Eurasian Journal of Chemical, Medicinal and Petroleum Research

Abstract Cooling systems in thermal power plants play a decisive role in maintaining steam cycle efficiency, enhancing equipment reliability, and reducing maintenance costs. In the present study, the water chemistry and corrosion behaviour in the hybrid (dry-wet) cooling system of a sample thermal power plant were investigated. This plant, with a nominal capacity of 1000 MW, supplies the bulk of its water demand from treated municipal wastewater and employs a combination of dry and wet cooling towers to reduce water consumption. Sampling was conducted on demineralised water, recirculating water of the dry tower, inlet water to heat exchangers, wet tower water, and makeup water. General parameters including pH, electrical conductivity, TDS, temperature, and salinity were measured. Additionally, the concentrations of metallic elements were determined using ICP-MS. The results indicated that the demineralised water exhibits exceptionally high purity and is virtually devoid of metal ions, whereas in the dry cycle, a significant increase in aluminium concentration up to approximately 260 ppb was observed, indicative of active corrosion in the aluminium radiators of the dry tower. In contrast, in the wet tower, the concentrations of calcium, sodium, potassium, silica, copper, and zinc increased markedly, attributable to evaporation, concentration of dissolved solids, and the use of wastewater as make-up water. Comparison of the results with EPRI guidelines revealed that although iron and copper levels fall within acceptable ranges, the elevated aluminium concentration may be regarded as the primary indicator of heat transfer equipment degradation. Accordingly, the revision of the water chemistry control programme, continuous monitoring of dissolved aluminium, and reassessment of the dry tower operating conditions are proposed as the most critical management strategies. The findings of this research can serve as a basis for the development of intelligent corrosion monitoring programmes in power plants equipped with hybrid cooling systems.

Abstract The discovery of effective and environmentally friendly organic corrosion inhibitors remains constrained by slow experimental screening and fragmented computational workflows . This study presents an integrated hybrid framework combining density functional theory (DFT), molecular dynamics (MD) simulations, and machine learning (ML) for high-throughput screening of organic corrosion inhibitors. DFT provides quantum-level insights into electronic structure and adsorption energetics through frontier molecular orbital analysis (EHOMO, ELUMO, energy gap ΔE), while MD captures time-dependent interfacial behavior and competitive ion interactions . A comprehensive dataset of 284 phenyl phthalimide derivatives was generated through DFT and MD simulations, with electronic properties correlated to experimental inhibition efficiency values . Among various ML models evaluated, Artificial Neural Networks demonstrated the highest prediction accuracy, achieving R² values of 93.18% for EHOMO and 91.12% for ELUMO . SHAP and PFI feature importance analyses revealed that descriptors B06[C-N] and qnmax are essential for inhibitor efficacy . The integrated framework addresses key limitations in current approaches including data scarcity, non-standardized descriptor selection, insufficient physical interpretability, and poor generalization across chemically diverse systems . Experimental validation through electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization confirmed the predictive capability of the ML models, with excellent agreement between predicted and measured inhibition efficiencies. This work establishes a unified, scalable, and physically informed computational framework for rational design and discovery of next-generation corrosion inhibitors.

Abstract Dissimilar metal welded joints (DMWJs) are essential components in offshore oil and gas infrastructure, yet they face critical degradation through corrosion-fatigue interaction under sour service conditions. This comprehensive review examines the multi-physics mechanisms governing crack initiation and propagation in DMWJs exposed to sour environments containing H₂S, where fatigue lives can be reduced by factors of 10× to 50× compared to air . The electrochemical and mechanical coupling arises from hydrogen embrittlement, where hydrogen generated at the crack tip diffuses into the fracture process zone (FPZ) and degrades material cohesion . Microstructural heterogeneity across the weld—including the heat-affected zone (HAZ), fusion boundary, and buttering layers—creates complex local stress-strain fields and galvanic corrosion cells that accelerate damage . Welding residual strain and ductility dip cracking have been identified as critical promoters of corrosion fatigue crack initiation in DMWJs, with cracks initiating preferentially at weld interfaces or regions of high residual strain . Advanced predictive models based on hydrogen transport kinetics to the FPZ have been developed to quantify corrosion fatigue crack growth (CFCG) rates over wide ranges of mechanical variables (ΔK, stress ratio, frequency) and environmental variables (H₂S partial pressure, pH, temperature) . The transition from short-crack to long-crack behavior in sour environments reveals that shallow flaws can grow up to an order of magnitude faster than deep flaws at equivalent ΔK, highlighting the non-conservatism of deep-crack data for shallow flaw assessment . This review concludes that effective life prediction requires integrated multi-physics frameworks coupling crack-tip electrochemistry, hydrogen diffusion, and fracture mechanics.

