Iranian Journal of Chemical Engineering (IJChE)

Abstract Natural gas (NG) is one of the cleanest and safest sources of energy transmitted in a high pressure that must be reduced before entering City Gas Station (CGS). Identifying the effective parameters in creating the hazardous areas of CGS is essential to crisis and management. This study using PHAST version 7.11(created by DNV Company) conducted a consequence modelling in three scenarios at three CGS stations in Qazvin Province, by actual data including weather conditions, gas pressure and temperature. The main results for the modeling in all three scenarios were jet fire, flash fire, and explosion. Based on the modeling results, most flame length was obtained in Avaj station with 10 meters more than others. Most radiation levels were also in Avaj station in about 150 m downwind distance, which can be caused by the longer flame length in this station.
The results showed that in fire jet modeling, an increase in air temperature can lead to an increase in gas pressure and temperature, which in this study increased the flame length of 2 to 3 meters. However, the flame length and the hazardous area was higher during the day and summer. The use of PHAST modeling software can provide useful information including high-risk operational area, hazard area, high-risk time period (day, night and season) for the management team to respond to emergency situations in process industries. In addition, it is necessary to consider the combination of different operating parameters such as gas pressure and gas temperature with different weather conditions.

Abstract The study examines the operational lifespan and catalytic efficiency of the acetylene hydrogenation reactor at Amirkabir Petrochemical Company in Iran, a critical component in industrial olefin production. Acetylene, an undesirable by-product in olefin synthesis, adversely impacts profitability and polymer product quality. To mitigate these effects, the acetylene concentration in the feed stream must be reduced to below 0.5 ppm through catalytic hydrogenation. However, excessive conversion leads to ethane production, thereby reducing ethylene yield. This research uses a modeling approach, supported by industrial data, to investigate the reactor’s behavior under various conditions. A major focus is placed on the reaction kinetics to optimize operational parameters and minimize ethane production, which is less desirable than ethylene. The analysis includes key variables such as temperature, pressure, and the hydrogen-to-hydrocarbon ratio. Moving average method was used to smoothing 78 operational data in this work. Results showed the average absolute selectivity is less than 10%. Additionally, the study evaluates the role of carbon monoxide (CO) as a selective agent that enhances ethylene yield while reducing operational risks. The results showed that the main conversion takes place in the beginning of the reaction (first 1 m of the bed). Additionally, findings indicate that optimal management of these parameters can greatly improve reaction selectivity and the efficiency of the hydrogenation process. The results provide significant insights for refining practices in acetylene hydrogenation, suggesting strategies for improving product quality and operational efficiency in the petrochemical industry.

Abstract In this research, the methods of oxidation, oxidation along with carbon nanotubes and surface absorption of carbon nanotubes were investigated to remove the drug substance of cefixime from aqueous solutions. In these methods, the removal percentage of cefixime was 78%, 96% and 70% respectively. Therefore, the results showed that oxidation with carbon nanotubes had a positive effect on the removal of cefixime. For this reason, oxidation along with carbon nanotubes was used to remove the cefixime. Next, different operating parameters such as the concentration of drug pollutants (20,30,40 and 55ppm), reaction time (5,10,15,20,25 and 30 min), concentration of hydrogen peroxide (1, 3 and 5ml) and amount of carbon nanotubes (0.05, 0.01 and 0.2 g/l) were studied in the removal process of cefixime using the method of  oxidation along with carbon nanotubes. It should be noted that in all experiments, certain amounts of carbon nanotubes and the oxidizing agent of hydrogen peroxide were used. In addition, a mixer, with a given round, was used to mix the materials. The maximum removal efficiency of cefixime from aqueous solutions is about 96% , which is related to the process of the removal of cefixime at the constant concentration of 55 mg/L by 0.1 g/L of carbon nanotubes and 5ml of hydrogen peroxide at the  t = 30 min.

