Nanofluids for Advanced Applications: A Comprehensive Review on Preparation Methods, Properties, and Environmental Impact

ACS Omega, Journal Year: 2025, Volume and Issue: 10(6), P. 5251 - 5282

Published: Feb. 3, 2025

Nanofluids, an advanced class of heat transfer fluids, have gained significant attention due to their superior thermophysical properties, making them highly effective for various engineering applications. This review explores the impact nanoparticle integration on thermal conductivity, viscosity, and overall performance base highlighting improvements in systems, such as exchangers, electronics cooling, PV/T CSP technologies, geothermal recovery. Key mechanisms nanolayer formation, Brownian motion, aggregation are discussed, with a focus hybrid nanofluids that show enhanced conductivity. The increase viscosity poses trade-off, necessitating careful control properties optimize while reducing energy consumption. Empirical data up 123% convective coefficients, demonstrating tangible benefits efficiency system miniaturization. also considers environmental impacts nanofluid use, potential toxicity challenges sustainable production disposal. Future research directions include developing specific integrating phase change materials, exploring new nanomaterials metal chalcogenides enhance sustainability management systems.

Language: Английский

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Development of high-efficiency Ti3C2-MXene/SiO2 composite nanofluids for solar thermal conversion: Synergistic effect of forward scattering and volumetric absorption

Applied Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 126159 - 126159

Published: March 1, 2025

Language: Английский

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A review of applications of green nanofluids for performance improvement of solar collectors

Renewable Energy, Journal Year: 2024, Volume and Issue: unknown, P. 122182 - 122182

Published: Dec. 1, 2024

Language: Английский

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Multiple exact solutions in tri-hybrid nanofluid flow: a study of elastic surface effects

International Journal of Numerical Methods for Heat &amp Fluid Flow, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 21, 2024

Purpose The purpose of this study is to investigate the simultaneous effects normal wall transpiration, stretching strength parameter, velocity slip and nanoparticles on flow a ternary hybrid nanofluid through an elastic surface. goal understand behavior field, temperature distribution, skin friction gradient under these conditions, explore existence nature solutions varying parameter values. Design/methodology/approach analysis involves expressing power-law in closed-form formulas. examines both shrinking surfaces, distinguishing between unique dual solutions. methodology includes deriving exact for exponential algebraic rate formulas analytically by system governing equations into ordinary differential equations. Findings reveals that sheet, solution unique, whereas are observed Special provided various parametric values, showing rate, with focus identifying turning points demarcate non-existence single or multiple represented graphs tables facilitate comprehensive qualitative analysis. research identifies determine presence absence solutions, uncovering different sets. These findings displayed graphically tabular form, highlighting complex interplay parameters resulting behavior. Originality/value This contributes field providing new insights phenomena flows, particularly combined strength, nanoparticle presence. identification profiles significant value, offering deeper understanding factors influencing thermal characteristics such systems. study’s have potential applications optimizing fluid engineering systems where conditions prevalent.

Language: Английский

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Bayesian regularization-based intelligent computing for peristaltic propulsion of curvature-dependent channel walls

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(2)

Published: Feb. 1, 2025

This study investigates the numerical analysis of curvature-dependent symmetric channel walls filled with porous media, focusing on various flow characteristics using Artificial Neural Networks optimized Levenberg–Marquardt Backpropagation Scheme (ANNs-BLMS). The explores Electrically Conducting Peristaltic Propulsion Carreau–Yasuda Ternary Hybrid Nanofluids (ECPPCY-THNFs) propagating through sinusoidal wave trains within a curved conduit. To streamline analysis, governing equations have been simplified under specific assumptions lubrication theory. are solved Adam and three-stage Lobatto IIIa formula techniques to generate dataset spanning walls, covering four cases nine scenarios ECPPCY-THNFs. encompasses ECPPCY-THNFs, step size 0.02. As result, domain is divided into 131 grid points for velocity temperature profiles 71 rates heat transfer analysis. three parts: 10% training, testing, 80% validation. apply proposed methodology, constructed by varying Hartmann number, rate, Darcy curvature parameter, radiation parameter. Subsequently, an artificial intelligence-based algorithm employed derive solution expressions fields analyze dataset. results presented detailed tabular graphical illustrations. Heat performed model, findings validated multiple techniques, including error histograms, regression plots, mean square (MSE), time series autocorrelation, state transition. A comparative between two methods Intelligence (AI)-generated predictions also undertaken. obtained AI-based ANN-BLMS framework confirm reliability accuracy methodology in effectively solving demonstrate that parameter has considerable effect mechanical thermal aspects flow, therefore, it must be incorporated modeling flows channels. Additionally, rate 7.5 critical value, representing minimum required sustain fluid channel. When below this increase decrease profile. However, when exceeds profile shows opposite trend. Furthermore, ternary hybrid nanofluids show concave-up shapes (Θ) values greater than concave-down less 7.5. highest lowest velocities occur near center Θ>7.5 Θ<7.5, respectively. Moreover, coefficient determination values, used as performance indicators, found unity (1.000) ANN model. MSE histogram 2.8467 × 10−11 −3.05 10−7,