Abstract The development of self-healing epoxy nanocomposites with long-term corrosion protection in marine environments represents a critical challenge in materials science, requiring sophisticated integration of passive barrier properties and active inhibition mechanisms . This comprehensive review systematically examines coordination-controlled self-healing epoxy nanocomposites, focusing on the synergistic inhibition mechanisms and long-term electrochemical impedance behavior in simulated marine environments. The coordination chemistry framework provides a unifying theoretical foundation: corrosion inhibitors function as multidentate ligands, nanocontainers serve as coordination carriers, and self-healing processes operate through in-situ coordination film formation . Advanced nanofiller systems incorporating pH-responsive nanocontainers—including metal-organic frameworks (MIL-100(Fe), ZIF-8), graphene oxide-based composites, and layered double hydroxides—have demonstrated exceptional performance, achieving low-frequency impedance modulus values of 5.03 × 10⁹ Ω·cm² after 50 days of immersion . The MIL-100@BTA system demonstrates alkaline-triggered release with up to 85% inhibitor release within 9 hours at pH 10, enabling targeted corrosion suppression at damaged sites . Tri-functional coating systems integrating passive barrier enhancement (109 Ω·cm² impedance after 120 days), active ion capture, and autonomous defect repair have been achieved through cascade synergistic mechanisms . This review concludes that coordination-controlled design principles offer transformative potential for durable, intelligent protective coatings with extended service life.

Abstract Electrochemical advanced oxidation processes (EAOPs) have emerged as promising technologies for the degradation of persistent organic pollutants (POPs) through the in-situ generation of reactive oxygen species, particularly hydroxyl radicals (•OH) . However, the practical application of EAOPs faces two critical challenges: the competitive chloride oxidation reaction (COR) caused by chloride ions in real wastewater, which leads to low Faradaic efficiency and severe corrosion of anode active sites, and the limited service life of electrodes due to dissolution of catalytic layers under harsh operating conditions . This comprehensive review systematically examines nanostructured anodes designed for dual-function applications—simultaneously achieving efficient electrochemical degradation of organic pollutants while providing in-situ corrosion protection of metallic substrates. Nanostructuring approaches, including TiO₂ nanotube arrays and hydrophobic surface modification, have demonstrated remarkable performance enhancement: TiO₂-NTs/SnO₂-Sb-PTFE composite electrodes achieve high oxygen evolution potential (2.4 V vs Ag/AgCl), significantly enhanced TOC removal efficiency for phenolic pollutants, and substantial reduction in Sn ion leaching compared to conventional electrodes . Surface hydrophobicity promotes effective release of free hydroxyl radicals from the anode surface into solution, facilitating pollutant mineralization while the hydrophobic PTFE layer acts as a barrier inhibiting anodic dissolution . Anti-corrosion design principles for seawater electrolysis—including selective oxygen evolution reaction active sites, anion exclusion layers, and electronic structure redistribution—offer valuable strategies for enhancing anode stability in chloride-rich environments . Recent advances in iridium-coated titanium anodes demonstrate service lives of 2-5 years with iridium loss below 0.1 mg/cm²/year, while PANI-modified iron anodes achieve corrosion inhibition efficiency of approximately 35% after repeated electrocoagulation treatment cycles . This review concludes that dual-function anodes represent a transformative approach for sustainable wastewater treatment, combining catalytic activity with corrosion resistance.