Abstract Conventional plastics have been a significant source of the environmental pollution, prompting considerable research into the development of biodegradable plastics using biological methods. Poly (3-hydroxybutyrate-co-3-hydroxyvalerate) has garnered particular attention due to its unique properties, including high flexibility and resistance to organic solvents. It has been demonstrated that certain microorganisms possess the intracellular capability to synthesize this biopolymer from organic waste. This study investigates bacteria that have been isolated from the municipal landfill of the Kermanshah Waste Recycling and Organic Fertilizer Production Company. Among the isolates, a strain capable of synthesizing biopolymers, exhibiting high similarity to the genus Stenotrophomonas geniculata strain Flmat 1, was identified via 16S rRNA gene sequencing. In order to verify the production of the biopolymer, Fourier-transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1H-NMR) analyses were employed. The results have shown that the isolated bacteria is capable of producing PHBV from unrelated carbon sources from waste food and producing 2.835 g/L biopolymer with the yield of 0.52 g PHBV per gram of CDW using waste food, at the pH of 9, temperature of 33°C, concentrations of 13.25 g/L and 27.71 g/L of nitrogen and glucose respectively.

Abstract In this study, carbon nanotubes were fully aligned by chemical vapor deposition at atmospheric pressure on a silicon substrate at two carbon source flow rates of 28 and 38 sccm (standard cubic centimeter per minute). Acetylene gas (C₂H₂) as the carbon source for argon gas (Ar) as the carrier gas for hydrogen gas (H₂) for the recovery of the nanoparticle and iron nanoparticles as the catalytic source at 800 °C were used for the growth of the carbon nanotube array. The reaction was carried out in a 48 cm long quartz tube and the gases were injected with specified flow rates. The silicon substrate was coated by the magnetic sputtering method with catalytic iron nanoparticles with a thickness in the range of 3-6 nm. The results of the FESEM analysis showed, as the carbon source flow rate was increased to 38 sccm, the average diameter of the grown carbon nanotubes is increased, and the carbon nanotubes with a diameter of 60-70 nm were most abundant.

Abstract The goal of this study was to examine the morphology and characteristics of a blend of polylactic acid (PLA) with thermoplastic corn starch (TPS) and polyethylene glycol (PEG-400) using the extrusion process. The blends were evaluated through the tensile and impact strength tests, scanning electron microscopy (SEM), and X-ray diffraction (XRD) analysis. The experimental design method was selected to quantitatively analyze the influence of the content of TPS and concentration of the plasticizer on mechanical properties. Results from the tensile test showed that the addition of PEG-400 decreased tensile strength and elastic modulus, but increased elongation at break and impact strength, significantly. The blend with 20% TPS and 20 phr PEG-400 had the best overall performance in terms of tensile strength, elastic modulus, elongation at break, and impact strength. The SEM analysis indicated increased incompatibility and phase separation in samples with 40% TPS. Additionally, at high concentrations of PEG-400, the excessive plasticizer caused polymer saturation, resulting in unabsorbed plasticizer and phase separation. The findings suggest that the blend with 20% TPS and 20 phr PEG-400 could be suitable for use in eco-friendly applications.

Abstract One of the effective catalysts for hydrogen purification and production via medium temperature shift reaction, is Cu-Ce solid solution. Cu0.1Ce0,9O1.9 was produced using co-precipitation method and then was utilized as support for 5Cu/Ce0.9Cu0.1O1.9 catalyst which was synthesized employing wet impregnation method. X-ray diffraction (XRD) analysis showed that crystalline sizes of Ce0.9Cu0.1O1.9 and 5Cu/Cu0.1Ce0,9O1.9 were 9.22 and 18.33 nm, respectively. The Catalysts were evaluated in medium temperature shift reaction at 300-390 °C and at gas hourly space velocities (GHSV) of 12000 and 30000 h-1, in a fixed bed reactor. Due to higher concentration of Cu and synergic positive effects of both active metal and support, 5Cu/Cu0.1Ce0,9O1.9 catalyst showed better performance. It was also concluded that, because of low residence time at high levels of GHSV, increasing GHSV leads to decrease CO conversion. Then 5Cu/Cu0.1Ce0,9O1.9 was evaluated in microchennel reactor in 2 GHSVs of 12000 and 30000 h-1 and results were compared with the fixed-bed reactor. It can be concluded that microchannel reactor is better in higher GHSVs (lower residence time of gas flow). A microchannel reactor provides a high surface-to-volume ratio and gases pass over the thin layer of catalyst on the coated plates. Hence, due to the better access to the catalytic bed, the reactants react even in a short time, which improves the microchannel performance compared to the fixed bed reactor

