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TO EVALUATE THE PERFORMANCE OF MOLTEN SALT COOLANTS IN PARABOLIC TROUGH COLLECTORS (PTCs)

International Journal of Energy for a Clean Environment 2025年第2期26卷 13-33页

作者： Raheem, Aneeq Siddique, Waseem Awais, Muhammad Qureshi, Kamran Nawaz, Rab Shabbir, Muzammil Ahmad Department of Mechanical Engineering Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Department of Nuclear Engineering Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan Department of Mechanical Engineering National University of Science and Technology Islamabad44000 Pakistan

Renewable energy sources such as solar, wind, hydro, and geothermal are potential energy sources with the capacity to mitigate environmental impacts. Parabolic trough collectors (PTCs) are the widely used application of solar energy. Molten salts are promising high-temperature, low-pressure coolants for thermal energy storage of concentrated solar power plants. The present novel work is aimed to develop a computational fluid dynamics (CFD) methodology for candidate molten salt coolants (FLiBe, Nafzirf, FliNaK, and NaNO3-NaNO2-KNO3) to compare their thermal hydraulic characteristics in terms of friction factor and Nusselt number distribution for a simple circular tube under turbulent flow conditions. This study is necessary for the thermal-hydraulic design of PTCs. The axial distributions of friction factor and Nusselt number of FliNaK, FLiBe, Nafzirf, and NaNO3 NaNO2-KNO3 salts in a simple circular tube under Reynolds number range of 20,000–100,000 have been compared. The predicted friction factor (f∞), Nusselt number (Nu∞), and hydrodynamic entrance length (LH) have been compared with available correlations for fully developed conditions. Blasius and Petukhov correlations adequately guessed the predicted f∞ of salts, whereas the Gneilinski correlation is found to be in close agreement with the predicted Nu∞ of salts, hence validating the proposed numerical scheme for investigating thermal-hydraulic characteristics of molten salts. NaNO3-NaNO2-KNO3 seems to be the potential candidate with high values of thermal efficiency for solar applications. © 2025 by Begell House, Inc.

关键词： Nusselt number

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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Thermodynamic aspects of higher-dimensional black holes in Einstein-Gauss-Bonnet gravity through exponential entropy

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Communications in Theoretical Physics 2025年第4期77卷 129-150页

作者： Sana Malik Abdul Jawad Shahid Chaudhary Mohammad Mahtab Alam Sanjar Shaymatov Shamaila Rani Department of Mathematics COMSATS University IslamabadLahore-CampusLahore 54000Pakistan Institute for Theoretical Physicsand Cosmology Zhejiang University of TechnologyHangzhou 310023China Department of Natural Sciences and Humanities University of Engineering and Technology LahoreNew CampusPakistan Department of Basic Medical Sciences College of Applied Medical ScienceKing Khalid UniversityAbha 61421Saudi Arabia Institute of Fundamental and Applied Research National Research University TIIAMEKori Niyoziy 39Tashkent 100000Uzbekistan University of Tashkent for Applied Sciences Str.Gavhar 1Tashkent 100149Uzbekistan Western Caspian University Baku AZ1001Azerbaijan

We assume exponential corrections to the entropy of 5D charged Ad S black hole solutions,which are derived within the framework of Einstein-Gauss-Bonnet gravity and nonlinear ***,we consider two distinct versions of 5D charged Ad S black holes by setting the parameters q→0 and k→0(where q represents the charge,and k is the non-linear parameter).We investigate these black holes in the extended phase space,where the cosmological constant is interpreted as pressure,demonstrating the first law of black hole *** focus extends to understanding the thermal stability or instability,as well as identifying first and second-order phase *** exploration is carried out through the analysis of various thermodynamic quantities,including heat capacity at constant pressure,Gibbs free energy(GFE),Helmholtz free energy(HFE),and the trace of the Hessian *** order to visualize phase transitions,identify critical points,analyze stability and provide comprehensive analysis,we have made the contour plot of the mentioned thermodynamic quantities and observed that our results are very *** investigations are conducted within the context of exponentially corrected entropies,providing valuable insights into the intricate thermodynamic behavior of these 5D charged Ad S black holes under different parameter limits.

