Iraqi Journal of Chemical and Petroleum Engineering
The Iraqi Journal of Chemical and Petroleum Engineering is a quarterly peer-reviewed scientific journal that was established in 2000 by the College of Engineering / University of Baghdad. The Iraqi Journal of Chemical and Petroleum Engineering receives citations in the category of Chemical /Petroleum Engineering and relevant subjects.
University of Baghdad/ College of Engineering
Studying the effect of different parameters on the oxidation desulfurization of diesel fuel using Fe2O3-NiO/SiO2 bimetallic catalyst: Experimental and kinetic models
Given the environmental and health risks posed by sulfur pollutants, their removal and the production of lower sulfur hydrocarbon fuels are essential. Therefore, oxidative desulfurization (ODS) technology has become crucial as it operates efficiently under moderate conditions. This study focused on the synthesis of a (Fe₂O₃ + NiO)/SiO₂ catalyst via incipient wetness impregnation, followed by drying at 120°C and calcination at 600°C. Several tests were performed on the catalyst before its application: BET, TGA, and SEM-EDX. The BET results showed a decrease in surface area from 166.47 to 149.57 m² g⁻¹ after metal loading, confirming the fixation of iron and nickel oxides on the silica support. XRD and FTIR analyses confirmed the formation of the metal oxide phases Fe₂O₃ and NiO, while preserving the amorphous nature of the silica. The prepared catalyst was tested in ultrasonic oxidative desulfurization of real diesel fuel containing up to 2018.14 ppm using hydrogen peroxide as the oxidizing agent. Various conditions were investigated, including the effect of temperature (25–75°C), reaction time (30–60 minutes), and ultrasonic intensity (80–100%). This was followed by ethanol extraction at a 1:1 diesel-to-solvent ratio. A sulfur removal efficiency of 90% was achieved. The study showed that the reaction followed a pseudo-first-order model with reaction rate constants of 0.0172, 0.0252, and 0.0400 min⁻¹ at 25, 50, and 75°C, respectively, with R2 =0.98. The activation energy of the reaction was also calculated and found to be 14.50 kJ mol⁻¹, indicating the suitability of the kinetics and the efficiency of the catalytic activity under the influence of ultrasonication.
oxidative desulfurization (ODS); diesel fuel; silica supports; ultrasonic reactor; Kinetic parameters
Copyright (c) 2026 The Author(s). Published by College of Engineering, University of Baghdad. https://creativecommons.org/licenses/by/4.0/
Synthesis of nanoporous SnO2 anode by anodization in a rotating cylinder configuration
Nanoporous-SnO₂ films were electrochemically prepared via anodizing of metallic tin electrodeposited on a cylindrical copper substrate using rotating cylinder electrode Technique. The effects of anodizing potential (4-7V), oxalic acid (OA) concentration (0.1-0.5M), time (10-20), and rotation speed (150-450 rpm) on the electrochemical activity of SnO2 as an anode in degrading methylene blue (MB) were investigated. Results showed that increasing oxalic acid concentration gives better performance in degrading MB while increasing anodizing potential enhanced the electrode activity up to a potential of 5 V beyond which no enhancement of electrode activity towared MB degradation was noted. Longer time of anodizing has opposite effect while rotation speed enhanced the electrocatalytic activity of SnO2. The best conditions of anodizing were potential of 5 V, 0.4M OA, 15 min, and 250 rpm in which MB removal was 87.6%. Structural morphology of SnO2 prepared at the optimum conditions confirmed the conversion of tin to SnO2 with free crack structure. These results demonstrate that adopting anodizing method with rotating cylinder technique to forming SnO2 anodes is a promising strategy for constructing high-performance anodes suitable for treatment wastewaters.
Nanoporous film; Tin oxide; Anodization; Oxalic acid; Methylene blue; Rotating cylinder electrode
Superior properties of drilling mud via sustainable nanoparticle priming
This study demonstrates a sustainable, "trash-to-treasure" approach by synthesizing silica (SiO2) and alumina (Al2O3) nanoparticles (30–80 nm) from local waste materials—specifically bentonite clay and aluminum wire waste—and evaluating their performance as eco-friendly additives in 350 mL water-based drilling fluids at concentrations ranging from 0 to 1 g. Tested under harsh subsurface conditions, the incorporated nanoparticles significantly enhanced the fluids' rheological properties, lubricity, filtration control, and swelling inhibition, with performance scaling alongside nanoparticle concentration. Notably, at a 1 g dosage, the fluid's yield point spiked from a baseline of 9 to 42 for SiO2 and 32 for (Al2O3), while high-pressure high-temperature (HPHT) fluid loss was reduced from 21 mL to 14.6 mL (SiO2) and 16.4 mL (Al2O3) due to the formation of a low-permeability filter cake. Furthermore, a 0.75 g dosage lowered the coefficient of friction from 0.45 to 0.35 (SiO2) and 0.37 (Al2O3), while effectively mitigating clay swelling (SiO2) showing superior inhibition at lower concentrations), ultimately proving that these waste-derived nanoparticles offer a highly effective, cost-efficient, and environmentally friendly alternative to commercial drilling mud additives.
Sustainable synthesis; silica; alumina; nanoparticles; drilling mud
Integrated adsorption-membrane separation for PFAS removal from complex wastewater
Per- and polyfluoroalkyl substances (PFAS) are persistent and toxic contaminants that are difficult to remove from complex wastewater because dissolved organic matter, salts, co-pollutants, and membrane fouling reduce treatment efficiency. This study evaluated an integrated adsorption-membrane process for PFAS removal through combined Aspen Plus/MATLAB simulation and bench-scale validation using synthetic complex wastewater. Adsorbent dosage (0.10-1.00 g/L), transmembrane pressure (4-10 bar), and filtration time were investigated. Standalone adsorption was limited by its reduced affinity for short-chain PFAS and by competitive uptake of co-existing dissolved organic matter, whereas standalone nanofiltration was constrained by progressive membrane fouling and flux decline; the integrated configuration was therefore designed to combine the strengths of both unit operations, using adsorptive pre-loading to lower the PFAS and organic load reaching the membrane so as to improve overall removal while mitigating fouling. Adsorption and nanofiltration achieved maximum total PFAS removals of 89.1% and 91.2%, respectively, while the integrated system reached 98.6% at 0.75 g/L PAC and 8 bar, with lower membrane flux decline (reduced from 33.5% to 21.8%) than NF-only operation. Model predictions showed good agreement with the experimental data (R² = 0.975-0.992), indicating that the integrated adsorption-membrane approach is a viable and scalable option for PFAS removal from complex wastewater.