Abstract This study investigated sarin gas dispersion in an indoor environment using transient three-dimensional Computational Fluid Dynamics (CFD) and Artificial Neural Network (ANN) approaches. To achieve this, the CFD model was first verified and validated. Then, random locations in the indoor environment were considered as inlets of airflow with sarin gas, and the dangerous times were calculated using the CFD model. Finally, these results of the CFD model were used as inputs to train the ANN model. The results of this study demonstrated that the present model exhibited strong agreement with experimental data. Also, the results of training the ANN showed that for all sections, the training, validation, and testing data and model results were consistent with a high R-squared value. Moreover, the results of different air inlet locations showed that if the air inlet was placed in the corner sections of the indoor environment, the danger time increased. Additionally, if the air inlet was placed near the open region, the danger time also increased, which is an important result for designing indoor environments.

Abstract The Micromixing plays a key role in the most of industrial processes; enhancing its efficiency is a very important issue. In this study, a typical rotating packed bed (RPB) reactor equipped with the blade packing and high frequency ultrasonic transducers were designed to study the micromixing efficiency using the iodide/iodate reaction. The utilized ultrasonic transducers were ultrasonic atomizer humidifiers with the frequency of 1.7 MHz. Taking advantage of both the controllable high gravitational force and induced effects of the high frequency ultrasound, simultaneously, in a small volume reactor is the novelty of the present work. The effects of different parameters like the rotational speed, volumetric ratio, concentration of acid, ultrasonic power and number of activ transducers were investigated with and without the ultrasonic field. By increasing the rotational speed and volumetric flow, the segregation index decreased and by increasing the concentration of acid and volumetric ratio, the segregation index increased. In all of experiments, the segregation index decreased significantly under the ultrasonic field. Moreover, by increasing the ultrasonic power and number of active transducers the segregation index decreased. The obtained results indicated that the relative segregation index increased up to 41.1 % under the 1.7 MHz ultrasonic field. Therefore, the high frequency ultrasonic waves can intensify micromixing, even in a high efficiency equipment like RPB

Abstract The optimization of membrane bioreactor (MBR) equipped with a submerged flat-sheet polyethersulfone (PES) membrane for the wastewater treatment from dairy processing facilities was investigated. The effects of key parameters such as the hydraulic retention time (HRT, from 8 to 16 hr), mixed liquor suspended solids (MLSS, 3000 to 9000
mg/L), and rate of aeration (Qair: 1 and 2 L/min) on COD removal efficiency were systematically investigated. Through the response surface method (RSM), the maximum the COD removal efficiency of 92.67% was obtained under the optimal conditions of HRT: 13.83 hr, MLSS: 7239.84 mg/L, and Qair: 1.75 L/min. The statistical analysis identified MLSS as the most influential factor in the COD removal efficiency, accounting for 30% of the variation, followed by HRT with
16%, and the rate of aeration showing the least impact of 8%. A notable reduction in the UV absorbance of wastewater between 200 and 500 nm, after treatment using MBR under optimal conditions, signified successful targeting of toxic or colored pollutants. Finally, a mechanism for the wastewater treatment in MBRs, which included the biological degradation, adsorption on the surface of biomass and membrane, and separation through membrane filtration, was proposed.

Abstract Optimization of the homogeneous rhodium-catalyzed methanol carbonylation reactor to reduce CO2 emissions is studied in this line of research. In this paper, the steady-state homogeneous rhodium-catalyzed methanol carbonylation reactor is simulated using Aspen HysysV.9 software, by comparing the simulation results with industrial information, a mean relative error (excluding methanol) of 4.8% was obtained, which indicates the high accuracy of the simulation. The central composite design (CCD) and genetic algorithm (GA) with the aid of a simplified process simulation were used to estimate the effect of individual variables (liquid level, the temperature of the catalyst-rich recycle stream, the mole ratio of CO to methanol (MeOH) in the feed, and flow rate of dilute acid stream) and their mutual interactions to reduce CO2 emissions. It is obtained that the liquid level percentage of 46%, the catalyst-rich recycle stream temperature of 120 °C, CO: MeOH molar ratio equal to 1.13:1, and the dilute acid flow rate of 513.14 kmol/hr lead to CO2 reduction by 34%.

