Search Results (156)

Exploring the dynamics of nonlinear nanofluidic flow-induced vibrations, this work focuses on single-walled branched carbon nanotubes (SWCNTs) operating in a thermal–magnetic environment. Carbon nanotubes (CNTs), renowned for their exceptional strength, conductivity, and flexibility, are modeled using Euler–Bernoulli beam theory alongside Eringen’s nonlocal elasticity to capture nanoscale effects for varying downstream angles. The intricate interactions between nanofluids and SWCNTs are analyzed using the Differential Transform Method (DTM) and validated through ANSYS simulations, where modal analysis reveals the vibrational characteristics of various geometries. To enhance predictive accuracy and system stability, machine learning algorithms, including XGBoost, CATBoost, Random Forest, and Artificial Neural Networks, are employed, offering a robust comparison for optimizing vibrational and thermo-magnetic performance. Key parameters such as nanotube geometry, magnetic flux density, and fluid flow dynamics are identified as critical to minimizing vibrational noise and improving structural stability. These insights advance applications in energy harvesting, biomedical devices like artificial muscles and nanosensors, and nanoscale fluid control systems. Overall, the study demonstrates the significant advantages of integrating machine learning with physics-based simulations for next-generation nanotechnology solutions. Full article

Heat pipes are highly efficient heat transfer devices relying on phase-change mechanisms, with performance heavily influenced by working fluids and operational dynamics. This review article comprehensively examines hydrodynamics and heat transfer in heat pipes, contrasting conventional working fluids with nanofluid-enhanced systems. In the present work we discuss mathematical models governing fluid flow and heat transfer, emphasizing continuum and porous media approaches for wick structures. Functional dependencies of thermophysical properties (e.g., viscosity, surface tension, thermal conductivity) are reviewed, highlighting temperature-driven correlations and nanofluid modifications. Transport mechanisms within wicks are analyzed, addressing capillary-driven flow, permeability, and challenges posed by nanoparticle integration. Fourth, interfacial phase-change conditions—evaporation and condensation—are modeled, focusing on kinetic theory and empirical correlations. Also, numerical and experimental results are synthesized to quantify performance enhancements from nanofluids, including thermal resistance reduction and capillary limit extension, while addressing inconsistencies in stability and pressure drop trade-offs. Finally, applications spanning electronics cooling, aero-space, and renewable energy systems are evaluated, underscoring nanofluids’ potential to expand heat pipe usability in extreme environments. The review identifies critical gaps, such as long-term nanoparticle stability and scalability of lab-scale models, while advocating for unified frameworks to optimize nanofluid selection and wick design. This work serves as a foundational reference for researchers and engineers aiming to advance heat pipe technology through nanofluid integration, balancing theoretical rigor with practical feasibility. Full article

Solar photovoltaic/thermal (PV/T) systems can simultaneously solve PV overheating and obtain high-quality thermal energy through nanofluid spectral splitting technology. However, the existing nanofluid splitting devices have insufficient short-wavelength extinction and stability defects. To achieve the precise matching of the nanofluid splitting performance with the optimal spectral window of the PV/T system, this paper carries out a relevant study on the optical properties of Al nanoparticles and proposes an Al@Ag nanoparticle. The optical behaviors of nanoparticles and nanofluids are numerically analyzed using the finite-difference time-domain (FDTD) method and the Beer–Lambert law. The results demonstrate that adjusting particle size enables modulation of nanoparticle extinction performance, including extinction intensity and resonance peak range. The Al@Ag core–shell structure effectively mitigates the oxidation susceptibility of pure Al nanoparticles. Furthermore, coating Al nanoparticles with an Ag shell significantly enhances their extinction efficiency in the short-wavelength range (350–640 nm). After dispersing Al nanoparticles into water to form a nanofluid, the transmittance in the short-wavelength range is significantly reduced compared to pure water. Compared to 50 nm pure Al particles, the Al@Ag nanofluid further reduces the transmittance by up to 13% in the wavelength range of 350–650 nm, while having almost no impact on the transmittance in the photovoltaic window (640–1080 nm). Full article