关键词： black hole thermodynamics thermodynamics quantities thermal stability higher dimensional Einstein-Gauss-Bonnet black hole modified entropy

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Tunable and wideband high-performance rare earth-doped Ni-Mg-Cu-Zn nano ferrite-based meta-absorbers for C-band application

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Journal of Rare Earths 2025年第1期43卷 124-132,I0005页

作者： Majid Niaz Akhtar Magbool Alelyani Fatimah Mohammed AAlzahrani Abdullah Almohammedi Sabih Qamar MABaqir MIrfan Muhammad Azhar Khan Kheir SAlbarkaty ZAAlrowaili MSAl-Buriahi Institute of Physics The Islamia University of Bahawalpur63100BahawalpurPakistan Department of Radiological Sciences College of Applied Medical ScienceKing Khalid University61421bhaSaudi Arabia Department of Chemistry College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabi Department of Physics Faculty of ScienceIslamic University of Madinah42352.Saudi Arabia Department of Chemical Engineering Muhammad Nawaz Sharif University of Engineering and Technology(MNSUET)60000MultanPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadSahiwal Campus57000Pakistan Department of Physics Umm Al-Qura UniversityMakkah24382Saudi Arabia Department of Physics College of ScienceJouf UniversityP.O.Box:201474331SakakaSoudi Arabia Department of Physics Sakarya University6900SakaryaTurkey

Due to advanced technology,electromagnet interference and dissipation problems in the electronic and portable devices at GHz range are increasing *** absorbing materials with outstanding electromagnetic properties,wide bandwidth,and strong absorption are highly *** present investigation deals with the preparation of Ni-Mg-Cu-Zn(NMCZ)substituted nano ferrites with composition of Ni_(0.3)Mg_(0.2)Cu_(0.3)Zn_(0.2)X_(0.02)Fe_(1.98)O_(4)(X=Nd,Ho,Pr,Gd,Yb).X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),transmission electron microscopy(TEM),a vibratory sample magnetometer(VSM),and a Vector network analyzer(VNA)were used to investigate these rare earth-doped nanocrystalline ferrites'*** reveals the single spinel phase structure in all Ni-Mg-Cu-Zn *** spectroscopy shows the presence of tetrahedral and octahedral bands of spinel *** images reveal the lowest agglomeration for the Ho-doped NMCZ nano-spinel ferrites *** images show the hexagon shapes of the Yb-and Nd-doped NMCZ ***-doped NMCZ ferrites show more coercivity than other rare earth metals substituted NMCZ nanocrystalline *** analysis was used to calculate the magnetic features like initial permeability,magnetic anisotropy constant,remanence,coercivity,and magnetic ***-frequency switching field distributions(SFD)analyses were also *** characteristics such as losses,permittivity,modulus,Q,ac conductivity,and impedance of the Nd^(-),Ho^(-),Pr^(-),Gd^(-),Yb-doped Ni-Mg-Cu-Zn ferrites were *** minimum reflection loss(-57.3 dB)is found at 1.4 GHz for Pr-doped Ni-Mg-Cu-Zn ferrite ***,the reflection loss(RL)of-53.9 dB at 2.9 GHz is observed for Ho-doped Ni-Mg-Cu-Zn ferrite *** magnetization,low coercivity,outstanding magnetodielectric,and absorption properties of theNd^(-),Ho^(-),Pr^(-),Gd^(-)and Yb^(-)doped Ni-Mg

关键词： Rare earths Reflection loss Cubic phase Magnetodielectric Ni-Mg-Cu-Zn(NMCZ)meta-absorber

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Advanced Computational Modeling for Brain Tumor Detection:Enhancing Segmentation Accuracy Using ICA-Ⅰ and ICA-Ⅱ Techniques

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Computer Modeling in engineering & sciences 2025年第4期143卷 255-287页

作者： Abdullah A Asiri Toufique A.Soomro Ahmed Ali Faisal Bin Ubaid Muhammad Irfan Khlood M.Mehdar Magbool Alelyani Mohammed S.Alshuhri Ahmad Joman Alghamdi Sultan Alamri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Artificial Intelligence and Cyber Futures Institute Charles UniversityBathurstNSW 2795Australia Department of Electronic Engineering The University of LarkanoLarkana75660Pakistan Electrical Engineering Department Sukkur IBA UniversitySukkur65200Pakistan Computer Science Department Sukkur IBA UniversitySukkur65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajran61441Saudi Arabia Department of Radiological Sciences College of Applied Medical ScienceKing Khalid UniversityGuraigerAbha62521Saudi Arabia Radiology andMedical Imaging Department College of AppliedMedical SciencesPrince Sattam bin Abdulaziz UniversityKharj11942Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesTaif UniversityTaif21944Saudi Arabia