Abstract 1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX) is one of the most powerful explosives of which the purity may have a significant effect on increasing the performance of rocket engines. In this research, the synthesis of high purity HMX is presented using the nitration of 1,5-diacetyl-3,7-dinitrooctahydro-1,3,5,7-tetrazocine (DADN) with a mixture of nitric acid and polyphosphoric acid. The nitration parameters including temperature, time, and the concentration of nitric acid, and polyphosphoric acid were optimized for the desirable purity and efficiency using the response surface method and central composite method (CCD). Based on the optimization, HMX was obtained with a purity of 99% and an efficiency of 92.9% at a temperature of 70°C and the time duration of 70 minutes with a molar ratio of polyphosphoric acid to nitric acid of 1:1:6.

Abstract Centrifugal pumps are extensively employed in mining, petrochemical, and wastewater treatment industries, where handling solid–liquid two-phase flows often results in the erosive wear of internal components. This study investigates slurry-induced erosion in a single-stage centrifugal pump through a three-dimensional CFD model developed in COMSOL Multiphysics. The model integrates Lagrangian particle tracking with an empirical erosion correlation and is validated with experimental data reported in the literature, showing good agreement with an average relative error of below 5%. Parametric simulations were conducted to examine the effects of two key operating parameters: flow rate and particle concentration. The results indicate that at sub-design flow rates, the prolonged particle residence time increases impact frequency, leading to severe localized erosion near the blade leading edges. Conversely, operating at rates close to the design flow rate and up to 1.4 Qd reduces erosion intensity and promotes a more uniform wear distribution. Increasing particle concentration produces a nearly linear rise in the maximum erosion rate—from approximately 3 mm/year at 0.5% to over 22 mm/year at 3%—while also expanding the affected blade area. Moreover, larger particles intensify erosion severity and shift erosion zones toward the downstream blade regions, altering the wear mechanism. Overall, the validated CFD framework provides a robust and predictive tool for evaluating both erosion intensity and spatial distribution in slurry-handling centrifugal pumps. The findings emphasize the importance of optimizing operational parameters and applying wear-resistant materials to enhance pump durability and reduce maintenance costs. 

Abstract During the regeneration-coupling process, a novel, plantwide control framework for the diethyl oxalate production unit is provided in this article. This study's benefit is that it uses process improvements that do not possess the intricacy and expense of the two prior structures described by Zhu and Luyben. The development of a plantwide control structure for this process was completed in two stages. The efficiency of the process was initially evaluated using a straightforward structure, with the primary goal being to prevent the usage of concentration controllers and complex cascading mechanisms to the greatest extent feasible. Due to the presence of persistent variations in the process effluents in the original structure, it was determined that there were numerous disruptions present that influenced the response during both recycle streams in the process and created variations. During the second phase, using trial and error to implement a functional adjustment in the process, the minimum amount of recycle stream during which the variations were fully removed was separated from the process, and a novel feeding stream was inserted. Following implementing these modifications, it was discovered that the effluent variations of the process are fully removed with just two concentration controllers, and this structure demonstrates instantaneous plantwide control over receiving disturbances.

Abstract The Fe3O4/MW-CNT composite was prepared for a hybrid photo-catalyst-assisted electrochemical process for the removal of BTX contamination from wastewater. Oxidation of multi-walled carbon nanotube was conducted by different treatments including acid treatment and hydrogen peroxide. The XRD, FTIR, SEM, TEM, and BET analyses were performed to characterize both the MW-CNT and the synthesized composite. Simultaneous photo-catalyst and electrochemical processes were conducted to evaluate the performance of a new hybrid process for wastewater treatment. The effect of current density, photo-catalyst loading, and BTX initial concentration was investigated experimentally. The characterization results of the synthesized composite show that a mixture of strong nitric acid and sulfuric acid treatment at a high exposure time and low temperature is the best route for MW-CNT oxidation. The removal efficiency of BTX compounds from wastewater using the hybrid photo-electrochemical process was found to be in the range of 28 to 43% for different conditions. The optimum condition for maximum removal of BTX was found by mathematical modeling of experimental data. The results indicate that a combination of photo-catalyst and the electrochemical process can enhance the BTX removal efficiency.