In the current paper, an analysis of magnetohydrodynamic Williamson nanofluid boundary layer flow is presented, with multiple slips in a porous medium, using a newly designed human-brain-inspired Ricker wavelet neural network solver. The solver employs a hybrid approach that combines genetic algorithms, serving as a global search method, with sequential quadratic programming, which functions as a local optimization technique. The heat and mass transportation effects are examined through a stretchable surface with radiation, thermal, and velocity slip effects. The primary flow equations, originally expressed as partial differential equations (PDEs), are changed into a dimensionless nonlinear system of ordinary differential equations (ODEs) via similarity transformations. These ODEs are then numerically solved with the proposed computational approach. The current study has significant applications in a variety of practical engineering and industrial scenarios, including thermal energy systems, biomedical cooling devices, and enhanced oil recovery techniques, where the control and optimization of heat and mass transport in complex fluid environments are essential. The numerical outcomes gathered through the designed scheme are compared with reference results acquired through Adam’s numerical method in terms of graphs and tables of absolute errors. The rapid convergence, effectiveness, and stability of the suggested solver are analyzed using various statistical and performance operators. Full article

The miniaturization and high integration of modern electronic devices have intensified thermal management challenges. Therefore, developing efficient heat sinks has become crucial to ensuring the stability and performance of high-performance CPUs. Previous studies have not considered the thermally demanding Intel i9 CPU; the current study targets this processor and explores the advantages of more complex minichannel path designs. In addition, this work investigates the enhanced heat transfer performance by integrating metal foams into microchannels. Using a computational approach, this study evaluates the thermal performance of uni-path, dual-path, and staggered-path (SP) minichannel heat sinks with water, Al₂O₃, and CuO nanofluids at varying Reynolds numbers. The impact of aluminum foam filling has also been examined. Results confirm that higher Reynolds numbers enhance fluid flow, reduce heat sink temperature, and improve temperature uniformity. Among the configurations, the SP heat sink combined with Al₂O₃ nanofluid achieves the best trade-off between cooling efficiency and energy consumption. While lower porosity foam and higher nanofluid volume fractions enhance heat transfer, they also increase flow resistance, leading to higher energy consumption. Due to its high specific heat capacity, Al₂O₃ nanofluid outperforms CuO, with optimal cooling observed at a 3–4% volume fraction. The performance evaluation criterion (PEC) captures the trade-off between heat dissipation and energy efficiency. It shows that the SP model with high-porosity aluminum foam and Al₂O₃ nanofluid turns out to be the most effective design. This combination maximizes cooling efficiency while minimizing excessive energy costs, demonstrating superior thermal management for high-performance microelectronic devices. Full article

Fluid flow in microporous and nanoporous media exhibits unique behaviors that deviate from classical continuum predictions due to dominant surface forces at small scales. Understanding these microscale flow mechanisms is critical for optimizing unconventional reservoir recovery and other energy applications. This review provides a comparative analysis of the existing literature, highlighting key advances in experimental techniques, theoretical models, and numerical simulations. We discuss how innovative micro/nanofluidic devices and high-resolution imaging methods now enable direct observation of confined flow phenomena, such as slip flow, phase transitions, and non-Darcy behavior. Recent theoretical models have clarified scale-dependent flow regimes by distinguishing microscale effects from macroscopic Darcy flow. Likewise, advanced numerical simulations—including molecular dynamics (MD), lattice Boltzmann methods (LBM), and hybrid multiscale frameworks—capture complex fluid–solid interactions and multiphase dynamics under realistic pressure and wettability conditions. Moreover, the integration of artificial intelligence (e.g., data-driven modeling and physics-informed neural networks) is accelerating data interpretation and multiscale modeling, offering improved predictive capabilities. Through this critical review, key phenomena, such as adsorption layers, fluid–solid interactions, and pore surface heterogeneity, are examined across studies, and persistent challenges are identified. Despite notable progress, challenges remain in replicating true reservoir conditions, bridging microscale and continuum models, and fully characterizing multiphase interface dynamics. By consolidating recent progress and perspectives, this review not only summarizes the state-of-the-art but underscores remaining knowledge gaps and future directions in micro/nanopore flow research. Full article