Abstract Electrochemical characterization techniques have become indispensable for understanding corrosion phenomena, enabling both fundamental mechanistic insights and practical corrosion monitoring across diverse industrial applications. This comprehensive review systematically examines the principles, applications, and data interpretation strategies for key electrochemical methods used in corrosion research. Cyclic voltammetry (CV) has emerged as a powerful mechanistic probe, capturing real-time redox activity and surface transformations, though historically underutilized due to the irreversible nature of corrosion reactions . Electrochemical impedance spectroscopy (EIS) remains the most versatile technique, providing frequency-dependent information on charge transfer resistance, double-layer capacitance, and diffusion processes, with applications ranging from reinforced concrete diagnosis to nanostructured coating evaluation . Potentiodynamic polarization enables rapid determination of corrosion current density, Tafel slopes, and pitting potentials through the Stern–Geary relationship . Electrochemical noise analysis detects spontaneous current and potential fluctuations sensitive to localized corrosion events such as metastable pit growth . Recent advances in machine learning have revolutionized data interpretation, with hybrid models achieving R² > 0.99 prediction accuracy for corrosion rate forecasting through integration of swarm intelligence optimization with deep learning architectures . Four-dimensional impedance analysis has emerged for time-varying systems, enabling instantaneous impedance determination during non-stationary corrosion processes . This review concludes that effective corrosion characterization requires integrated approaches combining complementary techniques with advanced data analytics, bridging laboratory mechanistic understanding with field-applicable monitoring solutions.

Abstract Cartilage repair remains a significant clinical challenge due to the tissue’s limited self-healing capacity, avascular structure, and complex mechanical requirements. Recent advances in additive manufacturing have enabled the fabrication of patient-specific scaffolds with controlled architecture and tunable mechanical properties. Among high-performance biomaterials, polyether ether ketone (PEEK) has emerged as a promising matrix material owing to its excellent chemical stability, thermal resistance, and mechanical strength. However, pristine PEEK is bioinert and hydrophobic, limiting its biological performance in cartilage regeneration. To address this limitation, fiber reinforcement and bioactive filler incorporation have been widely investigated to enhance both mechanical and biological functionality. This study provides a comparative analysis of different fiber types incorporated into 3D-printed PEEK composites for cartilage repair, considering fiber composition (carbon, glass, ceramic, natural, and polymeric), size (Nano to micro-scale), length (short, long, continuous, discontinuous), morphology, and volume fraction. The influence of fiber characteristics on mechanical performance—including tensile strength, compressive modulus, fatigue resistance, and interfacial bonding—as well as biological responses such as cell adhesion, proliferation, and extracellular matrix formation, is critically evaluated. Furthermore, the interaction between fiber selection and 3D printing parameters, including build orientation, infill density, layer thickness, and extrusion temperature, discussed. Comparative findings suggest that hybrid reinforcement systems, particularly short carbon fibers combined with bioactive Nano-fillers such as Nano-hydroxyapatite or graphene oxide, offer an optimal balance between mechanical integrity and bioactivity. Continuous carbon fibers provide superior strength but limited biological enhancement, whereas Nano-scale bioactive reinforcements improve cellular responses with moderate mechanical gains. Strategic optimization of fiber type, geometry, and processing conditions is essential to achieve mechanically robust and biologically functional 3D-printed PEEK scaffolds for cartilage regeneration.

