Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed
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Publication Metadata only Influence of graphene nanoplate size and heat flux on nanofluid heat exchanger performance: A molecular dynamics approach(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Yang, Zhongxiu; Basem, Ali; Jasim, Dheyaa J.; Singh, Narinderjit Singh Sawaran; Saeidlou, Salman; Al-Bahrani, Mohammed; Sajadi, S. Mohammad; Salahshour, Soheil; Hasanabad, Ali Mohammadi; Weifang University of Science & Technology; University of Warith Alanbiyaa; Al-Maarif University; INTI International University; Canterbury Christ Church University; Al-Mustaqbal University College; Okan University; Bahcesehir University; Ministry of Education of Azerbaijan Republic; Khazar UniversityThis study aimed to enhance the thermal efficiency of nanofluid-based heat exchangers by exploring the simultaneous effects of external heat flux and graphene nanoplate sizes on thermal and structural characteristics. Effective heat transfer is a critical requirement for managing heat in microscale systems, where optimizing the thermal performance of nanofluids can improve device performance. Molecular dynamics simulations were carried out of a sinusoidal inner surface copper heat exchanger coated with silicon nanoparticles to demonstrate atomic-level interaction within the nanofluid. The significant findings showed that while an external rising heat flux decreased heat flux from 41.7 to 37.26 W/m2 and thermal conductivity of nanofluid from 14.53 to 13.80 W/ m & sdot,K, only an increase in viscosity from 0.32 to 0.49 mPa & sdot,s, the agglomeration time of nanoparticles decreased from 3.71 to 3.33 ns and friction coefficient from 0.022 to 0.015, could indicate a difference in particle behavior responding to the thermal stress. However, the size of the graphene nanoplate from 5 to 15 & Aring, increases the heat flux from 40.05 to 46.77 W/m2 and thermal conductivity of the nanofluid from 14.15 to 14.99 W/m & sdot,K, since the larger graphene nanoplate films can produce a more substantial covalent bonding and link interlayer coupling. In contrast, the larger nanoplate also enhanced viscosity from 0.30 to 0.39 mPa & sdot,s, aggregation time from 3.64 to 4.01 ns, and friction coefficient from 0.020 to 0.026, which indicated lower particle mobility. This study was the first of its kind to contribute to the existing knowledge gap by investigating the simultaneous effect of both the nanoplate size and external heat flux in an oscillating microchannel heat exchanger. The knowledge provided offers an experimental pathway in optimizing the nanofluid properties and the heat exchanger geometry for improved thermal management for compact and microscale applications.Publication Metadata only Modeling the mechanical behavior of platinum-graphene nanocomposites prepared via powder metallurgy at various initial temperatures and pressures(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Ru, Yi; Basem, Ali; Hussein, Rasha Abed; Singh, Narinderjit Singh Sawaran; Al-Bahrani, Mohammed; Salahshour, Soheil; Mokhtarian, Ali; Hekmatifar, M.; Wang, Mengxia; University of Toronto; University of Warith Alanbiyaa; University of Manara; INTI International University; Al-Mustaqbal University College; Okan University; Bahcesehir University; Ministry of Education of Azerbaijan Republic; Khazar University; Islamic Azad University; Zhejiang University of Technology; Hangzhou Medical College; Zhejiang Provincial People's HospitalIntroduction: This study investigated the mechanical properties of platinum-graphene nanocomposites synthesized through powder metallurgy, focusing on how temperature and pressure affected their behavior. The aim was to understand these influences, which are crucial for industrial and medical applications. Using molecular dynamics simulations, the study investigated to optimize these materials for enhanced performance, particularly in improving the biocompatibility of platinum-based materials for medical use. Development: This study aimed to analyze the impact of various temperatures and pressures on the stress-strain curve, ultimate strength, and Young's modulus of platinum-graphene nanocomposites using molecular dynamics simulations. The study examined how these factors influenced the material's performance under different conditions. Conclusion: The results indicate that ultimate strength decreased from 116 to 105 MPa, and Young's modulus decreased from 1099 to 1000 MPa as temperature increased from 300 to 400 K. This decrease was due to higher temperatures causing increased atomic vibrations and weaker interatomic bonds, reducing resistance to deformation and failure. Similarly, fracture stress decreased from 106.744 to 97.655 MPa, and the strain ratio