Microelectronic technologies are progressing rapidly. As devices shrink in size, they produce a substantial heat flux that can adversely affect performance and shorten their lifespan. Conventional cooling methods, such as forced-air heat transfer and essential heat sinks, are inadequate for managing the elevated heat flux generated by these devices. Consequently, microchannel heat sinks have been developed to address this challenge. The present research is intended to study forced flow convection and heat transfer in a cone–column combined microchannel heat sink (MCHS). This study examines a regularly shaped MCHS to evaluate its heat transfer rate. The heat transfer medium employed is a graphene–water nanofluid, and the heat sink’s base is assumed to maintain a constant heat flux. The Galerkin weighted finite element method solves the nanofluid’s governing partial differential equations. This thesis investigates the impact of varying intake velocities on the Reynolds number (100 ≤ Re ≤ 900), externally applied heat flux (10⁴ ≤ q ≤ 10⁶), and the volumetric ratio of nanoparticles (0.001 ≤ φ ≤ 0.04). The study conducts a mathematical analysis to explore how these parameters affect pressure drop, friction factor, average Nusselt number, average substrate temperature, and heat transfer enhancement. The findings are compared with those of a conventional MCHS as the Re increases. The results are analyzed and visually represented through isothermal lines for temperature contours and streamlines for velocity. An increase in the inlet velocity of the water–graphene nanofluid significantly enhances heat transfer and thermal efficiency, achieving improvements of approximately 27.00% and 21.21%, respectively. The research demonstrates that utilizing water–G as a smart coolant with the cone–column combined MCHS enhances thermal efficiency by 4.05% compared to standard water. A comparison of the hydraulic performance index at the substrate reveals that the cone–column combined MCHS is significantly more effective at dissipating heat than the traditional MCHS. Full article

Spray cooling, of which the essence is droplet impacting, is an efficient thermal management technique for dense electronic components in unmanned aerial vehicles (UAVs). Nanofluids are pointed as promising cooling dispersions. Since the nanofluids are unstable, a dispersant could be added to the fluid. However, the added dispersant may influence the droplet, thereby impacting behaviors. In this work, the effects of dispersant on the nanofluid droplet-impacting dynamics are studied experimentally. The base fluid is deionized water (DI water), and Al₂O₃ is the selected nanoparticle. Sodium dodecyl sulfate (SDS) is used as the dispersant. Five different concentrations of nanofluids are configured using a two-step method. Droplet impacting behaviors are observed by high-speed imaging techniques. The other effects, i.e., the nanofluid particle volume fraction and the Weber number on droplet impact dynamics, are also systematically investigated. The results illustrate that the surface tension of the Al₂O₃ nanofluid increases with increased nanofluid concentrations. The surface tension of Al₂O₃ nanofluid with SDS is lower than that of DI water. And the increase in droplet impact velocity increases the spreading morphology. Nanofluid droplets exhibit spreading and equilibrium process when SDS is added. Furthermore, as the concentration of the nanofluid increases, the spreading process is inhibited. Whereas without SDS, the droplets undergo spreading, receding, and equilibrium processes. Moreover, there is no appreciable change in the impacting process with concentration increase. The empirical models of maximum spreading factor should be established without SDS and with SDS, respectively. This study can provide theoretical basis and specific guidance for experimental characterization of UAVs’ electronic devices based on the mechanism of nanofluid droplet impact on the wall. Full article

