EOR) methods, smart water injection is one of the most widely examined methods due to its unique advantages on wettability alteration. Besides, another...

In the current investigation, the solubility of fenoprofen as a nonsteroidal anti-inflammatory drug in supercritical CO2 (SC-CO2) is measured by employing a motorized PVT (pressure–volume–temperatu...

In the present study, the effect of two different kinds of surfactants namely conventional (Sodium dodecyl benzene sulfonate (SDBS)) and ionic liquid (IL)-based surfactants are investigated on the ...

Carbonated brine (CB) injection, known as one of the effective enhanced oil recovery processes, is highly dependent on the reservoir conditions (i.e. temperature and pressure) as well as the type of dissolved salt in aqueous solution. This study is aimed to investigate the influential parameters on the swelling of crude oil as the most important mechanism during CB injection. The swelling of crude oil in the presence of different CB solutions consisted of different salts such as KCl, NaCl, CaCl2 and MgCl2 with constant concentration of 15,000 ppm is studied using a high-pressure, high-temperature visual cell which measures the volume of drop using image processing software based on Young-Laplace method. Also, the Δ Bond number of crude oil is examined to more reliably find out the mechanisms. According to the results, it can be concluded that the solubility of CO2 in aqueous phase is not the only parameter affecting the swelling behavior, and that the crude oil and ion type as well as temperature have remarkable effect on the mobility of CO2 molecules and their partitioning from aqueous phase toward oil phase.

Unfortunately, malaria still remains a major problem in tropical areas, and it takes thousands of lives each year and causes millions of infected cases. Besides, on December 2019, a new virus known as coronavirus appeared, that its rapid prevalence caused the World Health Organization (WHO) to consider it a pandemic. As a potential drug for controlling or treating these two undesired diseases at the cellular level, chloroquine and its derivatives are being investigated, although they possess side effects, which must be reduced for effective and safe treatments. With respect to the importance of this medicine, the current research aimed to calculate the solubility of chloroquine in supercritical carbon dioxide, and evaluated effect of pressure and temperature on the solubility. The pressure varied between 120 and 400 bar, and temperatures between 308 and 338 K were set for the measurements. The experimental results revealed that the solubility of chloroquine lies between 1.64 × 10−5 to 8.92 × 10−4 (mole fraction) with different functionality to temperature and pressure. Although the solubility was indicated to be strong function of pressure and temperature, the effect of temperature was more profound and complicated. A crossover pressure point was found in the solubility measurements, which indicated similar behaviour to an inflection point. For the pressures higher than the crossover point, the temperature indicated direct effect on the solubility of chloroquine. On the other hand, for pressures less than the crossover point, temperature enhancement led to a reduction in the solubility of chloroquine. Moreover, the obtained solubility results were correlated via semi-empirical density-based thermodynamic correlations. Five correlations were studied including: Kumar & Johnston, Mendez-Santiago-Teja, Chrastil, Bartle et al., and Garlapati & Madras. The best performance was obtained for Mendez-Santiago-Teja's correlation in terms of average absolute relative deviation percent (12.0%), while the other examined models showed almost the same performance for prediction of chloroquine solubility., Highlights • Measuring solubility of chloroquine in supercritical CO2 • Thermodynamic modeling of chloroquine solubility at different conditions • Solubility of chloroquine lies between 1.64 × 10−5 to 8.92 × 10−4 (mole fraction).