decreased from 27.15 to 25.92 at the fracture stress point with rising temperature. Conversely, changing the pressure from 1 to 5 bar resulted in an increase in Young's modulus and ultimate strength to 1297 MPa and 137 MPa, respectively. Higher pressure enhanced atomic packing, strengthening interatomic bonds and improving fracture resistance. At 5 bar pressure, fracture stress rose from 106.744 to 119.40 MPa, while the strain ratio at the fracture stress point increased from 27.15 to 31.914. In conclusion, temperature and pressure significantly influenced the mechanical properties of platinum-graphene nanocomposites, impacting their industrial and medical applications.Publication Metadata only Numerical investigation of the heat flux frequency effect on the doxorubicin absorption by Bio MOF11 carrier: A molecular dynamics approach(ELSEVIER, 2024) Ben Said, Lotfi; Basem, Ali; Jasim, Dheyaa J.; Aljaafari, Haydar A. S.; Ayadi, Badreddine; Aich, Walid; Salahshour, Soheil; Eftekhari, S. Ali; University Ha'il; Universite de Sfax; Ecole Nationale dIngenieurs de Sfax (ENIS); University of Warith Alanbiyaa; Al-Amarah University College; University of Iowa; University of Technology- Iraq; Universite de Sfax; Ecole Nationale dIngenieurs de Sfax (ENIS); Universite de Monastir; Okan University; Bahcesehir University; Lebanese American University; Islamic Azad UniversityThe present study investigated the effect of heat flux frequency on doxorubicin adsorption by bio MOF11 biocarrier using molecular dynamics simulation. This simulation examined the effect of several heat flux frequencies (0.001, 0.002, 0.005, and 0.010 1/fs) on the quantity of drug particles absorbed, mean square displacement (MSD), diffusion coefficient, and interaction energy. The present outputs of simulations predicted the structural stability of the modeled MOF-drug system in 300 K. Also, simulation outputs predicted by frequency optimization, the adsorption of target drug inside MOF11 maximized, and efficiency of this sample in actual clinical applications, such as drug delivery process increased. Numerically, the optimum value of frequency was estimated to be 0.005 1/fs. Using this heat setting, the interaction energy between MOF 11 and the doxorubicin drug increased to -929.05 kcal/mol, and the number of penetrated drug particles inside MOF11 converged to 207 atoms. The results reveal that the MSD parameter reached 64.82 angstrom 2 after 100000 -time steps. By increasing frequency to 0.005 fs-1, this increased to 78.05 angstrom 2. By increasing MSD parameter, the drug diffusion process effectively occurred, and the diffusion coefficient increased from 67.29 to 82.47 nm2/ns. It is expected that the findings of present investigation guide the design of more efficient drug delivery platforms, enhance drugcarrier interactions, improve manufacturing processes, and aid in developing novel nanomaterials with enhanced adsorption properties for various applications.Publication Metadata only The effect of initial pressure and atomic concentration of iron nanoparticles on thermal behavior of sodium sulfate/magnesium chloride hexahydrate nanostructure by molecular dynamics simulation(ELSEVIER, 2024) Huang, Yijin; Kamoon, Saeed S.; Kaur, Mandeep; Basem, Ali; Khaddour, Mohammad H.; Al-Bahrani, Mohammed; Salahshour, Soheil; Zekri, Hussein; Emami, Nafiseh; Guangxi Normal University; Jain University; Vivekananda Global University; University of Warith Alanbiyaa; Al-Amarah University College; Al-Mustaqbal University College; Okan University; Bahcesehir University; Lebanese American University; University of Zakho; Islamic Azad UniversityThermal energy storage (TES) is one of the uses of phase change material (PCM). The primary factor contributing to this capability is the elevated latent heat of melting present in these materials. The current study investigates the effect of initial pressure (IP) (ranging from 1 to 5 bar), and atomic ratio (AR) of Iron nanoparticles (NPs) (Fe = 1, 2, 3, and 5 %) on the thermal behavior (TB) and phase transition process of sodium sulfate/Magnesium chloride hexahydrate (Na 2 SO 4 /MgCl 2 & sdot, 6H 2 O) nanostructures as PCMs using molecular dynamics (MD) simulation. The simulated PCM was positioned inside a spherical atomic channel composed of iron. The TB of simulated nanostructures was examined by reporting changes in viscosity (Vis), thermal conductivity (TC), and phase transition time (PTT). The results reveal that by increasing IP from 1 to 5 bar, the PTT reaches from 3.50 to 3.61 ns, and the TC decreases from 1.03 to 0.94 W/m.K. The results show that adding 3 % of Fe NPs was the optimal ratio to improve the TB of the Na 2 SO 4 /MgCl 2 & sdot, 6H 2 O-Fe NP. By raising the ratio of Fe NPs from 1 to 3 %, Vis slightly decreased from 4.31 to 4.22 mPa.s. In