Global mortality rates are greatly impacted by malignancies of the brain and nervous ***,Magnetic Resonance Imaging(MRI)plays a pivotal role in detecting brain tumors;however,manual assessment is time-consuming and susceptible to human *** address this,we introduce ICA2-SVM,an advanced computational framework integrating Independent Component Analysis Architecture-2(ICA2)and Support Vector Machine(SVM)for automated tumor segmentation and ***2 is utilized for image preprocessing and optimization,enhancing MRI consistency and *** Fast-MarchingMethod(FMM)is employed to delineate tumor regions,followed by SVM for precise *** on the Contrast-Enhanced Magnetic Resonance Imaging(CEMRI)dataset demonstrates the superior performance of ICA2-SVM,achieving a Dice Similarity Coefficient(DSC)of 0.974,accuracy of 0.992,specificity of 0.99,and sensitivity of ***,themodel surpasses existing approaches in computational efficiency,completing analysis within 0.41 *** integrating state-of-the-art computational techniques,ICA2-SVM advances biomedical imaging,offering a highly accurate and efficient solution for brain tumor *** research aims to incorporate multi-physics modeling and diverse classifiers to further enhance the adaptability and applicability of brain tumor diagnostic systems.

关键词： Brain image segmentation MR brain enhancement independent component analysis brain tumor

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Design of Nonlinear Delay Differential System for Analyzing Vulnerabilities in Nanoscale Hardware Implants: A Deep Dive into Intelligent Computing Networks

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Nano 2025年第3期20卷

作者： Asif Raja, Muhammad Junaid Ali Masood, Zaheer Hussain, Ijaz Zameer, Aneela Mehmood, Ammara Raja, Muhammad Asif Zahoor Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Department of Electrical Engineering Capital University of Science and Technology Islamabad Pakistan Department of Computer and Information Sciences Pakistan Institute of Engineering & Applied Sciences Islamabad Pakistan School of Electrical and Data Engineering University of Technology Sydney Australia Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan

In the annals of contemporary innovation, the study of miniature marvels nanoscale hardware implants emerged as a pivotal instrument, scarcely perceptible to the naked eye, embodies a prowess of cutting-edge technologies and clandestine intrigue. The objective of this research is to introduce a time delay nonlinear system for nanoscale hardware implants vulnerabilities that portray the exploitation of a system by utilizing the stupendous knacks of advanced deep bidirectional long short-term memory (LSTM) networks for time series predictions. Firmware-level bugs present the potential for escalating privileges and executing of code remotely beneath the operating system, allowing for infiltration or complete intervention within a computer system. The designed deep bidirectional LSTM is configured to precisely predict and forecast the dynamic states of time delay differential system, offering a robust framework for mimicking delays that commonly manifest in the real cyber-physical systems. To orchestrate the system compromises in real scenarios through the activation of bugged hardware, time delay factors τ1 and τ2 are introduced to account the time delays necessary for exploiting the bugged and patched nodes, respectively. Synthetic data is generated to train the LSTM network for all scenarios of the model for the dynamics of bugged, compromised, patched nodes and these acquired information is used for training, testing and validation purposes regarding exploitation of the bugged hardware. Comparative analysis on exhaustive simulations revealed a minimal difference between the LSTM's predictions and those from the numerical outcomes with MSE in the range of 10-7, underscoring the network's effectiveness, robustness and stability in modeling complex system dynamics of hardware vulnerabilities. © 2025 World Scientific Publishing Company.

关键词： Firmware

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Influence of Heat on Fractionalized Nanofluid with Magnetic Field

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International Journal of applied and Computational Mathematics 2025年第1期11卷 1-15页

作者： Ramzan, Muhammad Amir, Muhammad Abbas, Shajar Nazar, Mudassar Jan, Rashid Al Agha, Afnan AL Garalleh, Hakim Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan Department of Civil Engineering College of Engineering Institute of Energy Infrastructure (IEI) Universiti Tenaga National (UNITEN) Putrajaya Campus Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia Mathematics Research Center Near East University TRNC Nicosia 99138 Turkey Department of Mathematical Science College of Engineering Universty of Business and Technology Jeddah 21361 Saudi Arabia