Design and development of efficient processes for continuous manufacturing of solid dosage oral formulations is of crucial importance for pharmaceutical industry in order to implement the Quality-by-Design paradigm. Supercritical solvent-based manufacturing can be utilized in pharmaceutical processing owing to its inherent operational advantages. However, in order to evaluate the possibility of supercritical processing for a particular medicine, solubility measurement needs to be carried out prior to process design. The current work reports a systematic solubility analysis on decitabine as an anti-cancer medicine. The solvent is supercritical carbon dioxide at different conditions (temperatures and pressures), while gravimetric technique is used to obtain the solubility data for decitabine. The results indicated that the solubility of decitabine varies between 2.84 × 10–05 and 1.07 × 10–03 mol fraction depending on the temperature and pressure. In the experiments, temperature and pressure varied between 308–338 K and 12–40 MPa, respectively. The solubility of decitabine was plotted against temperature and pressure, and it turned out that the solubility had direct relation with the pressure due to the effect of pressure on solvating power of solvent. The effect of temperature on solubility was shown to be dependent on the cross-over pressure. Below the cross-over pressure, there is a reverse relation between temperature and solubility, while a direct relation was observed above the cross-over pressure (16 MPa). Theoretical study was carried out to correlate the solubility data using several thermodynamic-based models. The fitting and model calibration indicated that the examined models were of linear nature and capable to predict the measured decitabine solubilities with the highest average absolute relative deviation percent (AARD %) of 8.9%.

Improving oil recovery and decreasing greenhouse gas emissions are two important attractive features of CO2-enriched water injection into oil reservoirs. Regarding these unique features, the main objective of this study was concentrated to evaluate the swelling behavior of crude oil as a fundamental mechanism of carbonated water (CW) flooding. To achieve these goals, the swelling and Bond number of light and heavy crude oils (namely LCO and HCO, respectively) are measured and compared to each other. The results obtained from the measured swelling factors of crude oil/CW show some complicated behaviors. That is, as temperature increases the swelling factor decreases at low pressure conditions, while at high pressure a reverse trend was observed. In addition, the crossover pressure, which can be contributed to the different swelling behaviors of crude oil for different CO2 contents of water, was shifted to higher pressure for the LCO compared to that for the HCO.

Due to the vast production of crude oil and consequent pressure drops through the reservoirs, secondary and tertiary oil recovery processes are highly necessary to recover the trapped oil. Among the different tertiary oil recovery processes, foam injection is one of the most newly proposed methods. In this regard, in the current investigation, foam solution is prepared using formation brine, C19TAB surfactant and air concomitant with nano-silica (SiO2) as foam stabilizer and mobility controller. The measurements revealed that using the surfactant-nano SiO2 foam solution not only leads to formation of stable foam, but also can reduce the interfacial tension mostly considered as an effective parameter for higher oil recovery. Finally, the results demonstrate that there is a good chance of reducing the mobility ratio from 1.12 for formation brine and reservoir oil to 0.845 for foam solution prepared by nanoparticles.

A feedforward artificial neural network was used to correlate 956 experimentally measured thermal diffusivity data of hydrocarbons and aromatics. A network consisted of one input, one hidden and on...

Accurate estimation of liquid thermal conductivity is highly necessary to appropriately design equipments in different industries. Respect to this necessity, in the current investigation a feed-forward artificial neural network (ANN) model is examined to correlate the liquid thermal conductivity of normal and aromatic hydrocarbons at the temperatures range of 257–338 K and atmospheric pressure. For this purpose, 956 experimental thermal conductivities for normal and aromatic hydrocarbons are collected from different previously published literature. During the modeling stage, to discriminate different substances, critical temperature ( T c ), critical pressure ( P c ) and acentric factor ( ω ) are utilized as the network inputs besides the temperature. During the examination, effects of different transfer functions and number of neurons in hidden layer are investigated to find the optimum network architecture. Besides, statistical error analysis considering the results obtained from available correlations and group contribution methods and proposed neural network is performed to reliably check the feasibility and accuracy of the proposed method. Respect to the obtained results, it can be concluded that the proposed neural network consisted of three layers namely, input, hidden and output layers with 22 neurons in hidden layer was the optimum ANN model. Generally, the proposed model enables to correlate the thermal conductivity of normal and aromatic hydrocarbons with absolute average relative deviation percent (AARD), mean square error (MSE), and correlation coefficient ( R 2 ) of lower than 0.2%, 1.05 × 10 − 7 and 0.9994, respectively.