comparison, adding more Fe NPs with 5 % ratio raised the Vis to 4.30 mPa.s. According to the results, increasing the IP decreased the distance among the particles. So, the attraction among particles increased, leading to greater adhesion and Vis. By increasing the IP, the distance among atoms decreases, and the space between NPs and atoms in the simulation box decreases. Consequently, NP movement and fluctuations decrease, and collisions decrease. The results of this simulation will be effective in heating - cooling and ventilation systems, automotive industries, textile industries, and so on.Publication Metadata only A comprehensive review of data analytics and storage methods in geothermal energy operations(ELSEVIER, 2025) Basem, Ali; Al-Nussairi, Ahmed Kateb Jumaah; Khidhir, Dana Mohammad; Singh, Narinderjit Singh Sawaran; Baghoolizadeh, Mohammadreza; Fazilati, Mohammad Ali; Salahshour, Soheil; Sajadi, S. Mohammad; Hasanabad, Ali Mohammadi; University of Warith Alanbiyaa; University of Manara; Knowledge University; INTI International University; Shahrekord University; Islamic Azad University; Okan University; Bahcesehir University; Ministry of Education of Azerbaijan Republic; Khazar UniversityGeothermal energy storage (GES) systems are thoroughly examined in this research, with a focus on methods like borehole thermal energy storage (BTES), underground thermal energy storage (UTES), and aquifer thermal energy storage (ATES). It highlights the importance of thermal energy storage (TES) systems in addressing global energy challenges. The feasibility of UTES for large-scale energy storage and its integration with geothermal power plants is investigated. The ATES, with the advantage of large storage capacity and low operating costs has could be employed in regions with suitable aquifers. The adaptability of BTES to different ground conditions and its small land footprint made it a spotlight for the researchers. The study emphasizes the role of TES technologies in meeting the growing demand for renewable energy, reducing the impact of climate change, and providing efficient energy solutions for heating, ventilating, and air conditioning. HVAC systems. Also, the application of geothermal power plants and TES systems in decreasing the dependence on nonrenewable energy sources and increasing energy efficiency increase investigated. The development of reliable and affordable sensors, together with improvements in processing power, has made data-intensive algorithms and real-time operational decision-making applications in the field of geothermal energy. The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. It was shown that artificial neural networks were the most common kind of trained model, while several other models were often used as benchmarks for performance. Picture selection, systematic time series feature engineering and model evaluation were all areas that showed a lot of promise in the systematic review for future research and practical applications.Publication Metadata only Using different Heuristic strategies and an adaptive Neuro-Fuzzy inference system for multi-objective optimization of Hybrid Nanofluid to provide an efficient thermal behavior(ELSEVIER, 2024) Wang, Zhe; Shami, Hayder Oleiwi; Kazim, Khudhaier J.; Basem, Ali; Al-fanhrawi, Halah Jawad; Dacto, Karina Elizabeth Cajamarca; Salahshour, Soheil; Khajehkhabaz, Mohammad; Eftekhari, S. Ali; Chinese Academy of Sciences; National Center for Nanoscience & Technology, CAS; Al-Amarah University College; Misan University; University of Warith Alanbiyaa; Al-Mustaqbal University College; Universidad Nacional de Chimborazo; Okan University; Bahcesehir University; Lebanese American University; Islamic Azad UniversityThe importance of multi-objective optimization in hybrid nanofluid research lies in its wide-ranging applications across fields such as microelectronics, aerospace, and renewable energy. These specialized fluids hold the potential to elevate the performance and efficiency of diverse systems through enhanced heat transfer capabilities. This research endeavor is centered around optimizing a hybrid nanofluid composed of Silicon Oxide-MWCNTAlumina/Water by leveraging a mix of heuristic approaches and an adaptive neuro-fuzzy inference system. To this end, the most influential set of input parameters has been identified using four state-of-the-art algorithms: Non-dominated Genetic Algorithm, multi-objective particle swarm optimization, Strength Pareto Evolutionary Algorithm 2, and Pareto Envelope-based Selection Algorithm 2. The goal of the optimization process is to modify the temperature (T = 20 degrees C to 60 degrees C) and the volume fraction of nanoparticles (SVF=0.1 % to 0.5 %). Finding the optimal combination of these parameters that results in the hybrid nanofluid with