PFAS; complex wastewater; adsorption; nanofiltration; hybrid treatment; process simulation; membrane fouling
AI-driven carbon-neutral gas recovery through CO₂ injection and storage integration
The rising level of Carbon Dioxide (CO2) concentration and the growing energy demand of the world have given a desperate necessity of carbon-neutral and sustainable energy sources. Carbon Capture, Utilization and Storage (CCUS), especially CO2-Enhanced Gas Recovery (CO2-EGR) has become an attractive technology to maximize hydrocarbon recovery with a minimal environmental impact. The paper introduces an AI-based system of recovering carbon-neutral gas by implementing CO2 gas injection and storage. A number of supervised learning models, including XGBoost, Random Forest (RF), and a hybrid RF-XGBoost, were used in conjunction with data preprocessing and feature engineering to come up with the results from the NETL CCS dataset. They also use Bayesian Optimization to adjust the parameters. The findings reveal that the hybrid model does better than the individual models because it has the lowest MAE (0.080), MSE (0.011), and RMSE (0.105), as well as the highest value of R2 (0.96). Further, the recovery efficiency increases by 83 to 92 percent, the leakage risk is lowered by 0.14 to 0.06, and the cost of operation is lowered by 1.00 to 0.72. The results indicate that AI-based strategies are effective to maximize the efficiency, safety, and sustainability with a carbon-neutral gas recovery system.
Carbon Capture and Storage (CCS); CO₂-Enhanced Gas Recovery (CO₂-EGR); Machine Learning; XGBoost; Bayesian Optimization
Ciprofloxacin adsorption on a pomegranate peel adsorbent treated with oleic acid: Isotherm, kinetic, thermodynamic, and statistical studies
The performance of pomegranate peel treated with oleic acid (PPOA) was studied using a batch mode for ciprofloxacin (CIP) adsorption from an aqueous solution. Although other studies have investigated chemical modification with various chemical agents, the novel use of oleic acid for modification yields unprecedented results in terms of CIP removal efficiency. Dependent parameters were optimized using the sample pH, contact interval, initial CIP concentration, and adsorbent dose. Using response surface methodology (RSM) with a central composite design (CCD), a dose of 0.3 g/100 mL produced excellent removal efficiency (above 81%) for CIP concentrations of 60 mg/L after 90 minutes of contact at pH 6. With an R2 (correlation coefficient) value of 0.985, analysis of variance (ANOVA) based on the CCD-RSM demonstrated a good fit between the experimental results and the predictions of the quadratic model. The Langmuir isotherm model was found to fit the CIP adsorption isotherms on the PPOA very well, with a theoretical maximum of 19.90 mg/g, indicating monolayer adsorption. Furthermore, a pseudo-second-order model could adequately describe the adsorption kinetics, implying that the adsorption rate is influenced by chemisorption. The main mechanisms underlying CIP biosorption are ion exchange and electrostatic attraction, whereas adsorption mechanics are controlled by external mass transfer and intra-particle diffusion. Thermodynamic analysis confirmed that adsorption was exothermic and spontaneous. After four consecutive repetitions, the adsorbent adsorption efficiency decreased from 81.88% to 50.91%, indicating its reusability. The results showed that pomegranate peel (PP) is an inexpensive adsorbent for CIP removal. Using this byproduct, CIP was effectively removed.
Ciprofloxacin; Oleic acid; Adsorption; Pomegranate peels; Wastewater treatment
Multi-output machine learning prediction of CO₂ enhanced oil recovery and geological storage performance
Carbon dioxide-enhanced oil recovery (CO₂-EOR) is one of the best commercial carbon capture, utilization, and storage (CCUS) technologies, enhancing oil recovery and achieving safe geological storage. However, data density and computational costs hinder conventional reservoir simulations. This research presents a multi-output machine learning model to simultaneously predict both incremental oil production and CO₂ storage volume. A selected global dataset of 173 projects was compiled, preprocessed, and optimized. Among the evaluated algorithms (random forest, gradient boosting, and random forest chain), gradient boosting achieved the best predictive performance, with a weighted coefficient of determination (R²) of 0.722. Model analysis showed that permeability, depth, and miscibility strongly influence oil recovery (R² for gradient boosting = 0.87), while the predictability of storage volume is low (R² for gradient e boosting = 0.5), which is significantly affected by reservoir depth and porosity. This study highlights the potential of machine learning as a rapid screening tool for evaluating carbon capture, utilization, and storage projects, identifying the performance of key factors, and emphasizing the need for standardized storage reporting to improve prediction accuracy.
CO2-EOR; CO2-Storage; CCUS; Subsurface Storage; Geological Field Data; Machine Learning
Prediction of rock unconfined compressive strength for subsurface formation CO2 storage using physics augmented machine learning: A comparative performance evaluation
The paper introduces a state-of-the-art Physics Augmented Machine Learning framework to predict the critical geomechanical property – Unconfined Compressive Strength (UCS) – in the Zubair reservoir of the Zubair field for mitigating the risk of CO2 storage. The geomechanical results and modeling workflow were obtained via an integrated software system that was developed in Python, while all computational processes and model training were conducted in the Deepnote interactive cloud computing environment; thus, all of the necessary libraries and the high-performance processing capacities were seamlessly integrated. Through the comparison of six ensemble algorithms which are Categorical Boosting (CatBoost), XGBoost )Extreme Gradient Boosting(, RF(Random Forest Regressor), ExtraTrees (Extremely Randomized Trees), GBM (Gradient Boosting Machine), and Deep ANN (Deep Artificial Neural Networks), the research determined the most dependable models, while the Gradient Boosting model stood out by achieving UCS prediction with the best metrics of (R2=0.9995, MAE=3.64). The models are not only providing a precise and reliable but also a scalable assessment tool for subsurface stability, containment integrity, and real-time reservoir monitoring.