Language: Английский

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Solar Energy Storage Optimization Using Fractional Derivative Simulations of Maxwell Hybrid Nanofluid Flow: Entropy Generation Analysis

Energy Science & Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

ABSTRACT This attempt examines the heat transfer enhancement from unsteady bioconvective Maxwell nanofluid flow under incidence of solar radiation influenced by viscous dissipation and chemical reaction through a porous medium. The contains silver titanium alloy hybrid nanoparticles with gyrotactic micro‐organisms in ethylene glycol water‐based fluid. fundamental governing equations are formulated simulated novel fractional derivative approach. time‐fractional derivatives approximated Atangana–Baleanu Caputo solution approach discretized using Crank–Nicolson type finite differences scheme. Graphical results present outcomes diverse physical parameters for concentration, temperature, velocity profile. primary revealed that bioconvection diffusion declines as escalate, this definition gives an excellent approximation time derivative. temperature profile enhanced increased parameter, whereas concentration decreases parameter. resulting provides well‐balanced blend thermal efficiency, uniformity, operational flexibility would be impossible to achieve single base fluid complementary properties water. characteristic contributes improved efficiency collectors. Optimizing absorption collectors is essential improving performance reduce energy losses.

Language: Английский

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Applications of Radiated Tri Hybrid Nanoparticles (TiO2-CuO-SiO2) on Thermal Performance of Engine Oil (SAE10W-30): Case Study for HNF and MNF

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 106144 - 106144

Published: April 1, 2025

Language: Английский

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A numerical and statistical analysis of the unsteady ternary hybrid nanofluid flow and heat transfer over a generalized stretching/shrinking wall

ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, Journal Year: 2025, Volume and Issue: 105(2)

Published: Feb. 1, 2025

Abstract This study analyzes unsteady ternary hybrid nanofluid flow and heat transfer over a generalized stretching/shrinking wall using both analytical numerical methods. By applying similarity transformations, the governing nonlinear partial differential equations are reduced to system of ordinary equations, which numerically solved MATLAB bvp4c function. We find that exhibits two solution branches—an upper lower—within certain parameter ranges. A detailed stability analysis is conducted determine these solutions. Additionally, presents solutions for specific cases, relevant exchangers in low‐velocity environments. Next, MINITAB software used statistically model interactions parameters assess their impact on performance (measured through local Nusselt number), identifying low, medium, or strong effects regression analysis. Finally, sensitivity performed function obtained MINITAB, focusing key input parameters. To best our knowledge, this novel, as no previous work has explored problem, making results original.

Language: Английский

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Characterization and machine learning analysis of hybrid alumina-copper oxide nanoparticles in therminol 55 for medium temperature heat transfer fluid

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 11, 2025

Abstract Efficient heat dissipation is crucial for various industrial and technological applications, ensuring system reliability performance. Advanced thermal management systems rely on materials with superior conductivity stability effective transfer. This study investigates the conductivity, viscosity, of hybrid Al 2 O 3 -CuO nanoparticles dispersed in Therminol 55, a medium-temperature transfer fluid. The nanofluid formulations were prepared CuO-Al mass ratios 10:90, 20:80, 30:70 tested at nanoparticle concentrations ranging from 0.1 wt% to 1.0 wt%. Experimental results indicate that nanofluids exhibit enhanced maximum improvement 32.82% concentration, compared base However, viscosity increases loading, requiring careful optimization practical applications. To further analyze predict Type-2 Fuzzy Neural Network (T2FNN) was employed, demonstrating correlation coefficient 96.892%, high predictive accuracy. integration machine learning enables efficient modeling complex behavior, reducing experimental costs facilitating optimization. These findings provide insights into potential application solar systems, exchangers, cooling

Language: Английский

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Thermally Darcy-Forchheimer flow of tri-hybrid nanomaterials with temperature-dependent fluid characteristics

Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(2), P. 101404 - 101404

Published: March 17, 2025

Language: Английский

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