the maximum thermal conductivity (knf) and the lowest dynamic viscosity is the main objective. The findings of this research have the potential to drastically improve the performance of systems in a variety of applications and to change the creation of sophisticated, high-efficiency heat transfer fluids.Publication Metadata only Effect of channel thickness on the particle diffusion and permeability of carbon nanotubes a membrane in reverse electrodialysis process using molecular dynamics simulation(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Sun, Shuai; Basem, Ali; Singh, Narinderjit Singh Sawaran; Al-zahy, Younis Mohamed Atiah; Saeidlou, Salman; Muzammil, Khursheed; Salahshour, Soheil; Sajadi, S. Mohammad; Sahramaneshi, Hani; Shandong Huayu University of Technology; Dongshin University; University of Warith Alanbiyaa; INTI International University; Misan University; Canterbury Christ Church University; King Khalid University; Okan University; Bahcesehir University; Ministry of Education of Azerbaijan Republic; Khazar UniversityAdopting innovative technology and solutions is critical for ensuring clean water. Several methods may be used to remove salts from water. They may be divided into two categories: membranes and heat. Reverse electrodialysis, which uses a membrane, is an efficient way of separating substances. Prior research investigated systemlevel factors, but the nanoscale mechanisms that drive ion and water penetration across membranes were poorly understood. This study closed a research gap by investigating the influence of carbon nanotube membrane thickness on particle mobility and fluid dynamics in reverse electrodialysis systems. The research is contributed to the enhancement of energy conversion efficiency and membrane performance in reverse electrodialysis systems by offering a comprehensive understanding of the influence of channel thickness on particle transport and selectivity through the carbon nanotube membrane. Molecular dynamics simulations using the LAMMPS software package are conducted to examine the effect of carbon nanotube thickness variation (1-layer vs 2-layer) on fluid flow, ionic current, hydrogen bonding, and fluid density. To the findings, increasing the thickness of a carbon nanotube from one layer to two layers decreases the fluid flow rate to 203.79 atoms/ns and the current from 5.31 e/ns to 5.15 e/ns. Additionally, the number of broken hydrogen bonds decreases from 116 to 105, indicating decreased permeability and increased stability of the hydrogen-bonding network. In addition to offering useful information for the construction of more effective and selective membranes in renewable energy applications, these results provided a molecular understanding of how carbon nanotube thickness affected reverse electrodialysis effectiveness.Publication Metadata only Investigation of the effect of model structure type on the thermal performance of phase change materials through molecular dynamics simulation(ELSEVIER, 2024) Aich, Walid; Basem, Ali; Sultan, Abbas J.; Ghabra, Amer Ali; Eladeb, Aboulbaba; Kolsi, Lioua; Salahshour, Soheil; Baghaei, Sh.; University Ha'il; Universite de Monastir; University of Warith Alanbiyaa; University of Technology- Iraq; University of Missouri System; Missouri University of Science & Technology; Al-Amarah University College; Northern Border University; Okan University; Bahcesehir University; Lebanese American University; Islamic Azad UniversityUsing molecular dynamics (MD) simulation, the thermal efficacy of phase change materials (PCMs) in solar energy applications and solar thermal energy storage was evaluated. In order to achieve this objective, an investigation was conducted into the structure's temperature (Temp), velocity, and density profiles, heat flux, thermal conductivity, charge and discharge time, and thermal stability. Three models of tube, shell, and shell-tube were adopted to scrutinize the atomic behavior and thermal performance (TP) of PCMs. The results show that the maximum density of the tube model, shell model, and shell-tube model was 0.042, 0.036, and 0.033 atom/A 3 , respectively. Other numerical results showed that the maximum velocity for the three structures of tube model, shell model, and shell-tube model under the initial Temp of 300 K was 0.0066 & Aring,/fs, 0.0059 & Aring,/fs, and 0.0054 & Aring,/fs, respectively. The structure in the tube model manifested more optimal atomic behavior compared to other models. The TP of simulated structures revealed that the heat flux of the samples reached 5.69, 4.85, and 4.15 W/m 2 , respectively. Finally, the thermal conductivity of the structures approached 1.35, 1.32, and 1.31 W/m.K, respectively. The results suggested that the tube model had the most thermal stability and showed the optimal thermal