Abstract Graphene oxide (GO) has emerged as a transformative nanomaterial for advanced corrosion protection coatings, leveraging its unique two-dimensional lamellar architecture and abundant surface functional groups to provide both passive barrier properties and active inhibition capabilities. This comprehensive review systematically examines the multifaceted role of GO in multifunctional coatings, focusing on how surface functionalization and 2D lamellar structure synergistically enhance barrier properties and active corrosion protection. The physical barrier mechanism of GO arises from its high aspect ratio and impermeable nature, creating tortuous diffusion paths for corrosive species, with a 0.03 wt% addition to geopolymer coatings achieving high impedance modulus and ultra-low corrosion current density through a triple synergistic protection system integrating physical barrier, chemical adsorption, and structural reinforcement . Surface functionalization strategies—including carboxylation (-COOH), hydroxylation (-OH), amination (-NH₂), and dopamine/nano-TiO₂ co-modification—critically influence coating performance by improving dispersion, enhancing interfacial compatibility, and introducing active inhibition functionality . Dopamine and nano-TiO₂ co-modified GO demonstrates superior corrosion resistance through synergistic effects: polydopamine enhances dispersion while TiO₂ provides passivation film effects, covering CO groups on GO surface . Carboxylated GO (CGO) composites outperform hydroxylated and aminated counterparts, with CGO-15 coating achieving two orders of magnitude higher impedance modulus than pure resin and over 90% inhibition of sulfate-reducing bacteria through ROS-mediated oxidative stress . The interlayer entanglement toughening strategy improves GO paper delamination strength by 268%, approaching benchmark natural nacres . This review concludes that integrated design combining molecular functionalization, 2D architecture optimization, and multi-component hybridization offers transformative potential for durable, high-performance protective coatings.

Abstract This study explores the effects of temperature and pressure variations on catalyst degradation mechanisms—specifically catalyst crushing and catalyst cake formation—in a light naphtha isomerization unit. Operating conditions within the range of 200–280°C and 10–35 bar were simulated to evaluate mechanical and physical stress on the catalyst bed. Two performance indices were defined: the Catalyst Crushing Index (CCI) and Catalyst Cake Thickness (CCT). Results revealed that both CCI and CCT increase significantly with rising temperature and pressure, with pressure having a more pronounced impact. Elevated pressure intensified catalyst compaction, while temperature contributed to structural weakening and sintering. The analysis showed that high-pressure environments above 25 bar and temperatures exceeding 260°C led to accelerated crushing and cake buildup, contributing to pressure drop, pore blockage, and reduced hydrogen diffusion. These degradation mechanisms ultimately reduce catalytic activity and operational efficiency. The findings suggest that maintaining optimal reactor conditions and incorporating real-time monitoring systems are essential for preventing early catalyst failure. This research provides a predictive framework for improving catalyst performance and life cycle in isomerization processes and can support operational decision-making in refinery settings.

Abstract During treatment with chemotherapy drugs, many cancers become resistant to the therapeutic effects of the drugs used. Various mechanisms have been proposed in relation to drug resistance. One of the most important reasons for drug resistance is the high expression of ATP-dependent membrane proteins from the large family of membrane transporters (ATP Binding Cassette ABC). From this family, the membrane transporter with a molecular weight of 170 KDa named glycoprotein P plays an important role in drug resistance. Other membrane proteins from the MRP (Multidrug Resistance Associated Protein) family are also involved in drug resistance. ABC proteins are also expressed in normal cells. The mentioned proteins are responsible for the transfer of endogenous substrates. The high expression of these proteins in cancer cells is the most important obstacle to cancer treatment. The range of clinical responses is caused by the medicinal qualities of the treatment as well as the internal and acquired molecular and physical characteristics of cancer cells and external environmental factors. The latter can be caused by several factors, such as increased DNA repair capacity, altered drug metabolism, mutated or altered drug targets, reduced drug accumulation, and inactivated cell death signals. Cancer stem cells (CSCs) show drug resistance. Because transporters overexpress adenosine triphosphate (ATP) binding cassette. Through specific regulatory genes, FOXM1, a transcription factor specific for cell proliferation, controls the transition between G1/S and G2/M cell cycle phases. In addition, it is an oncogene that causes the expansion and proliferation of cancer cells. Via ABCC5 (ATP binding cassette subfamily member 5) expression, FOXM1 overexpression causes paclitaxel resistance in nasopharyngeal carcinoma.

Abstract Lithium-ion batteries have changed the landscape of energy storage and ushered in a new era of clean, efficient and sustainable energy solutions. From powering our smartphones and laptops to fueling the transportation and renewable energy sectors, lithium-ion batteries are essential to modern life. The main goal of the innovative technology is to solve one of the old challenges of the battery industry: The erosion of liquid electrolytes. As research and innovation continue to push the boundaries of battery technology, the future holds exciting opportunities for even more efficient, safer and environmentally friendly energy storage solutions. By harnessing the potential of lithium-ion batteries, we can pave the way to a greener and more electrified future for generations to come. Additionally, this solution can improve battery safety by reducing the risk of thermal runaway – a common concern in older lithium-ion batteries. This development is in line with phenomena such as the global determination for sustainable energy solutions as well as the increasing demand for high-performance batteries.