Numerous researchers have been drawn to the rheology of non-Newtonian fluids because of their diverse uses in the engineering and manufacturing fields, such as lubrication, plastic processing, and mining. Additionally, the characteristics of magnetohydrodynamics non-Newtonian fluids permit its widespread application in computer hard drives, loudspeakers, magnetic resonance imaging, the administration of magnetic medicines, and magnetic hyperthermia. The novelty of present study is the use of fourier’s and fick’s laws. The current work is focused on the analysis of heat and mass transfer in a magnetohydrodynamics Maxwell nanofluid flows across an inclined vertical plate because of these possible uses. The values of angle of inclination is chosen in the range 0 to π3. From Table 1, the values of nanoparticles lies in the range of 0.012–0.18. Using suitable non-dimensional variables, ordinary differential equations are created from the modeling equations, and the Laplace transform method is used to solve these equations. Semi-analytical solutions for temperature, concentration, Bio-Convection, and velocity are found after employing the Laplace transform approach to address the issue. The study highlights several key outcomes likes velocity of fluid is increased with increasing values of Gr but decreased with increasing values of Pr, M, and maxwell parameter. The effect of increasing values of parameters R, L1, and N1 are seen to suppress the concentration profile. The bioconvection concentration profile increases with Φ but reduced with increasing values of L2. Furthermore, the comparison between ordinary and fractionalized maxwell fluid has been drawn. The application of the unsteady flow of nanofluid over a plate with the CPC operator has the potential to impact a wide range of solar energy-related technologies and innovations, leading to increased efficiency, sustainability, and the advancement of renewable energy solutions. © The Author(s), under exclusive licence

关键词： Chemical reaction CPC derivative Free convection Magnetic field Maxwell fluid

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Synthesis of high performance electrocatalyst material for OER by hydrothermal method based on CoSnO3/rGO composite

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Journal of Sol-Gel science and Technology 2025年第3期114卷 1082-1094页

作者： Khan, Areesha Gouadria, Soumaya Chandra, Subhash Makasana, Jayanti Ballal, Suhas Krithiga, T. Pathak, Piyus Kumar Chaudhary, Rahul Raj Mishra, V.L. Kumar, Abhinav Department of Chemistry Government Graduate College Taunsa Sharif Taunsa32100 Pakistan Department of Physics College of Science Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Electrical Engineering Department GLA University Mathura281406 India Marwadi University Research Center Department of Chemistry Faculty of Science Marwadi University Gujarat Rajkot360003 India Karnatka Bangalore India Department of Chemistry Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Department of Applied Sciences-Chemistry NIMS Institute of Engineering & Technology NIMS University Rajasthan Jaipur India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Mechanical Engineering Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Mohali140307 India Department of Nuclear and Renewable Energy Ural Federal University Named after the First President of Russia Boris Yeltsin Ekaterinburg620002 Russia Department of Mechanical Engineering and Renewable Energy Technical Engineering College The Islamic University Najaf Iraq

The development of advanced electrocatalysts for oxygen evolution reaction (OER) is essential for improving effectiveness of electrocatalytic water splitting (EWS). Perovskite-type oxides acquired attention for their outstanding electrocatalytic capabilities in OER performance. This research involved the preparation of reduced graphene oxide (rGO) based perovskite CoSnO3 material via basic hydrothermal technique to improve OER efficiency. The produced composite was tested by multiple analytical methods to evaluate its structural, surface area and compositional properties. CoSnO3/rGO catalyst demonstrated a remarkable overpotential (η) of 209 mV at 10 mA cm−2, along with Tafel slope (36 mV dec−1), showcasing enhanced OER performance. Electrochemical surface area (ECSA) of CoSnO3/rGO catalyst was obtained to be 642.5 cm2, with enhanced cyclic durability of 35 h and least charge transfer resistance (Rct) of 0.88 Ω. The outcomes indicated that incorporating rGO resulted in an increased surface area (SA), which enhanced conductivity and significantly improved the OER activity of the catalysts. The noteworthy electrochemical characteristics of CoSnO3/rGO composite render it a superior material for applications in electrical and various other domains in the future. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Carbon carbon composites

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Effects of Multi-dimensional Defects on Optical and Thermoelectric Properties of Cerium-Doped ZnO Nanoparticles

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Brazilian Journal of Physics 2025年第4期55卷 1-11页