One of the effective medications for Glioblastoma Multiforme is Temozolomide (TMZ) which is taken as a treatment for some brain cancers. With respect to the importance of this drug in cancer therapy, the solubility of this medicine was analyzed under various ranges of pressure and temperature in supercritical carbon dioxide (SC-CO2) to evaluate the possibility of drug micronization for reducing its undesired side effects. The measurements were conducted using gravimetric method and revealed that the solubility of the drug is between 4.30 × 10−4 to 5.28 × 10−3 based on mole fraction. The results demonstrated the strong dependency of the TMZ solubility to pressure and temperature, while the effect of pressure is more profound at higher temperatures. Besides, the calculated solubility data was correlated employing five popular semi-empirical density-based correlations including Bartle et al., Chrastil, Kumar and Johnston, Mendez-Santiago-Teja, and Garlapati & Madras models. The obtained outcomes illustrated that among the tested models, KJ led to the best correlative ability with average absolute relative deviation percent (AARD %) of 8.39%, while Garlapati and Madras led to the worst modeling results with AARD % of 15.20%.

Particle size and morphology are among the most important parameters which must be precisely controlled in pharmaceutical industries to enhance the effectiveness of the solid dosage oral formulations. One of the most interesting methods for controlling these two quality attributes is supercritical fluid based technologies by which the drug solubility in supercritical (SC) solvent, commonly carbon dioxide, dictates whether the used method is applicable for suitable particle production or not. In this work, solubility of an anti-cancer drug namely tamoxifen in supercritical CO2 was measured under different conditions. The measurements were carried out between 120 and 400 bar pressure, and 308–338 K temperature. The measurements revealed the solubility of about 1.88 × 10−5 to 9.89 × 10−4 (mole fraction basis) for tamoxifen with strong functionality to pressure and complicated functionality to temperature. In details, pressure showed to have a direct effect on solubility, while the effect of temperature depends on existence of cross-over pressure that is about 200 bar for the case of tamoxifen. It was revealed that for the pressures greater than the cross-over point, increasing temperature led to enhancement of the tamoxifen solubility due to sublimation pressure dominanacy, while for pressures lower than cross-over point, density reduction (solvating power reduction) is the dominant mechanism as the temperature enhances. Besides the experimental measurements, the possibility of correlating and extrapolating the measured solubility of tamoxifen as a function of temperature and pressure was investigated using five well-known semi-empirical density-based models including Kumar-Johnston (K-J), Garlapati-Madras, Chrastil, Mendez-Santiago and Teja (MST), and Bartle et al., among which KJ model showed the lowest average absolute relative deviation percent of about 8.26%.

In the current study, the solubility of busulfan which is a chemotherapy drug for treating chronic myelogenous leukemia (CML) is measured in supercritical carbon dioxide (SC-CO2) at pressures between 120 and 400 bar, and temperatures between 308 and 338 K. It was indicated that the solubility of this drug via a static solubility measurement technique coupled with a gravimetric approach was between 3.27 × 10−5 to 8.65 × 10−4 (mole fraction). The measured solubility data reveled the direct effect of pressure on the solubility data, while the temperature has a dual effect of both increasing and decreasing effect considering the shifting point known as cross-over pressure which was measured to be around 160 bar for busulfan. Moreover, a theoretical approach was implemented to predict the solubility data using thermodynamic models. Indeed, five widely used semi-empirical density based correlations namely Kumar-Johnston (KJ), Bartle et al., Mendez-Santiago and Teja (MST), Garlapati and Madras and Chrastil models were used to model solubility data using only pressure, temperature and density of mixture as input parameters. The modeling as well as curve fitting results demonstrated that among the examined models, KJ model introduced more accurate correlative capability with AARD of about 7.57%.