Abstract Sensors are devices that convert physical properties into electrical signals. For example, temperature sensor, humidity sensor, presence detection sensor, etc. These sensors acquire information from the real world. Air quality sensors detect various air pollutants, gases and suspended particles and provide information about air quality in terms of health and environmental standards. They are used in a variety of applications from indoor air quality monitoring in homes and offices to outdoor air quality monitoring for environmental and public health purposes. Smart sensors generate and receive data and information that goes beyond traditional switching signals or measured parameters. They take input from the physical environment and, after identifying the input using internal computing resources, process the data before sending it. These devices are used for monitoring and control mechanisms in various environments, including smart networks, environmental detection, discoveries and scientific applications. Smart sensor is a vital and integral element in the Internet of Things. All these were once done as manual processes, but with the presence of smart sensors, these processes are done automatically. Smart sensors also play a key role in the development of modern security systems. Thermal imaging sensors detect the body heat of an intruder. Similarly, devices such as smart locks, motion sensors, and window and door sensors are usually connected to a common network. This allows security sensors to work together to create a comprehensive picture of the current security situation. They are also often used in homes and industrial applications to detect various leaks.

Abstract In recent years, the applications of nanoparticles separately and independently of nanotechnology have made significant progress, for example, the production of nanoparticle photo catalysts has significantly increased the catalytic efficiency of certain materials, and the variety of their applications has been developed. The spread of pollutants in surface water and groundwater has become an important issue worldwide due to population growth and the rapid development of industrialization. Therefore, it is necessary to control the harmful effects of pollutants and improve environmental conditions. Recently, the use of nanoparticles to remove environmental pollution and remove organic pollutants has caused photo catalysts and their potential applications to be widely considered. Photo catalysts are materials that receive energy from a specific wavelength of light and cause a reaction to occur. The catalytic principle of visible light is based on the visible light irradiation light catalyst, the capacity band of the catalyst is from the electron transfer of the ground state of light to the conduction band, the generation of holes born from light and photo electronics, the holes of light with water molecules to produce hydroxyl free radicals, electrons and molecule reactions Oxygen produces superoxide anion and holes, hydroxyl radicals, and superoxide anion production. Reactive oxygen species can break down odor molecules, organic matter, bacteria, and other pollutants into water, carbon dioxide, and other small molecules. A small amount of N, S and P in organic matter produces nitrate, sulfate, phosphate, etc. after decomposition, to play the effect of detoxification, deodorization and sterilization. Visible light photocatalytic coating technology offers a new green solution for indoor and outdoor air purification.

Abstract The global economic landscape is constantly changing and has cast a shadow over the global economy. Just this year (2024), presidential elections, military conflicts, and escalation of tensions have made understanding geopolitical risks especially important for forex traders. Supply chain dynamics refers to various factors and interactions that affect the supply of goods, services, information and financial affairs in a supply chain network. Factors that can affect supply chain dynamics include: changes in consumer demand, market trends, developments technological, regulatory requirements, economic conditions, geopolitical events and disruptions such as natural disasters or pandemics, understanding supply chain dynamics for organizations to effectively manage supply chains, optimize operations, reduce Risks and adaptation to changing market conditions are very important. Both of these conflicts could potentially disrupt the global supply of oil and gas in 2024, and hence geopolitical and supply chain issues are the hot topics of 2024 in the energy field. According to Global Data, a leading data and analytics company, it is important for the oil and gas industry to assess the impact of these issues as they chart their growth plans. Global Data’s thematic report, entitled Top 20 oil and gas issues in 2024, includes challenges that can have a significant impact on oil and gas production and supply operations in 2024. Concerns related to the security of energy supply are expected to be the main challenge for the oil and gas business in 2024.