With the increasing demand for thermal management in electronic devices and industrial systems, nanofluids have emerged as a research hotspot due to their superior thermal conductivity and heat transfer efficiency. Among them, CuO-H₂O demonstrates excellent heat transfer performance due to its high thermal conductivity, Fe₃O₄-H₂O offers potential for further optimization by combining thermal and magnetic properties, and Al₂O₃-H₂O exhibits strong chemical stability, making it suitable for a wide range of applications. These three nanofluids are representative in terms of particle dispersibility, thermal conductivity, and physical properties, providing a comprehensive perspective on the impact of nanofluids on microchannel heat exchangers. This study investigates the heat transfer performance and flow characteristics of various types and volume fractions of nanofluids in microchannel heat exchangers. The results reveal that with increasing flow rates, the convective heat transfer coefficient and Nusselt number of nanofluids exhibit an approximately linear growth trend, primarily attributed to the turbulence enhancement effect caused by higher flow rates. Among the tested nanofluids, CuO-H₂O demonstrates the best performance, achieving a 4.89% improvement in the heat transfer coefficient and a 1.64% increase in the Nusselt number compared to pure water. Moreover, CuO-H₂O nanofluid significantly reduces wall temperatures, showcasing its superior thermal management capabilities. In comparison, the performance of Al₂O₃-H₂O and Fe₃O₄-H₂O nanofluids is slightly inferior. In terms of flow characteristics, the pressure drop and friction factor of nanofluids exhibit nonlinear variations with increasing flow rates. High-concentration CuO-H₂O nanofluid shows a substantial pressure drop, with an increase of 7.33% compared to pure water, but its friction factor remains relatively low and stabilizes at higher flow rates. Additionally, increasing the nanoparticle volume fraction enhances the convective heat transfer performance; however, excessively high concentrations may suppress heat transfer efficiency due to increased viscosity, leading to a decrease in the Nusselt number. Overall, CuO-H₂O nanofluid exhibits excellent thermal conductivity and flow optimization potential, making it a promising candidate for efficient thermal management in MCHEs. However, its application at high concentrations may face challenges related to increased flow resistance. These findings provide valuable theoretical support and optimization directions for the development of advanced thermal management technologies. Full article

Two-dimensional (2D) nanofluidic channels are emerging as potential candidates for harnessing osmotic energy from salinity gradients. However, conventional 2D nanofluidic membranes suffer from high transport resistance and low ion selectivity, leading to inefficient transport dynamics and limiting energy conversion performance. In this study, we present a novel composite membrane consisting of porous MXene (PMXene) nanosheets featuring etched nanopores, in conjunction with cellulose nanofibers (CNF), yielding enhancement in ion flux and ion selectivity. A mild H₂O₂ oxidant is employed to etch and perforate the MXene sheets to create a robust network of cation transportation nanochannels that effectively reduces the energy barrier for cation transport. Additionally, CNF with a unique nanosize and high charge density further enhances the charge density and mechanical stability of the nanofluidic system. Under neutral pH and room temperature, the PMXene/CNF membrane demonstrates a maximum output power density of 0.95 W·m⁻² at a 50-fold KCl gradient. Notably, this represents a 43% improvement over the performance of the pristine MXene/CNF membrane. Moreover, 36 nanofluidic devices connected in series are demonstrated to achieve a stable voltage output of 5.27 V and power a calculator successfully. This work holds great promise for achieving sustainable energy harvesting with efficient osmotic energy conversion utilization. Full article

Measurements of transmission as well as thermophysical properties have been carried out for different concentrations of SiO₂ nanoparticles (0, 1, 2, 5, 10, and 20 wt.%) in pure water (W) and ethylene glycol–water mixture (EG/W) in a weight ratio of 25/75, from 298 to 323 K at 100 kPa. In particular, the density, specific heat capacity, and thermal diffusivity are measured by a density meter, differential scanning calorimetry, and the laser flash method. In the case of 20 wt.% SiO₂, transmission in the visible range is reduced by 9.3%. Simultaneously, the density rises linearly to 12.3% (in W) and 11.3% (in EG/W). The specific heat capacity decreases to 15.9% (in W) and 17.3% (in EG/W), while the thermal diffusivity rises to 16.4% (in W) and 20.4% (in EG/W). While the density measurements are in very good agreement with the literature, the measured values of the specific heat capacity deviate more than 5%, especially for concentrations below 5 wt.% SiO₂. Moreover, it is shown that the thermal conductivity increases less for fluids in small gaps compared to other authors, which could be due to the suppression of the Brownian motion. Based on the measurement results, temperature- and concentration-dependent correlations for the investigated thermophysical properties are developed using two adjustable parameters. In general, these correlations show deviations of less than 4% from the experimental results, which will help to fill the gaps in the variation of experimental results due to size, SiO₂ nanofluid production, and different measurement devices, and thus optimize solar thermal applications with SiO₂ nanofluid. Full article

