Engineering and Technology Journal

We are pleased to announce the official launch of the new website for Engineering and Technology Journal (ETJ) on the Digital Commons (Elsevier) platform. This transition represents an important step toward enhancing the journal’s visibility, improving the submission workflow, and providing a more streamlined experience for readers, authors, reviewers, and editorial board members.

The new platform is now fully operational, and authors are invited to submit their manuscripts directly through the updated system. All article submissions, revisions, and correspondence will be managed exclusively through this new website.

You may access the new ETJ website through the following link:
https://www.editorialmanager.com/etj/

We encourage our community of researchers and contributors to visit the new platform, explore its features, and begin using it for all future submissions.

We look forward to continuing our service to the scientific community with improved efficiency and expanded global reach.

www.editorialmanager.com

يسرّنا أن نعلن عن الإطلاق الرسمي للموقع الإلكتروني الجديد لمجلة الهندسة والتكنولوجيا (ETJ) على منصة Digital Commons (Elsevier). ويُعد هذا الانتقال خطوة مهمة نحو تعزيز حضور المجلة وانتشارها، وتحسين آلية استلام ومعالجة البحوث، وتوفير تجربة أكثر سلاسة وتنظيمًا للقراء، والباحثين، والمقيمين، وأعضاء الهيئة التحريرية.

أصبحت المنصة الجديدة قيد التشغيل بشكل كامل، وندعو الباحثين الكرام إلى تقديم بحوثهم مباشرةً عبر النظام المحدَّث. وستُدار جميع عمليات تقديم المقالات، والمراجعات، والمراسلات حصريًا من خلال هذا الموقع الجديد.

يمكنكم الوصول إلى موقع مجلة ETJ الجديد عبر الرابط الآتي:
https://www.editorialmanager.com/etj/

نحثّ مجتمع الباحثين والمساهمين على زيارة المنصة الجديدة، والاطلاع على خصائصها، والبدء باستخدامها في جميع عمليات التقديم المستقبلية.

نتطلع إلى مواصلة خدمة المجتمع العلمي بكفاءة أعلى وانتشار عالمي أوسع.

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An exhaustive review of carbon dioxide capture through the utilization of chemical solvents via absorption
https://doi.org/10.30684/etj.2024.152635.1799
Abstract
The release of carbon dioxide from the combustion of fossil fuels and chimney emissions has emerged as the primary catalyst for global warming. The significant increase in emissions is due to various factors, including power plants that rely on fossil fuels, different industrial processes, and many other factors, all of which are the main causes of environmental pollution. The need has arisen to invent an effective way to reduce carbon dioxide emissions into the atmosphere, where scientists have reviewed several methods, such as transitioning to renewable energy, improving energy generation stations, and capturing carbon dioxide emissions. However, the optimal and most realistic choice is carbon capture and storage to preserve a green environment. Currently, there are three methods: pre-combustion capture, post-combustion capture, and oxyfuel combustion. Post-combustion capture is the most common system; among its various methods, absorption is considered one of the most common processes for gas capture. Absorption involves contact between a gas-liquid mixture to remove one of the gas components by dissolving it in a suitable liquid. The purpose of this review is to clarify the techniques of CO2 capture with a focus on the absorption process using the absorbent material (NaOH), as well as to identify other types of absorbent materials used in absorption processes and the effect of reactor structure on absorption performance in addition to the impact of reaction parameters on absorption efficiency.
Highlights:
- The latest research on carbon dioxide capture through chemical absorption has been reviewed.
- This review helps in determining the optimal method for carbon dioxide capture .
- It discusses the impact of operating factors on the performance of absorption.
- The performance of absorption is determined by the mass transfer between the absorbent material and carbon dioxide.
Keywords:
- Chemical absorption
- CO2 Capture
- Global warming
- Solvents
- Post-combustion
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15205.html
Article: https://etj.uotechnology.edu.iq/article_185500.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Dear colleagues

We are pleased to announce the official launch of the new website for Engineering and Technology Journal (ETJ) on the Digital Commons (Elsevier) platform. This transition represents an important step toward enhancing the journal’s visibility, improving the submission workflow, and providing a more streamlined experience for readers, authors, reviewers, and editorial board members.

The new platform is now fully operational, and authors are invited to submit their manuscripts directly through the updated system. All article submissions, revisions, and correspondence will be managed exclusively through this new website.