Elimination of carbon dioxide from gas mixtures is a common commercial step in natural gas refineries. Nowadays, room-temperature ionic liquids, which are a relatively novel type of compounds have gained attention in recent years and have potential to be considered as a substitution for conventional volatile organic solvents in reaction and separation processes. No flammability, high thermal stability, a wide liquid range, and electric conductivity are some properties of ILs, which make them interesting more and more. Information about the solubility and the rate of solubility is a crucial factor for consideration of ILs for potential industrial processes. Because of some difficulties associated with experimental measurements and expenses spent on ILs, developing predictive methods for prognostication of the phase behavior of such types of systems are more favorable. Thermodynamic models are relatively complex and require complicated mathematical operations. Due to such difficulties there is a need to develop general models capable to predict phase behavior of systems such as CO2 with various kinds of ILs. In this study, four different methods based on artificial intelligence are proposed to predict CO2 solubility in different ionic liquids. The results showed that the predicted values are in great agreement with the experimental data and the maximum absolute error deviation for the best predictor is no more than 3.5%. A comparison between developed models and previously published ones reveals the superiority of the proposed models in this study.

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 well established that the heavy oil components including asphaltenes and resins play vital roles on the interfacial tension (IFT) of acidic crude oil (ACO) and aqueous solutions. Therefore, this experimental work is designed to investigate the possible synergism between salt ions, resin, and asphaltene on the IFT of ACO/low and high salinity brines containing MgCl 2 /NaCl and CaCl 2 . The results demonstrate that a complex ion of MgCl 2 – resin component created in the solution could occupy the sites at the interface at high MgCl 2 concentration. However, the results show that on the contrary, the molecular arrangement of MgCl 2 and asphaltene at low and high MgCl 2 concentration could be broken as the CaCl 2 is able to hackle the molecular management due to the high affinity of Ca 2+ to asphaltene molecules compared to that of Mg 2+ .

The tunable nature of the solubility of various compounds, including molecules of pharmaceutical and biological interest, in supercritical fluids (SCFs) makes SCF extraction technology attractive for many separation and purification processes. Among the different influencing parameters, the most important one in the supercritical based processes is the knowledge of solubility of model solute. But, experimental measurement of the solubility of all pharmaceuticals in wide ranges of temperature and pressure is not only cost effective but also impossible in some cases. Regarding this fact, during the past decades, several approaches are proposed to model the solubility of the compounds in the supercritical fluids especially carbon dioxide. In this way, in the current investigation, two different approaches including five semi-empirical density based correlations (Mendez-Santiago and Teja (MST), Bartle et al., Chrastil, Kumar and Johnston (KJ) and Hezave et al.) and Peng-Robinson equation of state are used to find if it is possible to correlate the solubility of cetirizine with acceptable deviation as a function of temperature and pressure. The results reveal that among the examined approaches Hezave and Lashkarbolooki model leads to better overall correlative capability with average absolute relative deviation of 5.04% although Peng-Robinson EoS leads to lower AARD % of 3.85 % in 338 K isotherm.

One of the main concerns of each petroleum engineer is the selection of the best EOR method to maximize the oil production from the reservoir. In this regard, one of the explored-not-productive southern Iranian oil fields was considered as the objective of this study to find which enhanced oil recovery (EOR) method is the proper method to apply on this reservoir. Therefore, a procedure capable of combining the data extracted from different sources ranging from worldwide field experiences to the existing tables into a unified expert system is used. This expert system is based on Bayesian network analysis in order to sort the proper EOR techniques for further assessment by economical and environmental criteria. In addition, after collecting of surface samples at the gas and liquid separator, and subsequently recombined with solution gas oil ratio, several tests including constant composition expansion (CCE) (flash vaporization, flash liberation flash expansion, pressure-volume relations), differential vaporization (differential liberation differential expansion) and solubility and swelling tests were performed.

During the past decades, producing micro- and nano-particles of drugs is gaining attention since it is possible to modify the solubility of insoluble drugs in the gastronical fluids significantly. Respect to this fact, in the current investigation, rapid e...