Physics-Augmented Machine Learning; Machine learning; Unconfined Compressive Strength; Zubair field; geomechanical property
Performance optimization of CO2 mineralization: A comparative study of caustic soda and soda ash as pH-risers under high-pressure reactor
Aqueous mineral carbonation is one of the most important methods of permanent CO2 sequestration in Carbon Capture, Utilization, and Storage (CCUS). This is carried out using alkaline pH-risers to neutralize the acidity of carbonic acid (H2CO3) to cause a change in the chemical balance to carbonate ions (CO32-). This paper assesses the different sources of alkalinity with special reference to the performance of caustic soda (NaOH) and soda ash (Na2CO3) under industrial circumstances. It has been shown in experiments that caustic soda is the most effective reagent in quick mineralization. It causes a sudden early increase in pH (about 2.0 to 2.5 units per gram) and maintains a very alkaline pH (pH >12), which are critical to the efficiency of CO2 absorption (95.52 %). Moreover, NaOH has a remarkable stability at high pressure and the rate of change in pH (0.3 ΔpH/gm) does not change at the pressure of 65 bars. Soda ash on the other hand is a moderate buffer that reaches its highest pH at approximately 11.6, with an easily lower absorption efficiency of 72.45%. Soda ash performance improves as the pressure is increased to conserve pressure up to 65 bar, thus making it difficult to use it in high-pressure systems. Optimization of the industry shows that the efficiency is maximized within the temperature regime between 40°C and 60°C, where the accelerated reaction rates resulting decrease in the gas solubility. Furthermore, the best mass transfer rate is 300 rpm that minimizes the CO2 bubble size. Though the stoichiometric superiority of caustic soda 1.0 kg does the work of 1.3 kg of soda ash, it presents severe challenges to operation because of its expensive nature, energy-consuming nature, and corrosivity. Soda ash is also still a feasible option in large scale sequestration due to its 30-40 % lower cost and the fact that it is dry and can be transported easily. Finally, a tradeoff between chemical reactivity, mechanical stability, and scalability of the economic side should be made even in the choice of a pH riser.
CO2; caustic soda; soda ash; mineralization; pH riser
Optimization and adsorption modeling of lead ions (II) on carbonaceous materials: Comparative evaluation of raw and citric acid-modified commercial activated carbon and tea waste derived biochar
The article investigated the effectiveness of removal (R%) of a batch study in the removal of lead (II) ions from synthetic aqueous water. A number of experiments were performed to determine the optimal parameters for the maximum removal procedure by using commercial activated carbon. The primary process variables studied included initial lead (II) ions concentration (pb (II)), pH, adsorbent particle size, dosage of adsorbent, and adsorption time. The maximum removal occurred at an initial pb (II) ions concentration of 10 ppm, a pH of 5, an adsorbent dosage of 0.3 g with a particle size of 75 µm, and an adsorption time of 75 min. This research employed isotherm models to determine how the system reached a stable state. Langmuir model confirmed the largest accuracy, as evidenced by the results with a correlation coefficient (R²) of about 97.91%. The kinetic data was the most accurately described by pseudo-second-order model (PSO), suggesting that chemisorption is the limiting factor in the reaction rate, which was supported by a correlation coefficient of 99.5%. Four different adsorbent materials were investigated to evaluate their lead ions (II) removal %: commercial activated carbon (CAC), tea waste-derived biochar (TWDB), and CAC and TWDB modified with citric acid (CAC-CA and TWDB-CA). The study demonstrated that these four adsorbents were very effective and inexpensive agricultural waste may serve as an efficient method to remove pb (II) ions from contaminant water.
Lead Ions (II) Removal; Adsorption; Commercial Activated Carbon; Isotherms and kinetics; Tea Waste Derived Biochar; Citric Acid Modification
Adopting the addition of iron waste as a source for iron (II) ion in Electro-Fenton system for the removal of triple dyes
Use of electrodes that provide a high surface area for reaction, such as Nickel foam and Carbon Fiber Felt, has proven highly efficient in treating wastewater. In this study, a mixture of dyes (Eosin Y, Methylene Blue, and Methylene Violet) was treated using Ni foam as a cathode and carbon fiber felt as an anode in the Electro-Fenton process, relying on iron waste, such as iron filings, as the catalyst source. The analysis characterization of electrodes and iron filings was determined by Energy dispersive X-Ray (EDX) and Scanning electron microscopy (SEM) tests. The results showed high efficiency in decomposing the dye mixture. The highest Re % 96.4591 which attained after accomplishing the experiments based on Response Surface Method (RSM) was recorded at 75 mA of current, 0.25 g/L of iron filings concentration, and 0.015 M of electrolyte concentration. The highest specific energy expenditure for this process was 6.892939 kWh/kg of dyes. In addition to the process's energy efficiency, using iron scrap as a cheap alternative to expensive iron salts is a cost-effective and environmentally friendly approach.