作者： Arif, Danish Abid, Adeel Younas Ishtiaq, Tabinda Safeen, Kashif Mersal, Gaber A. M. Shah, Sufaid Ali, Adnan Shah, Atta Ullah Safeen, Akif Department of Physics University of Poonch Rawalakot Rawalakot Pakistan Pakistan Institute of Engineering and Applied Sciences National Institute of Lasers and Optronics College Nilore Pakistan Department of Physics University of Sargodha Sargodha Pakistan Department of Physics Women University of Azad Jammu and Kashmir Bagh Bagh Pakistan Department of Physics Abdul Wali Khan University Mardan Mardan Pakistan Department of Chemistry College of Science Taif University Taif Saudi Arabia College of Electronics and Information Engineering Shenzhen University Shenzhen China Department of Physics Government College University Faisalabad Pakistan

The thermoelectric properties of materials are often limited by various factors, and enhancing these properties through defect engineering is an effective strategy. In this study, pure and cerium (Ce)–doped ZnO nanostructures were synthesized by a facile hydrothermal method with varying Ce concentrations. The thermoelectric enhancement in the context of point and bulk defects was experimentally demonstrated by establishing a correlation with structural and optical properties. X-ray diffraction analysis confirmed a hexagonal, highly crystalline structure. Scanning electron microscopy revealed that the particles took on a nanorod shape, elongating with increased doping. Photoluminescence spectra showed near-band-edge and green emissions for all samples, with the optical band gap decreasing as Ce doping increased. The absolute value of electrical conductivity and Seebeck coefficient depicted an increasing trend with the rise in Ce doping concentration. Our outcomes reveal that the addition of 1.2% of Ce into ZnO leads to improvements in the Seebeck coefficient to a maximum value of ~ 98 μV/K at 400 K, along with Figure-of-merit (ZT) improvement, which directly correlates with thermoelectric efficiency and oxygen vacancies along with secondary phase are thought to be the main reasons for that augmentation as supported by XRD and photoluminescence studies. Our study possibly possesses twofold advancements, first providing an opportunity to explore other rare earth–doped ZnO systems specifically for improved thermoelectric efficiency, second, it could be viable for better design of future thermoelectric materials via inspecting the role of defects.

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Federated Knowledge Distillation With 3D Transformer Adaptation for Weakly Labeled Multi-Organ Medical Image Segmentation

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IEEE Access 2025年 13卷 83619-83642页

作者： Tareq Mahmod AlZubi Hamza Mukhtar Department of Computer Science Prince Abdullah bin Ghazi Faculty of Information and Communication Technology Al-Balqa Applied University As-Salt Jordan Department of Computer Science University of Engineering and Technology Lahore (UET Lahore) Lahore Pakistan Intelligent Criminology Laboratory National Center of Artificial Intelligence Al-Khawarizmi Institute of Computer Science UET Lahore Lahore Pakistan

The increasing reliance on medical image segmentation for disease diagnosis, treatment planning, and therapeutic assessment has highlighted the need for robust and generalized deep learning (DL)-based segmentation frameworks. However, existing models often suffer from task-specific limitations, catastrophic forgetting, and poor scalability due to their dependency on narrowly annotated datasets. This creates a significant gap in developing unified, multi-organ segmentation systems that leverage distributed and partially labeled datasets across diverse clinical institutions. To address these challenges, we propose the Federated 3D Knowledge Distillation Network (Fed3D-KDNet), a hybrid federated learning (FL) framework that integrates both global and local knowledge distillation mechanisms. Our model adapts the Segment Anything Model (SAM) for volumetric medical imaging by introducing architectural enhancements, including 3D spatial feature adapters and an Auto Prompt Generator (APG), to optimize spatial representation and reduce reliance on manually crafted prompts. Fed3D-KDNet employs a dual knowledge distillation strategy to mitigate catastrophic forgetting and improve cross-client knowledge transfer, ensuring robust generalization across heterogeneous datasets. The proposed methodology was evaluated on multi-organ CT datasets, including the BTCV benchmark, under centralized and federated settings. Experimental results demonstrate that Fed3D-KDNet achieves state-of-the-art performance with an average Dice score of 80.53% and an average Hausdorff Distance (HD) of 11.43 voxels in federated experiments involving seven clients, showing 5.04% improvement in Dice accuracy and a 4.35 voxel reduction in HD. Moreover, our model demonstrates superior efficiency with a computational cost of 371.3 GFLOPs, 26.53 million tuned parameters, and an inference time of 0.058 seconds per iteration. These results validate the efficacy, scalability, and computational efficiency of Fed3D-K

关键词： Image segmentation Biomedical imaging Computational modeling Three-dimensional displays Training Computed tomography Adaptation models Federated learning Scalability Transformers

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