Ionic liquids (ILs) are a new kind of solvents that have recently gained an upsurge in attention in light of their unique potential for different applications. With respect to this, in the present study, applicability of an IL called 1-octadecyl-3-methylimidazolium chloride ([C18mim] [Cl]) as a new class of surfactant was investigated. Different interfacial tension (IFT) measurements were performed to find the effect of IL concentration and temperature on the IFT of water/crude oil system. The observed trend was explained based on mass transfer mechanisms including diffusion and convective mass transfer. In addition, the effect of rotational speed, ranging between 3000 and 9000 rpm, on the IFT was examined with the hypothesis that it can modify the convective mass transfer. Finally, since it has been reported that the Marangoni effect enhances the mass transfer flux in the surfactant solutions, two different methods of IFT measurements including the spinning drop and pendant drop methods were applied to i...

In recent years, using supercritical carbon dioxide for different chemical processes in particular particle micronization has been surprisingly increased. Knowing the substance solubility in supercritical solvent is a critical parameter during the particle size reduction processes. In this direction, solubility of cephalexin was measured in the supercritical carbon dioxide by changing the temperature and pressure between 308.15 K to 338.15 K and 16 Mpa to 40 MPa, respectively. The measured solubility of cephalexin in supercritical carbon dioxide was in the range of 1.13×10-5 to 4.89 ×10-3 based on the mole fraction at the different operational condition. Besides the experimentally measurement of cephalexin solubility, modeling of the results using four commonly used correlations namely Mendez-Santiago and Teja (MST), Bartle, Kumar and Johnston and Chrastil models were performed. The results revealed that the Chrastil model is the most accurate used semi-empirical correlation in the present study with the lowest average absolute relative deviation percent of (AARD %) of 9.43 %.

Microbial enhanced oil recovery (MEOR) process is divided into two main categories, namely in-situ and ex-situ techniques. It utilizes reservoir microorganisms or specially selected bacteria to use their metabolites for more oil recovery from depleted oil reservoirs. In the present study, the potential of two biosurfactant-producing strains of Enterobacter cloacae and Bacillus stearothermophilus SUCPM#14 were investigated on tertiary oil recovery efficiency in carbonated cores using different designed injection protocols. The required operational time, process cost and proper selection of bacterial formulation during the MEOR process were the main objectives of this study. The results of interfacial tension (IFT) measurements demonstrated the capability of E. cloacae to reduce the water/crude oil IFT from 30 to 2.7 mN/m after 24 h cultivation, while B. stearothermophilus SUCPM#14 was able to slightly reduce the IFT from 30 to 15 mN/m in the same period of time. The core flooding tests showed different bacterial formulations using various injection patterns, leading to different oil recovery efficiencies. Besides, the results showed that the required operational time as well as the cost of the process directly affects the design of the MEOR process for a selected reservoir. Based on the performed tests, E. cloacae in most of the MEOR scenarios leads to significant tertiary oil recovery efficiencies. Considering the economical parameters B. stearothermophilus SUCPM#14 demonstrated higher feasibility for in-situ MEOR processes compared to the ex-situ type. The proper design of injection protocols and appropriate selection of bacterial formulation result in considerable amounts of tertiary oil recovery.

Solubility of chlorpheniramine maleate in supercritical carbon dioxide at different temperatures (308–338 K) and pressures (160–400 bar) is measured using static method coupled with gravimetric method. The measured solubility data demonstrated that the solubility of chlorpheniramine maleate was changed between 1.54 × 10−5 and 4.26 × 10−4 based on the mole fraction as the temperature and pressure are changed. The general trend of measured solubility data shows a direct effect of pressure and temperature on the solubility of chlorpheniramine maleate. Finally, the obtained solubilities correlated using four semi-empirical density-based correlations including Mendez Santiago–Teja (MST), Kumar and Johnston (KJ), Bartle et al., and Chrastil models. Although the results of modeling showed that the KJ model leads to the average absolute relative deviation percent (AARD %) of 8.1% which is the lowest AARD %, deviation of other utilized correlations are rather the same.