Triple Dyes; Electro-Fenton; Iron Filings; Response Surface Methodology; Ni-Foam; Carbon Fiber Felt
Carbone dioxide sequestration using downhole water sink (DWS) technology: Effects of well placement on trapping efficiency, leakage, and reservoir pressure
Geological CO₂ sequestration is a widely accepted technique that consists of safely and securely hiding carbon emissions from human activities by storing them underground. It is considered the main method of carbon dioxide capturing and sequestration because of its large-scale application. Use of Downhole Water Sink (DWS) systems and other advanced reservoir control technologies is driven by the necessity to manage effectively the reservoir pressure change, the CO₂ plume migration, and the leakage pathways. The effectiveness of the DWS technology in providing better CO₂ storage performance in a depleted reservoir surrounded by a saline aquifer has been the focus of this research. The study analyzed three operational scenarios to evaluate how the different distances between the DWS wells and the CO₂ injectors would affect the storage efficiency, the leakage behavior, and the management of the reservoir pressure. Scenario 1 had DWS wells located right under the CO₂ injectors which caused negative hydrodynamic interactions, decreased the total trapped CO₂ and increased the leakage indices. Scenario 2 had a tiny lateral offset which led to small improvements in trapping and tiny increases in leakage, implying partial but still insufficient mitigation of injector-sink interference. In Scenario 3, with a 10-grid offset between the injection and extraction wells, achieved the maximum CO₂ storage efficiency, where trapping gained 2.79% (431,235 tons) at a CO₂ injection rate of 20 MMSCF/day and a DWS flow rate of 12,500 bbl/day. Leakage did not change, maintaining a Leakage Index of +0.06898 which indicated only a slight increase that was barely noticeable when compared to the more varying responses in Scenarios 1 and 2. In addition, the operation of DWS in Scenario 3 led to a peak pressure of the reservoir that was lower than that of the case without DWS, as the pressure dropped from about 6150 psi to 5100–5794 psi, thus relieving some of the stress on the formation. Although no specific fracture pressures or geomechanical analyses were performed, the pressure drop is likely to create better injection conditions and also enhance the integrity of the storage area. The overall results show that the DWS wells, when placed and managed properly and strategically, can not only increase the CO₂ trapping efficiency but also stabilize the leakage behavior and provide pressure control, thus making the geological CO₂ sequestration more reliable.
CO₂ sequestration; depleted reservoirs; downhole water sink (DWS); leakage index; saline aquifers; trapping efficiency; Reservoir pressure management; well placement; CO₂ trapping mechanisms
Treatment of real petroleum refinery wastewater using SiO₂/TiO₂ nanocomposite induced by UV–visible light
Petroleum refinery wastewater (PRW) is becoming a big problem for both people and the environment, so researchers have been trying harder to find better ways to treat it. One option that looks really promising is using advanced oxidation processes (AOPs) to break down all the pollutants inside this wastewater. In this study, new-designed photoreactor was used to conduct a photocatalysis approach that aimed to remove the chemical oxygen demand (COD) from PRW collected from Al-Diwaniya refinery in the south of Iraq. The geometrically optimized photoreactor enhances the formation of the free radicals required for efficient degradation by maximizing mass transfer and light dispersion. Bare TiO₂ and SiO₂/TiO₂ were fabricated as photocatalysts with the sol-gel technique and then examined by the XRD, FTIR, FESEM, AFM, BET, UV-DRS, and PL analysis. Results showed that, the optimal SiO₂/TiO₂ ratio was 5/95% (S-5) achieving 90% COD reduction efficiency with a photocatalyst dosage of 2 g/L, a reaction time of about 4 h, and using 8 UV-C lamps (8 W each). Under these conditions the process consumed 0.512 kWh/L electricity energy (EE/O). The results demonstrated that COD reduction exhibits behavior consistent with pseudo first order kinetics. In addition, the scavenger experiments revealed that the COD was primarily degraded by the ⦁O₂- radical. After five cycles, the photocatalyst S-5 maintained its stability and continued to remove over 82% of the COD. Refinery effluent was significantly better treated after using this innovative reactor design in conjunction with the SiO₂/TiO₂ photocatalyst. It provides an ecological, more efficient, and less expensive way to lower COD in PRW.
COD reduction; SiO2/TiO2 nanocomposite; photocatalytic degradation; PRW; scavenger
Hybrid particle swarm neural network and regression models for dew-point pressure prediction
Accurate prediction of dew-point pressure (DPP) is essential for the development and production management of gas condensate reservoirs; however, existing empirical correlations and standalone machine learning models often suffer from limited generalization and sensitivity to data variability. This study addresses this gap by developing and comparing a nonlinear multiple regression (NLMR) correlation and a hybrid particle swarm optimized neural network (PSONN) model using a large and diverse dataset of 880 experimental samples collected from published literature and Middle East reservoirs. The PSONN model was selected due to its capability to overcome neural network limitations such as slow convergence by optimizing network weights through global swarm intelligence. The hybrid PSONN model achieved superior predictive accuracy with APRE of 2.45% and CC of 0.997, outperforming both the proposed NLMR correlation and previously published models. The results demonstrate that the developed hybrid framework can significantly improve dew-point pressure estimation, thereby supporting reliable reservoir characterization, surface facility design, and production planning in gas condensate fields.
Hybrid; Neural network; Particle swarm; Nonlinear regression; Dew-point pressure
Sustainable CO2-basd acidizing: A comprehensive review of chemical additives for enhanced carbonate reservoir stimulation
CO₂-based acidizing provides a corrosion-resistant alternative to potent mineral acids in carbonate reservoirs by producing carbonic acid in situ. This method synchronizes stimulation procedures with carbon-management objectives while minimizing the necessity for comprehensive corrosion-inhibitor systems. This review assesses six categories of chemical additives—amines, inorganic salts, inorganic bases, metal-oxide nanoparticles, biological macromolecules, and natural biopolymers—emphasizing their effects on CO₂ absorption, pH buffering, and wormhole morphology at reservoir-relevant temperatures and salinities. Experimental findings indicate that specific formulations can achieve CO₂ absorption levels reaching 2612 mg/L while maintaining pH levels between 4.5 and 5.2. Furthermore, computed CT imaging confirmed consistent wormhole development, indicating effective acid transfer and diminished corrosion risk. According to the reviewed literature, natural biopolymers and biological macromolecules provide the most advantageous equilibrium of reactivity and environmental compatibility; however, the heterogeneity of experimental data, diversity of reservoirs, and scalability are significant considerations. This review methodologically synthesizes peer-reviewed research and field reports published till October 2025, emphasizing mechanistic insights and identifying shortcomings in converting laboratory performance to field application. The proposed approach connects additive selection to carbonate reactivity, transport mechanisms, and operational limitations, thus informing the development of multifunctional fluids for sustainable stimulation and carbon-conscious reservoir management.