behavior in the simulation. The findings of this study, particularly the optimal atomic behavior and thermal stability of the tube model, can be useful in designing and optimizing PCMs for solar energy applications. In general, this research had the potential to significantly advance the field of solar energy system efficiency and cost-effectiveness.Publication Metadata only Thermal and mechanical attributes and swelling percentage of hydrogels by changing in magnetic field frequency using computer simulation(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Wang, Haoyu; Basem, Ali; Alhamdi, Sabah F. H.; Singh, Narinderjit Singh Sawaran; Al-Bahrani, Mohammed; Abdullaeva, Barno; Salahshour, Soheil; Esmaeili, Sh.; Xijing University; University of Warith Alanbiyaa; Misan University; INTI International University; Al-Mustaqbal University College; Tashkent State Pedagogical University; Okan University; Bahcesehir University; Ministry of Education of Azerbaijan Republic; Khazar UniversityThe thermodynamic, mechanical, and expansion properties of synthetic hydrogels derived from polyacrylamide (PAM) are investigated in this study to the impact of magnetic field frequency (MFF) as an external stimulus. The impact of various MFFs on essential parameters, such as swelling percentage (SP), ultimate strength (US), Young's modulus (YM), heat flux (HF), and thermal conductivity (TC), is assessed using Molecular Dynamics (MD) simulation with LAMMPS software, ranging from 0.01 to 0.05 1/fs. It is important to note that our results indicate that the structural volume decreased from 356,985 to 349,982 & Aring, at 0.05 1/fs as the MFF increased. The alignment of polymer chains in the hydrogel was improved by increasing the MFF, resulting in a more compact structure. Through this compaction, the total structural volume diminished as the chains were drawn closer together, thereby reducing the spaces among them. US experienced a decrease from 0.0325 to 0.0331 MPa, while YM converged to 0.0008 MPa. The alignment and packaging of polymer chains improved, resulting in an increase in the US of hydrogels as the MFF increased. This enhanced alignment resulted in a material that can withstand a larger amount of stress before failing, as a result of the stronger intermolecular interactions. Additionally, the temperature coefficient (TC) increased to 0.56 W/m & sdot,K as the MFFs increased. An increase in molecular alignment and a decrease in free volume within the hydrogel can be attributed to the higher MFF. This enhanced alignment enabled the molecules to transfer heat more efficiently, resulting in improved TC and increased HF. These findings illustrate the substantial influence of MFF on hydrogel properties, offering valuable insights for the development of drug delivery systems and responsive materials.Publication Metadata only Utilizing machine learning algorithms for prediction of the rheological behavior of ZnO (50%)-MWCNTs (50%)/ Ethylene glycol (20%)-water (80%) nano-refrigerant(PERGAMON-ELSEVIER SCIENCE LTD, 2024) Song, Xiedong; Baghoolizadeh, Mohammadreza; Alizadeh, As'ad; Basem, Ali; Jasim, Dheyaa J.; Sultan, Abbas J.; Salahshour, Soheil; Piromradian, Mostafa; Jining University; Inner Mongolia University of Finance & Economics; Shahrekord University; Cihan University-Erbil; Al-Amarah University College; University of Warith Alanbiyaa; University of Technology- Iraq; University of Missouri System; Missouri University of Science & Technology; Okan University; Bahcesehir University; Lebanese American University; Islamic Azad UniversityThis paper aims to explore the utilization of machine learning techniques for the accurate prediction of rheological properties in a specific nanofluid system, ZnO(50 %)-MWCNTs (50 %)/Ethylene glycol (20 %)-water (80 %), designed for nano-refrigeration applications. The effective manipulation of the rheological behavior of nanofluids is pivotal for enhancing their heat transfer efficiency and overall performance. By harnessing the predictive power of machine learning, this study endeavors to unravel the intricate relationships governing the rheological characteristics of the nano-refrigerant, ultimately contributing to the development of advanced cooling solutions. The obtained results show that pnf of ZnO(50%)-MWCNTs (50%)/ Ethylene glycol(20%)-water (80%) nano-refrigerant is little affected by T, and even when T varies, this result does not alter much. Also, the lowest pnf occurs when it has the highest temperature and the lowest gamma and m. Finally, it was concluded that the best algorithm in terms of the Taylor diagram for pnf output is the MPR algorithm and the worst is the ECR algorithm and the pattern of gamma changes shows that the ideal value of gamma is the biggest when pnf levels fall in tandem with their growth.