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%.

Interfacial tension between crude oil and water plays a significant role in enhanced oil recovery. Many researchers seek surfactants to reduce the interfacial tension of crude oil and water that can be applicable in reservoir conditions of high salinity and temperature. The current study introduces the results of using two different families of ionic liquids (ILs) including imidazolium (1-dodecyl-3-methylimidazolium chloride ([C 12 mim][Cl]) and 1-octyl-3-methylimidazolium chloride ([C 8 mim][Cl])) and pyridinium (1-dodecyl pyridinium chloride ([C 12 Py][Cl]) and 1-octyl pyridinium chloride ([C 8 Py][Cl])) for this purpose. Measured IFT values between solutions of ILs and a southern Iranian crude oil reveal that these ILs are successful in reducing the IFT. Unlike traditional surfactants, these ILs are more effective as the salinity increases. Also the measurements revealed that there is a correlation of the IFT of the solutions with salinity and temperature.

Remaining oil after primary and secondary oil recovery processes is the target of enhanced oil recovery (EOR) methods. One of an efficient EOR method is chemical flooding changes several parameters lead to higher oil recovery. One of the parameters can be manipulated by chemical flooding (injection) is reduction of formation brine/oil interfacial tension (IFT). During the past decades, several kinds of chemicals called surfactants have been used to change the IFT of water/crude oil system. The most limitation of these surfactants is their inability to tolerate harsh conditions of salinity (ions). In the present study, functionality of a new kind of ionic liquid-based surfactants, can tolerate harsh condition of salinity, was investigated by measuring dynamic interfacial tension of water/heavy crude oil system. In this direction, 1-dodecyl-3-methylimidazolium chloride ([C12mim] [Cl]) was selected as an ionic liquid (IL)-based surfactant for the experiments and IFT measurements. The effects of salinity, NaCl concentration, temperature and concentration of IL on dynamic interfacial tension of IL solution (water + IL)/heavy crude oil system were examined. The experiments surprisingly revealed that presence of salinity leads to significant reduction of IFT of IL solution/heavy crude oil system. In addition, obtained results showed that IFT of the IL solution/heavy crude oil system was decreased as temperature was increased.

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.

This study was aimed to measure the solubility of carvedilol in the temperature and pressure ranges of 308⿿338 K and 160 bar to 400 bar, respectively. In this direction, a homemade high pressure visual equilibrium cell was used to measure the solubility of carvedilol using a static method coupled with gravimetric technique. The results revealed that the carvedilol solubility was ranged between 1.12 y 10⿿5 and 5.01 y 10⿿3 based on the mole fraction (mole of carvedilol/mole of carvedilol + mole of CO2) in this study as the temperature and pressure was changed. Finally, the results were correlated using four density-based semi-empirical correlations including Chrastil, Mendez⿿Santiago⿿Teja (MST), Bartle et al., and Kumar and Johnston (K-J) models. Results revealed that although the K-J model leads to the lowest average absolute relative deviation percent (AARD %) of 6.27%, but it could not be considered as the most accurate correlation since all the used four correlations introduces AARD % of about 6⿿10% which may be in the same range as the experimental error.

Since the knowledge of pharmaceutical solubilities in the supercritical carbon dioxide is one of the first essential necessities for designing the supercritical carbon dioxide-based processes, solubility of piroxicam a non-steroidal anti-inflammatory drug was experimentally measured. In this regard, a static method coupled with gravimetric method was used to measure the solubility of piroxicam in the supercritical carbon dioxide in temperature and pressure range of 308.15–338.15 K and 16–40 MPa, respectively. The obtained solubility data were in the range of 1.17 × 10 −5 and 5.12 × 10 −4 based on the mole fraction (mole piroxicam/(mole piroxicam + mole CO 2 )) then modeled using four different density based correlations namely Bartle et al., Mendez-Santiago-Teja, Chrastil and Kumar and Johnston models. The results of error analysis revealed that the used correlations were potential to correlate the solubility of piroxicam with minimum and maximum average absolute relative deviation percents (AARD%) of 14.4% and 15.2%, respectively.