You may access the new ETJ website through the following link:
https://etjuot-sandbox.digital-commons.com/

We encourage our community of researchers and contributors to visit the new platform, explore its features, and begin using it for all future submissions.

We look forward to continuing our service to the scientific community with improved efficiency and expanded global reach.

Editorial office team

etjuot-sandbox.digital-commons.com

Effect of friction stir processing of in-situ A356/Al3Ni composites: microstructure refinement and wear behavior
https://doi.org/10.30684/etj.2025.156833.1887
Abstract
This research investigated the impact of friction stir processing on grain refinement in the surface layer of composite materials. The in-situ composite was created by stir casting, incorporating 15% pure Ni into the Al matrix type A356. Microstructural analysis performed with optical microscopy and X-ray diffraction revealed the formation and dispersion of intermetallic phases such as AlNi, Al3Ni, and Al3Ni2, contributing to significant grain refinement. FSP further enhanced the micros structure by breaking and uniformly distributing small particles, including the primary Si phase and Al₃Ni, while refining α-Al dendrites. These microstructural changes resulted in improved mechanical properties, including a 13.81% increase in hardness for the A356/Al3Ni composite and a 14.47% increase for the base A356 alloy. Wear rate tests were conducted using a ball-on-disc apparatus under dry sliding conditions for both the base alloy A356 and the in-situ composite A356/Al3Ni, before and after FSP. Compared to the base alloy A356 and in situ composites before and after friction stir processing, the in-situ composite (A356/Al3Ni) after FSP exhibited a lower wear rate. However, during the wear test, the coefficient of friction decreased as the applied load increased for the base alloy A356 and the in-situ composite (A356/Al3Ni) following the friction stir process.
Highlights:
- A356/Al3Ni in-situ composites were fabricated using the stir casting method
- FSP enhanced the microstructure by refining grains in A356 and the in-situ composite
- FSP increased hardness to 87 HV for A356 and 173 HV for the A356/Al3Ni composite
- The A356/Al3Ni composite after FSP showed superior wear resistance over the base and pre-FSP composite
Keywords:
- Al alloy A356
- Stir casting
- Friction stir processing
- In situ composite Al3Ni
- Wear rate
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15492.html
Article: https://etj.uotechnology.edu.iq/article_189581.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Investigating the role of solvent extraction in altering pH levels for efficient Neodymium extraction from magnet scrap
https://doi.org/10.30684/etj.2025.159446.1948
Abstract
Recycling rare earth elements, specifically neodymium from magnet scrap, is crucial for advancing sustainable technologies across various industries. In this research, neodymium was recovered by solvent extraction using a stock solution prepared in 200 mL by dissolving 1 g of neodymium (III) nitrate hexahydrate, Nd(NO3)3.6H2O, in 0.5 M nitric acid. Then, it was mixed with 1 M di-(2-ethylhexyl) phosphoric acid (D2EHPA) in Isopar-L, as the organic phase, and 3 M H2SO4, as the aqueous phase, with an organic/aqueous volume ratio of (1:1). Specifically, the study examined the pH variation of the aqueous phase (from 0.5 to 2). The pH of the solution was measured using a pen-type pH meter, where the stripping agent was HNO3 at a concentration of 6 M. The experiments were conducted using a magnetic stirrer at ambient temperature with an agitation speed of 300 rpm for 24 hours. The concentration of metals was measured using an EDX. The extraction efficiency of neodymium increased from 51.7% at a pH of 0.5 to 82.02% at a pH of 1.5, with a slight decrease observed at pH values of 1.7 and 2. Moreover, samples of Mg-Nd alloy were manufactured with various extractant Nd contents of (1, 3, 4, and 5%). The microstructure of the alloys, both before and after corrosion in 3.5% NaCl, was examined using a scanning electron microscope (SEM). The results indicated that the alloys consisted primarily of the α-Mg phase and the Mg12Nd phase, and that the corrosion resistance increased with the increasing amount of neodymium.
Highlights:
- At pH ≤ 2, the concentration of rare earth elements and metal ions increased, enhancing the extraction potential.
- D2EHPA acted as an efficient cation exchanger, releasing H⁺ ions during metal cation uptake.
- In solvent extraction, precipitated particles promoted rare earth attachment to extractant compounds.
- The highest neodymium extraction efficiency was achieved at a pH of 1.5.
- The addition of neodymium to magnesium improved its corrosion resistance.
Keywords:
- Rare earth
- Neodymium
- Magnet
- Solvent extraction
- Corrosion
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15442.html
Article: https://etj.uotechnology.edu.iq/article_189917.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Impact of surface-modified silica and magnesium oxide nanoparticles on the flow behaviour of East Baghdad crude oil and emulsion
https://doi.org/10.30684/etj.2024.147425.1710
Abstract
The transportation of crude oil naturally, including emulsion from the wellhead to the processing facility, presents a challenge in the oil industry, particularly as wells age and the production of associated water increases. To improve the flowability of the emulsified oil, traditional methods for reducing the viscosity, such as dilution and heating, are costly and energy-intensive. However, nanotechnology offers a potential solution to improve flowability and crude oil behavior. This paper examines how adding 3% wt of surface-modified silicon dioxide (SiO2) and magnesium oxide (MgO) nanoparticles impacts the flow properties of an emulsion containing East Baghdad crude oil. The investigation is conducted across different water cut levels (5%, 35%, 50%, and 75% v/v) within a horizontal pipe 0.0145 m inner diameter and 13m in length. The effect of these nanoparticles on emulsion stability, rheology, viscosity, pressure drop, and energy consumption was studied. The rheology study found that the best results were achieved by adding surface-modified nano silica at 3%, which significantly reduced viscosity with shear thinning behavior. Adding 3% nano-silica obtained a highly stable emulsion and a higher reduction of 69% in power consumption for pumping the fluid. In comparison, a 25% increase in power consumption was achieved by adding the same concentration of MgO.
Highlights:
- As oil wells age, water content rises, creating stable emulsions at 50% water cut.
- 3% modified Nanosilica enhances flow and reduces viscosity.
- 3% MgO addition significantly alters fluid behavior at high water cuts.
- Power consumption decreases with SiO2-added emulsions.
Keywords:
- Emulsion
- Rheology
- Pressure drop
- Low API crude oil
- Nanoparticles
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_14819_15035.html
Article: https://etj.uotechnology.edu.iq/article_183781.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