An efficient cooling system is necessary for the reliability and safety of modern microchips for a longer life. As microchips become smaller and more powerful, the heat flux generated by these chips per unit area also rises sharply. Traditional cooling techniques are inadequate to meet the recent cooling requirements of microchips. To meet the current cooling demand of microelectromechanical systems (MEMS) devices and microchips, microchannel heat sink (MCHS) technology is the latest invention, one that can dissipate a significant amount of heat because of its high surface area to volume ratio. This study provides a concise summary of the design, material selection, and performance parameters of the MCHSs that have been developed over the last few decades. The limitations and challenges associated with the different techniques employed by researchers over time to enhance the thermal efficiency of microchannel heat sinks are discussed. The effects on the thermal enhancement factor, Nusselt number, and pressure drop at different Reynold numbers in passive techniques (flow obstruction) i.e., ribs, grooves, dimples, and cavities change in the curvature of MCHSs, are discussed. This study also discusses the increase in heat transfer using nanofluids and how a change in coolant type also significantly affects the thermal performance of MCHSs by obstructing flow. This study provides trends and useful guidelines for researchers to design more effective MCHSs to keep up with the cooling demands of power electronics. Full article

Polydimethylsiloxane (PDMS) has become a popular material in microfluidic and macroscale in vitro models due to its elastomeric properties and versatility. PDMS-based biomodels are widely used in blood flow studies, offering a platform for improving flow models and validating numerical simulations. This review highlights recent advances in bioflow studies conducted using both PDMS microfluidic devices and macroscale biomodels, particularly in replicating physiological environments. PDMS microchannels are used in studies of blood cell deformation under confined conditions, demonstrating the potential to distinguish between healthy and diseased cells. PDMS also plays a critical role in fabricating arterial models from real medical images, including pathological conditions such as aneurysms. Cutting-edge applications, such as nanofluid hemodynamic studies and nanoparticle drug delivery in organ-on-a-chip platforms, represent the latest developments in PDMS research. In addition to these applications, this review critically discusses PDMS properties, fabrication methods, and its expanding role in micro- and nanoscale flow studies. Full article

In recent years, the field of micro- and nanochannel fabrication has seen significant advancements driven by the need for precision in biomedical, environmental, and industrial applications. This review provides a comprehensive analysis of emerging fabrication technologies, including photolithography, soft lithography, 3D printing, electron-beam lithography (EBL), wet/dry etching, injection molding, focused ion beam (FIB) milling, laser micromachining, and micro-milling. Each of these methods offers unique advantages in terms of scalability, precision, and cost-effectiveness, enabling the creation of highly customized micro- and nanochannel structures. Challenges related to scalability, resolution, and the high cost of traditional techniques are addressed through innovations such as deep reactive ion etching (DRIE) and multipass micro-milling. This paper also explores the application potential of these technologies in areas such as lab-on-a-chip devices, biomedical diagnostics, and energy-efficient cooling systems. With continued research and technological refinement, these methods are poised to significantly impact the future of microfluidic and nanofluidic systems. Full article

The combination of micro- or nanofluidics and strong light–matter coupling has gained much interest in the past decade, which has led to the development of advanced systems and devices with numerous potential applications in different fields, such as chemistry, biosensing, and material science. Strong light–matter coupling is achieved by placing a dipole (e.g., an atom or a molecule) into a confined electromagnetic field, with molecular transitions being in resonance with the field and the coupling strength exceeding the average dissipation rate. Despite intense research and encouraging results in this field, some challenges still need to be overcome, related to the fabrication of nano- and microscale optical cavities, stability, scaling up and production, sensitivity, signal-to-noise ratio, and real-time control and monitoring. The goal of this paper is to summarize recent developments in micro- and nanofluidic systems employing strong light–matter coupling. An overview of various methods and techniques used to achieve strong light–matter coupling in micro- or nanofluidic systems is presented, preceded by a brief outline of the fundamentals of strong light–matter coupling and optofluidics operating in the strong coupling regime. The potential applications of these integrated systems in sensing, optofluidics, and quantum technologies are explored. The challenges and prospects in this rapidly developing field are discussed. Full article