Abstract The application of the agro-industrial waste as the feedstock helps to decrease the operational cost of the fermentation process. Soapstock is a by-product of the vegetable oil refinery and enriched with fatty acids including linoleic acid which has a high potential application in the production of biosurfactants. In this study, a dual carbon source system, including glucose and free fatty acids recovered from a sunflower soapstock, was used for the synthesis of sophorolipid (SL) by Candida catenulata. The production of SL showed a major dependence on the initial carbon sources and the concentration of urea as the nitrogen source. The inoculum size was another influential factor in the fermentation process. The optimization of these factors was evaluated by the one-factor-at-a-time and the response surface methodology (RSM). The one-factor-at-a-time approach gained the best SL productivity (Y₁) of about 52.08 mg L^-1 h^-1 and SL-to-biomass yield (Y₂) of 712 mg_SL g_cell^-1 at the inoculum size of 4% vv^-1, 100 g L^-1 of glucose, 80 g L^-1 of soapstock, and 7.5 g L^-1 of urea. While the RSM, due to considering interactional effects of the factors, obtained the best condition at 100 g L^-1 of glucose, 100 g L^-1 of the soapstock, 9.3 g L^-1 of urea, and an inoculum size of 6.3% vv^-1 with the Y₁ and Y₁ values of about 58.10 mg L^-1 h^-1 and 713 mg_SL g_cell^-1, respectively. The characterization of the produced SLs by the GC-MS analysis indicated that a di-acylated C16:1 acidic sophorolipid with an m/z ratio of 679 amu was the main product.

Abstract To reduce water production from oil and gas reservoirs, it is necessary to block certain fractures and layers of hydrocarbon formations. Although polymer gels are employed as water shut-off agents to reduce water production, they face challenges due to inefficiencies. This study aims to examine silicate-polymer gels, based on the factors influencing the formation of gel by focusing on controlling the gelation time of the silicate-polymer gelants at various temperatures and investigating the stability of gels. An experimental design was conducted based on 5 levels and 2 parameters, where these two parameters are the concentration of the polymer ranging from 0.06% to 0.3% by weight and the temperature ranging from 20 to 100 degrees Celsius in the presence of a crude oil from the southwest of Iran. Experimental results indicated that citric acid successfully covered the ions and effectively controlled the gelation time. Sodium silicate proved to be one of the main components, along with formation water, citric acid to mitigate the impact of formation ions on the gelation time, and the polymer itself. The presence of formation water led to an increase in gel strength and a decrease in the gelation time. Moreover, elevated temperatures resulted in shorter gelation times and lower viscosity in the polymer gel. Doubling the concentration of the polymer reduced the gelation time by 43%, while a two-fold increase in temperature decreased it by 54%. Increasing the concentration of the polymer indicated a decrease in the gelation time, and an increase in both gel strength and gel viscosity.

Abstract Considering the high number of ionic liquids (ILs) and impracticability of laboratory measurements for all ILs’ properties, applying theoretical methods to predict the properties of this large family can be very helpful. In the present research, ILs’ thermophysical properties are predicted by a combination of statistical associating fluid theory and group contribution concept (SAFT-γ GC EoS). The studied ionic liquids are 1-ethyl-3-methylimidazolium trifluoromethanesulfonate ([emim][CF3SO3]), 1-butyl-3-methylimidazolium trifluoromethanesulfonate ([bmim][CF3SO3]), 1,3-dimethylimidazolium methylsulfate ([mmim][MeSO4]), 1-ethyl-3-methylimidazolium methylsulfate ([emim][MeSO4]), 1-butyl-3-methylimidazolium methylsulfate ([bmim][MeSO4]), 1-ethyl-3-methylimidazolium methanesulfonate ([emim][MeSO3]) and 1-ethyl-3-methylimidazolium ethylsulfate ([emim][EtSO4]). The thermophysical properties including coefficient of thermal expansion, coefficient of thermal pressure, coefficient of isentropic compressibility, coefficient of isothermal compressibility, speed of sound, isochoric and isobaric heat capacities are estimated within broad ranges of pressure and temperature (0.1-60 MPa and 273-413 K). The comparison among the SAFT-γ predictions and some available experimental data show good ability of SAFT-γ EoS to estimate the ILs’ second-order derivative thermophysical properties.

