The Role of Nanofluids in Renewable Energy Engineering

Bhatti, Muhammad Mubashir; Vafai, Kambiz; Abdelsalam, Sara I.

doi:10.3390/nano13192671

Cited by 59 publications

(8 citation statements)

References 13 publications

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“…Feature selection (FS) is not merely a desirable option but a necessity in data analysis and machine learning. Its significance cannot be overstated, as it underpins the efficacy of predictive models in various fields like Nano fluids [ 9 ], Neural Network Applications [ 10 , 11 ], and Space Exploration [ 12 ]. The elimination of pointless and duplicate features results in an adequate text portrayal and a diminution in data dimensionality, which accelerates the model's learning process and improves the predictive model's effectiveness and accuracy [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

S-shaped grey wolf optimizer-based FOX algorithm for feature selection

Feda,

Adegboye,

Adegboye

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

S-shaped grey wolf optimizer-based FOX algorithm for feature selection

Feda,

Adegboye,

Adegboye

et al. 2024

Heliyon

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“…32,33 The behavior of fluids with various nanoparticles have been extensively studied revealing the importance of nano-fluid viscosity and the porous media dimensions. [34][35][36][37][38] The effect of nano particles on fluid temperature profile over a stretching sheet of porous medium is also studied. 39,40 Fluid flow through a porous media in a threedimensional rectangular duct is studied elucidating the impact of aspect ratio, phase difference, variable channel width, and wave amplitudes on the features of pumping and trapping phenomena.…”

Section: Introductionmentioning

confidence: 99%

Flow control by circular cavities in lateral flow porous membranes

Jamil,

Abbasi,

Jafry

et al. 2024

Science Progress

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This research explores the flow penetration in porous media by virtue of capillary action and geometric control of the liquid imbibition rate in microfluidic paper-based analytical devices (μPADs) having applications in food quality management, medical diagnostics, and environmental monitoring. We examine changes in flow resistance and membrane geometry, aiming to understand factors influencing capillary penetration rates for various practical applications. We conducted experiments and simulations using lateral porous membranes and altered the flow resistance by changing the liquids or the paper channel geometry by adding cavities. From experiments, it was revealed that by creating a circular cavity in the paper channel, the penetration rate was sufficiently altered. Moreover, increasing the cavity size and type of liquid (w.r.t. viscosity) also caused a decrease in the flow rate. Imbibition rates were also influenced by the position of the cavities in the paper channel. The maximum delay for water was almost 2 times with a 16 mm circular cavity located at 3 cm from strip bottom edge. Overall, we attained a maximum delay in the case of castor oil which was almost 85 times slower than water and 3.7 times slower than olive oil. A good agreement was observed with CFD analysis. We believe that this research would help in developing advance techniques to enhance the flow control strategies in μPADs and indicators.

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“…It is well known that a confined fluid's phase behavior differs from that of the bulk [1][2][3][4]. In particular, under nanoscale confinement, the observed phase behavior is influenced by liquid-wall/pore interactions.…”

Section: Introductionmentioning

confidence: 99%

A facile way of controlling capillary condensation: particle-based crystal

Jiao,

McCarthy

2024

Mater. Res. Express

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To demonstrate a facile method to control capillary condensation via the design of confined geometric structures, we use a particle self-assembly technique to fabricate porous materials with well-defined pore sizes. Four groups of silica particles were synthesized using the modified Stober method, and these groups of particles were then arranged in closely packed structures. Quantitative predictions of capillary condensation were made based on the Kelvin equation and an approximation of the geometric structures of our closely packed samples. Experimental observations revealed that water uptake at 100% relative humidity reached 40-50% relative to particle mass across sizes, closely aligning with theoretical predictions for small-particle systems, despite the fact that the geometry of some of the confined spaces corresponds to distances smaller than 10 nm. Despite deviation from theoretical predictions that are observed in larger particle systems, and which can be attributed primarily to practical limitations of attainable ordered structures at these scales, this fabrication method shows great potential for the creation of devices that allow facile control of capillary condensation in relevant applications such as vapor capture and humidity control.

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The Role of Nanofluids in Renewable Energy Engineering

Abstract: The phenomenon of nanofluid flows is intrinsically characterized by several scales and intricate physical processes [...]

Cited by 59 publications

References 13 publications

S-shaped grey wolf optimizer-based FOX algorithm for feature selection

S-shaped grey wolf optimizer-based FOX algorithm for feature selection

Flow control by circular cavities in lateral flow porous membranes

A facile way of controlling capillary condensation: particle-based crystal

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