CO₂ acidizing; Carbonate reservoir stimulation; Chemical additives; In situ acid generation; Carbon sequestration; CO2 uptake
Energy and cost evaluation for biodiesel production using conventional heating and microwave heating (batch and continuous)
The cost of raw materials and the production process remain major challenges hindering the expansion of biodiesel production on a large scale. Several technologies have been developed to reduce production costs. This research aims to investigate the energy recovery and economic aspects of biodiesel production from used cooking oil (WCO) using conventional and microwave (batch and continuous) transesterification technology. Used cooking oils are an alternative source of energy, given their high potential for use in biofuels production, especially biodiesel. The production of biodiesel in this study relies on a basic esterification reaction using calcium oxide prepared from willow leaves as a catalyst. The results showed that the optimal operating conditions include a catalyst concentration of 3% wt.%, a methanol content of up to 70wt%, and an operating temperature of 65 °C. The reaction time varied depending on the heating technique; the conventional method required 90 minutes, while the time decreased to 20 minutes with batch microwave heating, and to only 5 minutes with continuous microwave heating. These conditions resulted in the highest biodiesel yields of 93.852%, 96.313%, and 93.43%, respectively, for the three methods. From an economic perspective, the cost of producing one liter of biodiesel for conventional and microwave heating (batch and continuous) was approximately 1074.190, 483.588, and 510.162 Iraqi dinars/liter, respectively. The analysis also showed that the total energy consumption of the three methods was 0.945, 0.026666 and 0.03433 kWh respectively, demonstrating that microwave technologies offer a significant reduction in reaction time and higher energy efficiency, thus potentially leading to greater economic returns and operational benefits compared to traditional methods. Finally, the findings result calculated the energy payback period for producing 1 liter of biodiesel using microwave technology. The results showed that the system is sustainable, making it a suitable means of reducing the cost of biodiesel production and supporting its future commercialization.
Biodiesel; Transesterification; CaO catalyst; willow leaves Extract; Energy recovery; cost
Silica sand-supported nZVI-Cu nanoparticles synthesized in a green method for antibiotics removal from aqueous solutions
It is challenging to remove antibiotics from water bodies, as they are among the most widespread contaminants in the environment, particularly with conventional wastewater treatment methods, due to their persistence and low biodegradability. The current study examined the use of nanoscale zero-valent iron to remove antibiotics. Conocarpus leaf extract, which is primarily composed of polyphenols like flavonoids and tannins, was employed as a green source to prepare Fe/Cu nanoparticles, which can act as an eco-friendly reducing agent. The nanoparticles were immobilized onto silica sand (SS), forming SS-Fe/Cu nanocomposite to remove tetracycline (TC) and ciprofloxacin (CIP) from aqueous solutions. The structural characteristics of the produced nanocomposite were examined using a number of analytical techniques, including XRD, FTIR, FE-SEM, EDS, TEM, BET, TGA, and DSC. The structural and morphological analyses confirmed the successful synthesis of the SS–Fe/Cu nanocomposite, with well-dispersed nanoparticles (FE-SEM/TEM), characteristic functional groups (FTIR), crystalline structure (XRD), surface area enhancement (BET), elemental composition (EDS), and good thermal stability (TGA/DSC). Studies were conducted through batch experiments, and the influence of various variables (contact time, pH, agitation speed, nanocomposite dosage, and initial pollutant concentration (Co)) was investigated. The maximum removal efficiencies of 93% and 85% were achieved for TC and CIP, respectively, under ideal conditions: time = 90 min, pH of 11 for TC and 7 for CIP, agitation speed = 200 rpm, Co = 10 mg/L, and nanocomposite dosage of 1 g/50 mL. Isotherm, kinetic, and thermodynamic studies showed that adsorption of both TC and CIP followed the Freundlich model and pseudo-second-order kinetics, indicating chemisorption as the main mechanism. Thermodynamic results revealed that TC adsorption was endothermic and non-spontaneous (positive ΔS°), while CIP adsorption was exothermic and spontaneous (negative ΔS°), confirming the efficiency of the SS–Fe/Cu nanocomposite. The results revealed that the green-fabricated SS-Fe/Cu nanocomposite could be used as an efficient agent for extracting TC and CIP from aqueous solutions.
Conocarpus leaf extract; nZVI; SS-Fe/Cu nanocomposite; Tetracycline; Ciprofloxacin; Adsorption
Fixed bed adsorption of nitrate and phosphate nutrients using char prepared by co-pyrolysis of waste tires and date stones
Conversion of waste tires and date stones into char through co-pyrolysis is an effective way to safely remove and recycle these materials. This study tested char as a low-cost adsorbent for removing nitrate and phosphate in fixed-bed systems, offering a way to reuse waste tires and date stones. The effects of inlet pollutant concentration (50, 150, and 300 mg/L), flow rate (5, 10, and 15 ml/min), and bed height (5, 10, and 15 cm) on the adsorption system’s breakthrough were measured. Characteristics of char were analyzed via the Fourier transform of infrared (FTIR), Brunauer-Emmett-Teller (BET), and zeta potential. The fixed-bed analysis demonstrated superior correlation of breakthrough data with both the Yoon-Nelson and Thomas models. Under varying circumstances, the findings agreed with the Yoon-Nelson and Thomas models, as measured by the correlation coefficient R2 values (0.8147-0.9913) for phosphate, (0.9187-0.9913) for nitrate, and (0.8146-0.9907) for phosphate, (0.9189-0.9801) for nitrate, respectively. The results demonstrate the potential of the prepared char as an efficient and sustainable adsorbent for nutrient removal in continuous treatment systems, providing a promising approach for wastewater treatment and waste valorization.
Fixed bed adsorption; Breakthrough curves; Binary pollutants; Anion adsorption; Co-pyrolysis
Glutaraldehyde-crosslinked chitosan reinforced with nanoparticles for wastewater treatment: Chemical structure modification
Lead (II) pollution from the various industries is a serious environmental problem that requires urgent attention due to its stability and non-biodegradability. Current research addresses the development of a natural polymer's chemical structure to produce an absorbent nanocomposite for lead removal. This development relied on the available functional groups (amino-NH2 and hydroxyl-OH groups) in biopolymers to create adsorbent material through two steps. The first step was chemical bonding of chitosan with glutaraldehyde as a crosslinking agent (CT-GLA) using emulsion cross linking technique, followed by another bonding with a heterogeneous organic compound to provide additional functional groups (CT-GLA-PD). The second step involved supporting the compound with copper oxide nanoparticles (CT-GLA-PD-Cu) to improve characterizations of the adsorbent. The chemical structure of the materials prepared by paraffin dispersion followed by nanoparticle support was carried out in the current study to explain the functional groups that disappeared and formed during the preparation stages. The surface characterization and chemical composition of the adsorbent resulting from the two stages were performed using advanced descriptive techniques such as Fourier Transform Infrared spectroscopy, X-ray Diffraction, Field Emission Scanning Electron Microscope and Energy Dispersive X-ray. According to the experimental data, the chemical modification showed a significant enhancement in morphology properties and composition elements, which positively impacted removal efficiency. This structure development has been reflected in the lead removal efficiency compared to the raw adsorbent. The results showed that the adsorbent produced in the first stage achieved acceptable lead removal efficiency. This performance was further doubled after the use of nanoparticles as supporting material in the second stage.