Abstract In this paper, modeling approaches were given for explaining mass transfer during solid-liquid extraction in continuous fixed, expanded, and fluidized-bed extractors. The first approach utilizes a differential mass balance-based model, focusing on the differential mass conservation within an element of fixed and expanded-bed columns. The second approach employs a model by applying a mass balance concept to a control volume of the fluidized-bed column. The differential mass balance method segments the column into well-mixed stages, with the fluid flowing axially in an ideal plug flow regime. The solute diffusion inside the porous particles is modeled using Fick's second law of diffusion. Modeling parameters like the effective diffusivity and equilibrium concentration were estimated using the batch extraction experiments. These models were developed and validated using experimental column data involving the extraction of potassium bicarbonate from polyamide 6 pellets with distilled water as the solvent. The modeling results show a good agreement with experimental data.

Abstract Polymer nanocomposites reinforced with multi-walled carbon nanotubes (MWCNTs) offer promising mechanical performance; however, predicting their tensile modulus remains challenging due to the complex interplay of multiple factors such as filler content, functionalization, and interphase quality. In this study, a dataset of 229 samples was compiled from the literature, augmented via cubic spline interpolation to 4,933 training points, and analyzed using six machine learning models, including SVR, Random Forest, Gradient Boosting Regressor, XGBoost, KNN, and Artificial Neural Networks (ANNs). The inclusion of the interphase modulus (Ei), calculated via an extended Ji model, proved critical for improving prediction accuracy. Among all models, Gradient Boosting Regressor and XGBoost achieved the best predictive performance (Test R² = 0.9868 and 0.9837, respectively), while ANN demonstrated competitive accuracy (Test R² = 0.9703) but higher sensitivity under cross-validation (Mean CV R² = 0.7486). Feature importance analysis using SHAP further confirmed the significant contribution of Ei to prediction outcomes. Overall, this work demonstrates that incorporating physically-informed features like interphase modulus, combined with robust machine learning pipelines, can substantially enhance the predictive modeling of nanocomposite mechanical properties, providing a valuable tool for material design and optimization.

Abstract Current research has simulated polymer oxide/metal oxide nanofibers (nanocomposites) through the COMSOL Multiphysics software. The oil was placed inside a cylindrical tank covered with a thin layer of phase change material nanocomposites. A combination of polyethylene glycol (PEG) as a the phase change material (PCM) and polyamide 6 (PA6) as a support matrix for nanofibers were used. The effect of some parameters such as the type of metal oxide nanoparticles (Al₂O₃, Fe₂O₃, TiO₂, and CuO), the ratio of metal oxide to polymer (2% and 8% by weight), and time (600 and 4800 s) on some thermophysical properties such as changes in temperature, density and thermal conductivity were investigated. The simulation results showed that the most suitable system for thermal management is related to the presence of nanoparticles and PCM with the highest weight percentage. It was also found that the use of the nanofibers of phase change materials is very effective in improving thermal management and temperature control. As a result, they can be used as suitable materials for storing and transferring energy. The addition of 8% nanoparticles led to a 22.5% increase in thermal conductivity. Also, by providing the same initial and boundary conditions for all cases, the amount of melting in the presence of nanoparticles with a high percentage (8%) was higher than the with a low percentage (2%). As a result, the addition of nanoparticles to increase the melting rate can be very useful for various heat management purposes such as energy storage.

Abstract This paper presents a machine learning-based approach for accurately predicting pyrolysis product yields. Methods such as Linear Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Support Vector Regression (SVR), Random Forest (RF), and Neural Networks (NN) leverage operating conditions and/or ultimate/proximate analysis data, eliminating the need for reaction kinetics. This innovative approach offers a broader range and higher accuracy of feedstock compared to traditional kinetics-based methods. The KNN model demonstrated superior performance, achieving a correlation coefficient greater than 0.998 and an RMSE of 0.64. These findings provide valuable insights for engineers and practitioners, facilitating the efficient design and operation of pyrolysis units.The selectivity exhibited a notable increase from 2.46 to 5.27. This improvement in selectivity can primarily be attributed to the significantly higher increase in the solubility coefficient of CO₂ compared to that of CH₄.