AI-driven attacks on database security: taxonomy and defense strategies
https://doi.org/10.30684/etj.2025.163946.2003
Abstract
Artificial intelligence has introduced both unprecedented capabilities and novel vulnerabilities into database environments, enabling highly adaptive attacks that can evade traditional defenses. This review surveys recent research published between 2022 and 2025 on AI-assisted database security threats and synthesizes the literature to develop a comprehensive taxonomy of emerging attack approaches. We identified five primary classes of AI-based attacks: intelligent SQL injection attacks, adversarial machine learning strategies targeting database security systems, data poisoning attacks on AI-based databases, automated reconnaissance exploits, and sociotechnical manipulations aimed at database administrators. We systematically reviewed publications on cyber defense stored in IEEE Xplore, ACM Digital Library, Science Direct, and Scopus databases. Boolean search terms were used on the databases specific to cyber defense. Findings indicate that automated SQL injection attacks can escalate the bypass rate of security systems to over 85% effectiveness. The effectiveness of rule-based defense systems degrades by 32% when pitted against sophisticated AI-adapted adversarial attacks. Conversely, machine learning-based defenses maintain a detection rate of 85 to 95%. To combat advancing techniques, a multilayer approach that includes adversarial training, anomaly-based intrusion detection, and automated user behavior analysis and reporting technology should be employed. This approach utilizes anomaly-based defenses through a monitoring model. Analysis shows that conventional database defense techniques need to be upgraded with real-time analytics, dynamic response mechanisms, and zero-day vulnerability protection to keep pace with the increasingly sophisticated nature of AI adversarial attacks on database systems.
Highlights:
- A novel taxonomy of five AI-powered database attacks bypassed traditional defenses with 85% success.
- Analysis of 23 recent studies revealed critical gaps in AI-driven database security frameworks.
- A layered defense model with adversarial training and behavioral monitoring was proposed.
- Statistical results showed a 32% decline in rule-based systems against advanced AI attack variants.
- A multi-disciplinary approach addressed technical, organizational, and human factors in AI threats.
Keywords:
- AI driven attacks
- Database security
- Adversarial machine learning
- SQL injection
- Data poisoning
- Federated learning security
- GAN based attacks
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15442.html
Article: https://etj.uotechnology.edu.iq/article_189916.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