DBT oxidation; Adsorption; Chitosan; Copper oxide; Composite; Emulsion; Glutaraldehyde
Adsorption of methyl violet dye using MgO nanoparticles: Synthesis and kinetics
A scalable method of oxalate co-precipitation was used to prepare magnesium oxide (MgO) nanoparticles. The precipitant used was oxalic acid and the source of soluble magnesium was magnesium sulfate. Highly crystalline MgO nanoparticles prepared by calcining at 700 were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Atomic Force Microcopy Analysis (AFM). The (MgO) nanoparticles were employed to investigate the adsorption performance of Methyl Violet (MV) dye from aqueous solutions under different conditions, i.e., contact time, pH, dye concentration and temperature. Maximum adsorption (96%) was obtained at time (60 min.), pH 6, at (20 ) and adsorbent dosage (0.05 g/L). It was found that the effect of temperature is inversely proportional to the percentage of dye removal in the studied range (20-50 ). Pseudo-second-order (R2=0.9968) and Langmuir models (R2=0.9931) described excellent fits in kinetic and isotherm experiments, respectively, indicating monolayer coverage and chemisorption. The greater adsorption capability of MgO was verified in comparison to equivalent adsorbents (qmax=83.1 mg/g).
Magnesium Oxide Nanoparticles; Methyl Violet Dye; Adsorption Isotherm; Adsorption kinetics
Photocatalytic degradation of a cationic dye using Ag2O@CuO nanoellipsoidal photocatalyst under ultraviolet irradiation
The photocatalysis oxidation process is a promising technology within the series of advanced oxidation processes, which implements light-induced catalysts to generate strong oxidative species to eliminate organic pollutants from wastewater treatment. The Ag2O@CuO photocatalyst was successfully prepared by the co-precipitation method. The developed photocatalyst was characterized using X-ray diffraction, Fourier transform infrared spectroscopy, X-ray fluorescence spectrometer, field-emission scanning electron microscopy, Ultraviolet-Visible diffuse reflectance spectra, and photoluminescence spectra. The Ag2O@CuO efficiency was examined in the photocatalysis degradation of Rhodamine B (RhB) as a cationic dye under the illumination of ultraviolet light. The effect of various parameters, such as the type of light, photocatalyst dose, initial RhB concentration, and pH of the RhB solution, was studied. The results revealed that 90% degradation was achieved within 90 min at a pH of 6.8, 50 mg of a photocatalyst dose, and 10 mg/L of RhB dye under UV irradiation. However, 98% degradation of RhB dye was achieved at a pH of 10 under the same other conditions mentioned above. The kinetic study was performed based on the experimental data of the oxidative photocatalytic degradation of the RhB dye. The zero-order, pseudo-first order, and modified Freundlich kinetic models were applied to accomplish this study. The results showed that the photocatalytic oxidation of RhB dye by the Ag2O@CuO heterojunction photocatalyst followed a pseudo-first order kinetic model, with an apparent rate constant of 0.0429 min-1. Furthermore, the Langmuir-Hinshelwood model was used to investigate the RhB photocatalytic degradation kinetics of RhB at concentrations of 5-10 mg/L. The determined value of the intrinsic photocatalytic reaction rate constant was 0.7184 mg/L.min for the Ag2O@CuO heterojunction photocatalyst. Also, the equilibrium adsorption constant was 0.0767 L/mg for the Ag2O@CuO heterojunction photocatalyst.
Bimetallic oxide; Co-precipitation; Copper oxide; Photocatalysis; Rhodamine B dye; Silver oxide
Copyright (c) 2025 The Author(s). Published by College of Engineering, University of Baghdad. https://creativecommons.org/licenses/by/4.0/
Petroleum refinery wastewater degradation by heterogeneous-electro-fenton process using activated carbon loaded with Iron and Cerium: A kinetic study
This work aims to study the kinetics of heterogeneous electro-Fenton (HEF) process used to treat petroleum refinery wastewater by a catalyst made of an activated carbon loaded with iron and cerium. Effects of HEF operating variables such as current density, dose of catalyst, and pH on the removal of COD and reaction rate constant (kapp) were examined. Results showed that decline of COD with time at different operating conditions obeys a pseudo-first-order kinetics with a regression fitting (R2) not less than 0.97. Furthermore, increasing the current density was found to give higher rate of COD removal and kapp to a limit beyond which no longer enhancement can be achieved. Similar behaviour regarding to the dose of catalyst while increasing pH has an adverse effect. The best operating conditions that give high rate of COD removal and kapp were a current density of 10 mA/cm2, a dose of catalyst equal to 1.0 g/L, and a pH of 3, in which 86.97% of COD was removed with kapp value equal to 0.0188538 min-1 which required only13.06 KWh/kg COD as an electrical energy consumption. The present system approved to have high reaction rate and could be applied to treat various types of wastewaters.