Abstract In many industrial applications, the presence of selectable catalysts in terms of molecular shape and size is of particular importance. The most significant feature of metal-organic structures, which has made their application important in the catalytic discussion, is the absence of dead space that cannot be accessed. Also, in such regular structures, the active sites are well separated from each other, and on the other hand, the very high surface area of these structures provide the possibility of having a high density of active sites per unit volume of the catalyst. Organometallic compounds are materials that have at least one carbon-metal bond in their structure and contain pseudo metals such as B, As, Si and real metals. Organic compounds are widely used in industry and environment. They play a role as cleaners and catalysts in industrial processes and are used in the environment because of their compatibility with it. Characterization was done in a similar way for new catalysts. The characterization tests showed that the presence of oxygen-donating ligands in the structure of manganese catalyst increases the specific surface area, dispersion of manganese particles and abundance of oxygen holes and decreases the level of crystallinity. The maximum catalytic activity was related to 12Mn-BTCarg/Al5,0.4 calcined in argon atmosphere. The activity of the optimal catalysts of each part was investigated in the activation of hydrogen peroxide to remove the drug azithromycin in aqueous solution. The catalytic elimination reaction of azithromycin followed a pseudo-first-order kinetic model. For V-DETA-MIL-101 catalyst, the amount of 15 mg of catalyst, 1.12 mmol of tertiobutyl hydrogen peroxide and 1 ml of carbon tetrachloride solvent at 80℃ temperature were selected as optimal conditions.

Abstract Today, artificial intelligence (AI) has emerged as a vital tool and a driver of innovation in the oil, gas, and petrochemical industries. The use of AI in oil and gas exploration has transformed the capabilities of the industry and made the search for new reserves more efficient and reliable. AI can identify areas with high potential for oil and gas exploration by analyzing geological and geophysical data. These analyses can increase the accuracy and speed of exploration processes and reduce the costs associated with these processes. AI can analyze and summarize large and complex data and provide valuable information for strategic decision-making. AI and machine learning in the oil and gas industry are revolutionizing the exploration process by analyzing vast datasets, including seismic surveys, well logs, satellite imagery, and geological data. Machine learning algorithms can identify patterns and anomalies in this data, helping geologists more effectively identify potential oil reservoirs. For example, consider a scenario in which an exploration team is looking to identify offshore drilling sites. Rather than relying on traditional geological methods, the team is applying AI applications to the oil and gas industry. The AI system ingests data from multiple sources and performs complex analysis to identify areas most likely to contain oil reserves. This focused approach reduces exploration time and costs and minimizes environmental impact by drilling only in areas with high potential. AI also enhances the interpretation of seismic data, a critical aspect of oil exploration.

Abstract Introduction: Trauma patients undergoing femoral intramedullary nailing surgery often experience significant blood loss, leading to the need for effective management strategies. Dexmedetomidine, an alpha-2 adrenergic agonist, has shown promise in reducing intraoperative blood loss and stabilizing hemodynamics, making it a potential adjunct in trauma surgeries.

Methods: In this double-blind, randomized controlled trial, 60 trauma patients undergoing femoral intramedullary nailing were randomly assigned to either the dexmedetomidine (n = 30) or control (n = 30) group. The dexmedetomidine group received an infusion of 0.6 µg/kg for 10 minutes before induction, followed by a maintenance dose. Intraoperative blood loss, transfusion requirements, heart rate, and systolic blood pressure were assessed. Statistical analyses were performed using independent t-tests and chi-square tests, with p-values < 0.05 considered significant.

Results: The dexmedetomidine group exhibited significantly lower intraoperative blood loss (p = 0.001) and more stable hemodynamic parameters, including heart rate and systolic blood pressure (p < 0.05). The need for blood transfusions was lower in the dexmedetomidine group, although not statistically significant (p = 0.073). Recovery time was also significantly shorter in the dexmedetomidine group (p = 0.002).

Conclusion: Dexmedetomidine significantly reduced intraoperative blood loss and stabilized hemodynamic parameters in trauma patients undergoing femoral intramedullary nailing surgery. Its potential benefits for trauma surgery include reduced transfusion needs and faster recovery times.