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.

The purpose of this study was to measure the solubility of gabapentin in supercritical carbon dioxide at different pressures and temperatures of 16–40 MPa and 308–338 K, respectively. The measured solubility data revealed that solubility of gabapentin was 8.97 × 10 −5 –7.36 × 10 −3 based on the mole fraction in supercritical carbon dioxide at the aforementioned operational conditions. At last, the obtained results were correlated using four density based semi-empirical correlations namely Bartle et al., Mendez-Santiago and Teja (MST), Chrastil and Kumar and Johnston (K–J). The results revealed that according to the obtained average absolute relative deviations (AARD) for the used density based correlations of MST (AARD % = 9.88%), Chrastil (AARD % = 9.47%), K–J (AARD % = 11.5%) and Bartle et al. (AARD % = 9.29%), none of the correlations can be considered as the most accurate one. In other words, all the examined semi-empirical correlations are in the same level of accuracy.

Microbial enhanced oil recovery (MEOR) process utilizes microorganisms or their metabolites to mobilize the trapped oil in the oil formation after primary and secondary oil recovery stages. MEOR technique is considered as more environmentally friendly and low cost process. There are several identified mechanisms for more oil recovery using MEOR processes however; wettability alteration and interfacial tension (IFT) reduction are the important ones. Enterobacter Cloacae, a facultative bio-surfactant producer bacterium, was selected as a bacterial formulation due to its known performance on IFT reduction and wettability alteration. To quantify the effects of these two mechanisms, different tests including oil spreading, in situ and ex situ core flooding, wettability measurement (Amott), IFT, viscosity and pH measurements were performed. The obtained results revealed that the experimental procedure used in this study was able to quantitatively identify the individual effects of both mechanisms on the ultimate microbial oil recovery. The results demonstrated considerable effects of both mechanisms on the tertiary oil recovery; however after a proper shut in time period, more tertiary oil was recovered because of wettability alteration mechanism. Finally, SEM images taken from the treated cores showed biofilm formation on the rock pore surfaces, which is responsible for rock surface wettability alteration.

Extraction of deactivatived materials from contaminated clay soils (Tonsil CO 610 G) by supercritical carbon dioxide was investigated. Effect of different conditions including extraction temperature (308.15–338.15 K) and pressure (100–330 bar) (thermodynamic conditions), flow rate (4.2–42.6 cc/min), and static time (45–85 min) were investigated to find the optimum conditions for extraction of deactivatived materials. Based on the different experiments, optimum conditions for flow rate (4.2 cc/min), static time (85 min) and extraction pressure and temperature (330 bar and 313.15 K) were obtained. In addition, the GC-MS analysis and Bromine index (BI) analysis were revealing that the clay soil is activated and could be used as catalyst again.

It is estimated that two-thirds of crude oil remains in the oil reservoirs after primary and secondary (water flooding) recovery stages. The extent of residual oil trapped in the reservoir pore structure is dominated by capillary and interfacial forces. The residual oil will be mobilized if the capillary forces are reduced because of interfacial tension (IFT) reduction during surface active agents flooding into the oil reservoir. In this work, 1-dodecyl-3-methylimidazolium chloride ([C 12 mim] [Cl]) is proposed as the IFT reducing agent and its dynamic IFT with one of the Iranian crude oil under different conditions were examined. The obtained results revealed that the critical micelle concentration (CMC) between the crude oil and formation brine was obtained at a very low concentration of 100 ppm. Unlike to the traditional surfactants, this ionic liquid based surfactant found to be more effective for higher saline formation water. In addition, several core flooding experiments were performed to find both, tertiary oil recovery efficiency and IL adsorption on the rock surfaces which indicated promising results.