petroleum refinery wastewater; pseudo first order kinetics; heterogeneous electro-Fenton; Advanced oxidation process
Experimental study of gas-brine capillarity measurement at high temperature and pressure
Understanding capillary pressure profiles during gas-brine coreflooding is essential for analyzing fluid behavior in porous media, particularly in gas reservoirs. Direct measurement of capillary pressure in dynamic displacement experiments relies on evaluating the balance between capillary forces and pressure gradients within the porous structure. In this experimental study three rock samples were taken from a natural gas reservoir located on Australia's Northwest Shelf. Experiments were conducted under simulated reservoir conditions (~ 41.37 MPa and 368.15 K) to investigate the effects of pore size, porosity, and water saturation on the capillary pressure profile. The capillary pressure curves (Samples C1–C3) reveal distinct dynamic behaviors. Samples C1 and C2, which have higher permeability and porosity, exhibit an initial decrease followed by a monotonic rise in capillary pressure until breakthrough. In contrast, Sample C3, characterized by lower permeability and porosity, shows lower brine saturation. However, higher brine saturation would typically be expected in low-porosity samples due to increased grain surface area and smaller pore throats that trap the wetting phase. This unexpected result is attributed to the experiments being conducted under high-pressure and high-temperature conditions. These findings underscore the critical role of pore geometry in governing displacement efficiency and capillary trapping. They also provide valuable quantitative insights for reservoir modeling, particularly in predicting gas recovery under HPHT conditions where capillary forces are significant.
Capillary Pressure; Coreflooding; HPHT; Gas Reservoir
Prediction of cadmium removal efficiency by emulsion liquid membrane using an artificial neural network
This study presented Intelligent Network's proposed methodology for forecasting the effectiveness of cadmium removal from wastewater using emulsion liquid membrane (ELM). The research examined the removal of cadmium from an aqueous solution in the internal phase of water-in-oil emulsions. ELM was composed of kerosene as the membrane phase, Span 80 as the surfactant, di-2-ethylhexyl phosphoric acid (D2EHPA) as the extracting agent, and hydrochloric acid (HCl) as the stripping solution. Experiments were conducted to investigate the effects of five parameters: surfactant concentration, feed-phase agitation speed, internal-to-membrane phase volume ratio, emulsion-to-feed volume ratio, and stripping-phase concentration in the internal phase. More than 97.4% of cadmium can be extracted in less than 15 minutes. This study evaluates the effectiveness of various learning algorithms, including gradient descent (GD), resilient back propagation (RB), gradient descent with momentum (GDM), gradient descent with learning momentum and adaptive rate (GDX), polak-ribiére conjugate gradient (CG), and levenberg marquardt (LM), in predicting the efficiency of cadmium elimination from wastewater using liquid emulsion membrane technology. The researchers developed a neural network model with 8 input neurons, 10 hidden neurons, and 1 output neuron. This feed-forward artificial neural network (ANN) incorporated various back-propagation training algorithms to simulate the cadmium removal process using ELM. The neural network model's predictions closely aligned with results from batch experiments, as demonstrated by a correlation coefficient (R2) of 0.9723 and a Mean Squared Error (MSE) of 0.0041, calculated in MATLAB. In conclusion, the ANN models demonstrated high accuracy and reliability in predicting cadmium removal efficiency, confirming their potential as practical tools for process optimization.
emulsification; surfactant; cadmium removal; emulsion; artificial neural network
Design and evaluation of advanced nanocomposite drilling fluid systems through marl-based lithologies: A study based on outcrop samples from Kurdistan
Swelling is recurring challenges, which can lead to formation damage and compromising the wellbore integrity. Synergizing nanomaterials with their distinctive properties, alongside cost-effective materials, can provide a significant approach in enhancing the treatment of wellbore stability. This study employs a green, simple, and economical approach for the biosynthesis of SiO₂/KCl/Xanthan nanocomposites (NCs), aimed at reducing swelling and improving the rheological and filtration properties of Water-Based Drilling Fluids (WBDFs). The impact of SiO₂/KCl/Xanthan nanocomposite on swelling was assessed, followed by a comprehensive investigation into fluid’s filtration and rheological properties, including apparent viscosity, plastic viscosity, yield point, gel strength, and filter cake thickness. The results confirmed that the green-synthesized NCs effectively reduced clay swelling by approximately 22.2%. Furthermore, they significantly improved the mud’s rheological characteristics, decreasing filter cake thickness and fluid loss by approximately 91.29% and 91.7%, respectively, under HPHT conditions. The findings strongly suggest that SiO₂/KCl/Xanthan NC is an effective additive for mitigating clay swelling, enhancing rheology, and reducing filtration challenges in marl rich formation.
Nanotechnology; Drilling Engineering; Marl-Rich Formation; Swelling, Rheological and Filtration
Kinetic modeling of Dodonaea viscosa decomposition under microwave-assisted pyrolysis: A combined model-fitting and iso conversional approach
This work examines the kinetic behavior of Dodonaea viscosa during microwave-assisted pyrolysis as a means of addressing the limited insight regarding how biomass degradation pathways are affected by non-conventional heating. Thermogravimetric data were analyzed using both model-fitting (Coats–Redfern) and model-free (Friedman and Kissinger–Akahira–Sunose) methods to provide a thorough analysis. Results indicated that a third-order kinetic model appropriately described the general trend of decomposition; in contrast, iso-conversional analyses verified a multi-stage sequence with the activation energy declining during volatile yields and increasing at elevated conversion levels as a result of carbonaceous residue decomposition. These complementary understandings demonstrate that microwave-assisted heating ensures the development of characteristic reaction dynamics rather than those derived from traditional pyrolysis and thus supply mechanistic support for increased energy efficiency. The results not only unify methodology gaps between model-fitting and iso-conversional methodology but also provide useful direction for the optimization of microwave pyrolysis parameters, thus enhancing the sustainable production of lignocellulosic biomass-derived bioenergy.