Abstract This study investigates the performance of an electrodialysis metathesis (EDM) process using polyvinyl chloride/carbon nanotube (PVC/MWCNTs) nanocomposite ion-exchange membranes (IEMs) for simultaneous water desalination and chemical production. IEMs, with MWCNTs loadings of 0% (M1), 4% (M2), 8% (M3), and 10% (M4) by weight, were fabricated and characterized for water sorption, areal electrical resistance, hydrophobicity, and mechanical strength. Their ion selectivity, separation performance, desalination efficiency, and production yield were systematically evaluated under varying applied voltages, feed compositions, and operation times. Among the fabricated membranes, M3 (8 wt% MWCNTs) exhibited the best performance, providing optimal ionic conductivity, selectivity, and structural stability. The maximum chemical yield was achieved when the solute concentrations in the electrode chambers exceeded those in the desalination chamber. In contrast, M4 (10 wt% MWCNTs) showed reduced efficiency, attributed to the agglomeration of MWCNTs and pore blockage that hindered ion transport. Increasing voltage improved ion transport to the optimal level, but excessive voltage (15 V) caused water splitting and concentration polarization, lowering both chemical yield and desalination efficiency. These results highlight the importance of optimizing MWCNT loading and controlled operating conditions. Overall, PVC/MWCNT composite IEMs exhibited significant potential for integrated chemical production and the treatment of saline wastewater, providing a cost-effective and scalable strategy for resource recovery.

Abstract In this research, silica gel as a low-cost adsorbent for the uptake of carbon dioxide was investigated experimentally. The samples were characterized by XRD, BET and FT-IR. It shows that as pressure was increased from 2 to 8 bar, the CO2 adsorption capability improved over time. At a pressure of 6 bar and a dose of 1 g of silica gel, the impact of temperature (25, 45, 65, and 85 °C) on the CO2 adsorption capacity (mg/g) was determined. The process behavior was investigated using isotherm, kinetics and thermodynamic models. As the temperature rises at a constant pressure, the adsorption capacity decreases. The experimental data of the carbon dioxide adsorption using silica gel have a high correlation coefficient with both Langmuir (0.998) and Freundlich (0.999) models. The results of the carbon dioxide adsorption kinetics with the silica gel adsorbent show that the correlation coefficient (R2) of the second-order model and Ritchie's second model are equal to 0.995 and have the highest value. The total pore volume was 0.005119 (cm3 g-1) and the specific surface area was 2.1723 (m2g−1). The maximum CO2 adsorption capacity at 25 °C near 8 bar was 195.8 mg/g.

Abstract Polymeric gels can be injected into reservoirs to regulate fluid dynamics and enhance oil recovery by creating physical barriers to redirect water flow. In this study, a polymer gel system was developed using sulfonated polyacrylamide combined with chromium acetate. Silica nanoparticles were synthesized via the sol-gel method, and their effects on the polymer gel system, including the gelation time and gel strength, at the concentrations of below 1% weight were evaluated through the bottle test. The performance of the polymer gel containing silica nanoparticles and the silica nanoparticle gel in formation waters was assessed. Furthermore, homogeneous microscopic models and heterogeneous two-layer microscopic models, which included regions with high and low permeability, were constructed to evaluate the functional effectiveness of the polymer gel and silica nanoparticle gel in porous media environments. Factors influencing oil recovery were examined in relation to the volume of injected pore water. The results indicated that silica nanoparticles enhanced the gel strength and increased its swelling capacity under saline conditions. Microscopic model testing in both homogeneous and heterogeneous configurations demonstrated that the silica nanoparticle gel provided better blockage in high-permeability regions and fractured zones, compared to the polymer-only gel. In the heterogeneous microscopic model, oil production rates were 55.60% for the polymer gel and 57.21% for the silica nanoparticle gel, while in the homogeneous model, these rates were 62.6% and 68.24%, respectively.