Present work investigated the potential of artificial neural network (ANN) model to correlate the bubble and dew points pressures of binary systems containing carbon dioxide (CO2) and hydrocarbon systems as functions of reduced temperature of non-CO2 compounds, critical pressure, acentric factor of non-CO2 compounds and CO2 composition. In this regards, five binary systems at the temperature and pressure ranges of 263.15–393.15 K at 0.18–12.06 MPa were used to examine the feasibility of cascade-forward back-propagation ANN model. In this regard, the collected experimental data were divided in to two different subsets namely training and testing subsets. The training subset was selected in a way that covers all the ranges of the experimental data and operating conditions. Then, the accuracy of the proposed ANN model was evaluated through a test data set not used in the training stage. The optimal configuration of the proposed model was obtained based on the error analysis including minimum average absolute relative deviation percent (AARD %) and the appropriate (close to one) correlation coefficient (R2) of test data set. The obtained results show that the optimum neural network architecture was able to predict the phase envelope of binary system containing CO2 with an acceptable level of accuracy of AARD % of 2.66 and R2 of 0.9950 within their experimental uncertainty. In addition, comparisons were done between the Peng–Robinson (PR) equation of state (EOS) and ANN model for three different binary systems including CO2 + 1-hexene, CO2 + n-Hexane, and CO2 + n-butane. Results show that developed optimal ANN model is more accurate compared to the PR EOS.

Phenylephrine is used as a decongestant sold as an oral medicine, as a nasal spray, or as eye drops. Phenylephrine is now the most common over-the-counter decongestant in the United States. In this regard, measuring the solubility of phenylephrine hydrochloride seems applicable in supercritical carbon dioxide-based processes dealing with this drug. The obtained solubility data obtained by a static method coupled with gravimetric method were in the range of 1.01 × 10 −4 to 2.89 × 10 −3 based on the mole fraction at the different temperature and pressure ranges of 308.15–338.15 K and 160–400 bar, respectively. In addition, the solubility data were used to obtain the adjusting parameters of semi-empirical correlations namely Kumar and Johnston, Bartle et al., Chrastil and Mendez-Santiago-Teja using a simple data regression.

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.

Supercritical extraction (SE) is a separation technique utilizes near or above critical properties of the solvents. In this technique, modeling of yield and solubility of materials are crucial points in supercritical fluid extraction processes. Generally, mathematical modeling of the supercritical oil extraction is a very difficult task since a highly nonlinear relation exists between process variables and solubility. Considering these facts, in the present study, a trainable cascade-forward back-propagation network (CFBPN) was proposed to correlate the yield of spearmint oil extracted by supercritical carbon dioxide. The results revealed the applicability of the proposed model to correlate the yield of spearmint oil extraction with an acceptable level of accuracy. Finally, the obtained results were compared to mathematical models namely Goodarznia & Eikani and Kim & Hong. The comparison between the results of proposed network and mathematical models demonstrated a better predictive capability of the proposed network.

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 this study, the rapid expansion of supercritical solution (RESS) process was used to precipitate fine solid particles of amoxiccilin where supercritical carbon dioxide was used as a solvent. The process has been done by changing the RESS parameters, including extraction pressure (150–210 bar), extraction temperature (313–333 K), nozzle length (2–15 mm), effective nozzle diameter (450–1700 µm), and spraying distance (1–10 cm), to investigate the effect of these parameters on the size and morphology of the precipitated amoxicillin particles. The characterization (size and morphology) of the particles was examined using scanning electron microscopy (SEM). Based on the different experimental conditions, the mean particle size of the fabricated particles were between 1.08 and 5.72 µm, while the intact particles of amoxicillin were about 41.46 µm. Also, no regular changes in the morphology of the processed particles were observed.