Microwave-assisted pyrolysis; Dodonaea viscosa; Thermogravimetric analysis (TGA); Kinetic modeling; Isoconversional methods; Activation energy
Sustainable air gap membrane distillation using recycled acrylic (RA) membranes: Application to Shatt Al-Arab water desalination
One of the research motivations in the MD field is to develop high-performance membranes by preparing hydrophobic membranes due to their high throughput and rejection. The current work focuses on the fabrication and performance evaluation of electrospun nanofiber membranes using recycled acrylic (Polymethyl Methacrylate) (RA) via air gap membrane distillation (AGMD). Recycling this material not only reduces plastic waste and pollution, but it also offers a low-cost alternative to virgin polymers, which aids in membrane fabrication. Scanning Electron Microscopy (SEM) confirmed a uniform, highly porous nanofibrous structure with interconnected pores in the prepared nanofiber membranes. Atomic Force Microscopy (AFM) revealed a rough surface morphology, while water contact angle measurements exceeding 121° indicated excellent hydrophobicity, critical for effective liquid-vapor separation. Fourier-transform infrared spectroscopy (FTIR) verified the preservation of key ester functional groups, confirming the chemical integrity of the RA. The assessments revealed that the electrospun nanofibers demonstrated considerable flexibility while preserving their structural and surface characteristics as evaluated through mechanical strength testing. The resulting membranes were utilized in a water desalination process employing an AGMD setup, tested under varying feed temperatures (45, 55, and 65°C) and flow rates (0.2, 0.3, and 0.4 L/min) to evaluate their impact on desalination efficiency. It was observed that increasing the feed temperature significantly boosted water flux; moreover, the feed flow rate notably improved permeate flux within AGMD systems, thereby enhancing mass and heat transfer capabilities. The highest permeate flux recorded was approximately 19 kg/m²·hr, achieved at a temperature of 65°C with a flow rate of 0.3 L/min and a salt rejection rate of 99.999%. Consequently, this study's results indicate that RA-based nanofiber membranes hold potential for sustainable and effective water desalination. Furthermore, AGMD proved to be highly efficient in salt removal from the Shatt al-Arab river and may serve as a viable solution for providing clean drinking water in southern Iraq.
Desalination; Air gap membrane distillation (AGMD); Electrospinning system; Hydrophobic polymer; Nonwoven Nanofibers; Shatt al-Arab River
Implementation of chemical injection with WJSTP in the Gullfaks field attributed to reservoir permeability
The Gullfaks field is a complex field and it’s divided into several formations, which have reservoirs in several stratigraphic layers and fragments of numerous faults. With current technological advancement techniques used in the Gullfaks field, the WJSTP is one of the solution-testing platforms that focuses on treating produced water for re-injection back into the reservoir to increase oil production. The implementation of chemical injection with WJSTP in the Gullfaks field, attributed to reservoir permeability to increase oil production, is the aim of this paper. To attest to the set aimed, a three-dimensional static model of the reservoir is constructed using data provided by NGB Geosciences Consulting LTD. With credit to the Petrel software simulation tool, an in-place volume estimate of 2,748,727,672.95 Bbls of oil and 970,264,150,943.39 SCF of gas was reviewed. Subsequently, a dynamic model is constructed on the foundation of the static model and the specified water injection parameters, and simulated with the use of the Eclipse software. The reduction in permeability of the reservoir's high-permeability zones through chemical injection of WJSTP resulted in 70% oil recovery, representing a 44.99% increase, and 74% gas recovery, representing a 37.9% increase. The sensitivity analysis conducted on oil price, oil production, and investment demonstrates that the viability of the project is highly contingent on the oil price. The findings of this study indicate that chemical injection of WJSTP represents a technically feasible and economically profitable method of enhancing oil production in the Gullfaks field.
Gullfaks field; static and dynamic model; permeability; WJSTP; Petrel; Eclipse; profitability
Ciprofloxacin adsorption via compressed wood activated carbon with ZnCl2 activating agent from simulated wastewater: Mechanism studying
The current study objective is to synthesize activated carbon (AC) from compressed wood using the ZnCl2 activating agent and to assess the ciprofloxacin (CIP) elimination efficiency in simulated wastewater. The produced AC was characterized using multiple techniques, including SEM, BET, FTIR, AFM, and XRD. The adsorbent demonstrates high adsorption performance, achieving 91% removal of CIP within 5 hours at an initial pollutant concentration of 100 mg/L with an AC dose of 2 g/L. Experimental data correspond to the Freundlich isotherm model (R² = 0.995) as well as the Langmuir competitive fitting (R² = 0.99), while the root mean square error (RMSE) equation best fits the Langmuir model. Moreover, the pseudo-second-order model (R² = 0.999) was used to describe the kinetic data. The adsorption thermodynamics indicate spontaneous adsorption with exothermic behavior (ΔG◦<0, ΔH◦<0, ΔS◦<0). A combination of mechanisms contributed to the CIP adsorption process (π-π interaction, hydrophobic interaction, bulk diffusion, hydrogen bonds, in addition to physical and chemical adsorption mechanisms). Pyrolysis recoverability shows a good result after three cycles (qe = 101.08 mg/g, compared to 170.13 mg/g in the first cycle). In conclusion, compressed wood AC offers a sustainable, low-cost adsorbent for treating wastewater and presents a prospect for addressing ecosystem contamination challenges.
Compressed wood; activated carbon; ZnCl2 activating agent; intraparticle diffusion; Temkin model; ciprofloxacin; adsorption mechanism; exothermic adsorption
Field development planning using an active surrogate model and optimization algorithms for a Southern Iraqi oil field
Greenfield development planning is a challenging problem due to the complex objective function and the large number of variables. While stochastic algorithms and data-driven offline surrogate models have been used to locate and control wells, these methods often require a large number of runs or fail to reach an accurate optimal solution. For this reason, the current study aimed to develop a dynamic surrogate model updated after each evaluation, referred to as an active learning model. In this study, deepEnsemble and gaussian process (GP) algorithms were applied as an active alternative model. This approach was compared with optimization algorithms directly coupled with real simulations, where algorithms such as genetic algorithms (GA), particle swarm optimization (PSO), complex matrix adaptation evolution strategy (CMA-ES), and differential evolution (DE) were used for comparison. The deepEnsemble active model outperformed the other approaches, achieving a net present value (NPV) of more than 1 E+10 and 17% recovery factor (RF) for a field in southern Iraq for a production scenario. The algorithm suggested shutting in two existing wells and drilling 23 new wells. The algorithm was also tested using a water injection scenario; a stable pressure, NPV of approximately 1.28 E+10, and 25% RF was achieved by suggesting drilling 39 new wells, 17 of which were injection wells. The approach has proven effective in dealing with complex field development problems with a minimum number of runs.
DeepEnsemble; Optimization; Proxy Model; Well Placement; Field Development