A comparative study of viscoelastic characteristics in polymer composite with respect to the damping performance and structural behavior
https://doi.org/10.30684/etj.2025.160856.1965
Abstract
This study systematically investigates the viscoelastic characteristics and damping performance of polymer composites, examining the interplay between filler morphology, matrix-filler interactions, and structural behavior. The purpose is to understand and predict how different fillers influence key viscoelastic properties to enable tailored composite design. Methods and Key Findings: Dynamic mechanical analysis (DMA) and forced vibration tests were used to characterize temperature- and frequency-dependent viscoelastic properties, including storage modulus (E′), loss modulus (E′′), and damping factor (tanδ). Key results demonstrate distinct effects: Spherical calcium carbonate increased stiffness (E′) by 45% at 15 wt% loading but restricted damping (tan δ) due to agglomeration-induced stress concentrations. In contrast, core-shell rubber particles increased tan δ by 280% through interfacial slip, achieving a damping ratio (ζ) of 0.052 (2.8 times higher than neat epoxy). Nanoclay composites exhibited frequency-dependent damping anisotropy from processing alignment. Hybrid filler systems showed synergistic damping effects within the 10–50 Hz range. Optimal performance occurred at 5 wt% Al₂O₃, balancing moderate stiffness (E′ = 1.5 GPa) with peak damping (tan δ = 0.82). Microstructural analyses (SEM/AFM) correlated maximized interfacial friction and damping with an agglomerate area fraction

Comparative study on finite time tracking design based on PID for 1-degree of freedom manipulator
https://doi.org/10.30684/etj.2025.155004.1842
Abstract
In this paper, the application of Sliding Mode Control (SMC) and its integration with Finite-Time Stability (FTS) for controlling 1-degree of-freedom (DOF) system has been explored. By combining FTS with SMC, the convergence speed is significantly improved, enhancing the system's resistance to external disturbances. This paper demonstrates a detailed comparative study on the application of SMC based on FTS with a SMC, and with conventional-PID (C-PID). The SMC developed in this paper is based on a PID controller to ensure that the system's trajectory converges exponentially to zero. The results show that using SMC with FTS provides faster and more reliable system stability compared to the other two methods. The comparison also includes the utilization of different functions in the developed SMC, such as sign, tan, and saturation functions. The effects of disturbance and uncertainty have been considered as well. The results show that using SMC with FTS significantly outperforms SMC without FTS and the C-PID in all cases; the achieved Settling Time of SMC with FTS is approximately 1.5 seconds, compared to 4 seconds for the Conventional PID (C-PID) controller. This represents a 62.5% improvement in response speed. The reduction in Overshoot for the C-PID controller is around 15%, while using SMC with an FTS controller reduces the overshoot value to just 3%, indicating an 80% improvement in overshoot and demonstrating enhanced stability and performance.
Highlights:
- A PID-based sliding surface ensures exponential convergence of the system's trajectory to zero.
- Combines PID precision with SMC robustness for enhanced stability against disturbances.
- Achieves finite-time stability, improving efficiency and responsiveness to disruptions.
- Integrates SMC with FTS for faster convergence, reduced errors, and smoother performance.
- Resists disturbances effectively, enabling rapid stabilization in unstable conditions.
Keywords:
- Sliding mode controller (SMC)
- Conventional PID (C-PID)
- Finite time stability (FTS)
- 1-Degree of freedom (1-DOF)
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15398.html
Article: https://etj.uotechnology.edu.iq/article_186762.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Traditional machine learning techniques for explainable AI in lung and colon cancer classification
https://doi.org/10.30684/etj.2025.158895.1935
Abstract
Lung and colon cancers are two of the most common and deadly tumors around the world, creating significant public health concerns. Artificial intelligence (AI) and machine learning (ML) have heavily improved cancer research, particularly in early detection, histopathological analysis, and personalized therapy planning. However, despite their remarkable accuracy, ML models sometimes lack transparency, making explainability crucial in medical applications. Although various machine learning (ML)-based classifications for cancer models exist, their interpretation is not understood. The current research overcomes the diagnostic gap by developing a highly accurate system that uses XAI (Explainable Artificial Intelligence) methods to clarify its predictions. We used Kaggle's LC25000 dataset, which included histology images for lung and colon tumors in humans. To determine the best cancer classification strategy, we tested various machine learning algorithms, including Random Forest, Decision Tree, Support Vector Machine (SVM), and Extreme Gradient Boosting. Furthermore, XAI approaches such as LIME (Local Interpretable Model-Agnostic Explanations) and SHAP (Shapley Additive Explanations) were utilized to evaluate model predictions and identify important information affecting classification outcomes. XGBoost confirmed that it was useful in identifying colon and lung cancer by achieving the highest accuracy of 99.80% among the models used. Also, XAI techniques offered useful information on the most significant features. SHAP analysis highlighted LBP and color histogram features as key for distinguishing lung and colon tissues, while LIME confirmed their importance by identifying critical image regions influencing predictions.
Highlights:
- An image-based method was developed to classify lung and colon cancer using CLAHE-enhanced histopathology images
- Color histograms and LBP features were combined to improve classification across five cancer-related classes
- XGBoost with RFE achieved 99.80% accuracy by selecting the most relevant handcrafted features
- CLAHE preprocessing enhanced feature clarity, improving model accuracy and interpretability
- SHAP and LIME tools were used to explain model decisions, supporting transparent AI-driven cancer diagnosis
Keywords:
- Lung cancer
- LC25000 dataset
- Colon cancer
- Machine learning
- Explainable AI
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15442.html
Article: https://etj.uotechnology.edu.iq/article_188848.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt

Self-sensing engineered cementitious composites with carbon nanotubes and reinforcing fibers for damage detection
https://doi.org/10.30684/etj.2025.156508.1879
Abstract
Engineered Cementitious Composites (ECC) represent innovative construction materials that exhibit established mechanical properties and strength features. The exceptional characteristics of this substance render it a compelling option for various kinds of facilities. However, the increased implementation of ECCs necessitates monitoring the structural integrity of the systems that utilize them. This paper focuses on developing this concept by employing the traditional matrix after incorporating it with conductive fillers. These fillers transform the matrix into a functional state to sense the damage caused by various loads. Such loads include indirect tensile loads and compressive strength of mortar samples composed of cementitious matrix injected with multi-walled carbon nanotubes (MWCNT) and reinforced once with polyvinyl alcohol fibers (PVA) and with nylon fibers (NF) at another time, with different study ages of 28, 56, 90, and 180 days of curing with water at room temperature. In order to develop previous works and fill part of the gap, the traditional matrix was injected with carbon nanotubes at a dose of 0.5 by weight of cementitious materials with one of the reinforcement fibers of (PVA) or (NF) at a rate of 2% by the total volume of the mixture, which is a constant ratio throughout the study. In addition, a control mix free of additives was created for comparison. The results indicate that clever matrices have excellent mechanical properties. The PVA fiber-reinforced matrix performed better than the other matrices under applied loads. The electrical properties of the matrices were recorded from the start of load application and increased with increasing load. The CNT0.5PVA2 matrix had more gains under compressive loading, with a self-sensing ratio reaching about 200%. In split tensile loading, the CNT0.5NF2 matrix had a higher electrical resistance by about 20% than the CNT0.5PVA2 matrix, which had a resistance of less than 10%.
Highlights:
- The mechanical and self-sensing properties of ECC with nano-additives were assessed.
- In split tensile loading, the CNT0.5NF2 matrix had a higher electrical resistance by 20% than the CNT0.5PVA2 matrix.
- PVA and nylon fibers at 2 vol.% were applied to enhance mechanical properties.
- A synergistic effect between C**s and fibers improved the overall mechanical behavior.
- PVA fibers enhanced electrical conductivity by absorbing nanofillers.
Keywords:
- Functional fillers
- Multi walled carbon nanotubes
- Polyvinyl alcohol fibers
- Nylon fibers
- Self sensing
Journal: https://lnkd.in/dgnvtdte
Issue: https://etj.uotechnology.edu.iq/issue_15129_15449.html
Article: https://etj.uotechnology.edu.iq/article_187989.html
ETJ LinkedIn: https://lnkd.in/d_8SPqAt