Explaining the disparity in nanofluid results: Role of morphology, material, and state of aggregation of colloidal particles

Maji, Nitai Chandra; Chakraborty, Jayanta

doi:10.1016/j.ijheatmasstransfer.2020.119709

Cited by 8 publications

(3 citation statements)

References 43 publications

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“…The issue of large variances of measured thermal conductivity between identical nanofluid systems has raised suspicion between reported results [7]. This experiment conducted by Maji and Chakraborty [7] addresses this issue by demonstrating that particle morphology and state-ofaggregation of a colloid vitally effects thermal conductivity. The three morphologies involved in this research included nanowires, nanoplates and nanoparticles.…”

Section: Inlet Temperature Of Water (K) 308mentioning

confidence: 98%

The Effects of Thermophoresis and Brownian Motion on the Flow of a Nanofluid in Rectangular Channels Using Buongiorno’s Model

Ghalayini

2024

Preprint

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Nanofluids is an emerging sector of working fluids that promise to enhance heat transfer by increasing fluids’ thermal conductivity by inputting metal nanoparticles into a base fluid. There are two ways of modelling nanofluids; single-phase and two-phase. Since nanoparticle sedimentation may influence heat extraction, the Buongiorno two-phase model will be of focus to understand Brownian motion as well as thermophoretic effects on nanofluids. This research presents the case of investigating the thermal performance of plain water, as well as Al 2 -3ater and TiO -2ater nanofluids with varying concentrations and flow rates in rectangular channelled configurations. The results revealed that the Nusselt number and thermal efficiency index augmented by increasing the Reynolds number and nanoparticle concentrations. Furthermore, higher Reynolds numbers and nanoparticle concentrations increased homogeneity in nanoparticle distributions. Lastly, 2 and 3-channel configurations were utilized in the study, the 2-channel model yielded symmetrical flow allowing uniform nanoparticle distributions, leading to higher thermal efficiencies.

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Section: Inlet Temperature Of Water (K) 308mentioning

confidence: 98%

The Effects of Thermophoresis and Brownian Motion on the Flow of a Nanofluid in Rectangular Channels Using Buongiorno’s Model

Ghalayini

2024

Preprint

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“…The thermal conductivity enhancement (TCE) ratio can be defined as the change in thermal conductivity compared to the base fluid [40]:…”

Section: Effects Of Surfactant Ratio and Base Fluid Ratiomentioning

confidence: 99%

Experimental Performance Evaluation and Artificial-Neural-Network Modeling of ZnO-CuO/EG-W Hybrid Nanofluids

Zhai¹,

Li²,

Xuan³

et al. 2022

Fluid Dynamics &Amp; Materials Processing

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The thermo-physical properties of nanofluids are highly dependent on the used base fluid. This study explores the influence of the mixing ratio on the thermal conductivity and viscosity of ZnO-CuO/EG (ethylene glycol)-W (water) hybrid nanofluids with mass concentration and temperatures in the ranges 1-5 wt.% and 25-60 C, respectively. The characteristics and stability of these mixtures were estimated by TEM (transmission electron microscopy), visual observation, and absorbance tests. The results show that 120 min of sonication and the addition of PVP (polyvinyl pyrrolidone) surfactant can prevent sedimentation for a period reaching up to 20 days. The increase of EG (ethylene glycol) in the base fluid leads to low thermal conductivity and high viscosity. Thermal conductivity enhancement (TCE) decreases from 21.52% to 11.7% when EG:W is changed from 20:80 to 80:20 at 1 wt.% and 60 C. A lower viscosity of the base fluid influences more significantly the TCE of the nanofluid. An Artificial Neural Network (ANN) has also been used to describe the effectiveness of these hybrid nanofluids as heat transfer fluids. The optimal number of layers and neurons in these models have been found to be 1 and 5 for viscosity, and 1 and 7 for thermal conductivity. The corresponding coefficient of determination (R 2 ) was 0.9979 and 0.9989, respectively.

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“…These include replacing the conventional catalysts with copper nanoparticles as an efficient catalyst for many catalytic applications [1,2]. In addition, copper nanoparticles are also considered as competent thermal fluids in switching the conventional fluids for coolant applications [3][4][5] and reflecting as an alternative material for making RFID antenna in microelectronics applications [6,7], etc.…”

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confidence: 99%

Biocompatible polymer-capped oxidation-resistant copper nanoparticles for nanofluid and hydrogel applications

et al. 2021

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This work aims at the preparation of oxidation-resistant copper (Cu) nanoparticles using biocompatible and naturally available polymers such as polyacrylamide and xanthan gum for their possible application in nanofluid and nanohydrogels. Cu nanoparticles as powder were successfully synthesized using a simple chemical reduction technique followed by centrifugation and drying under inert gas environment. The optical properties and morphology of synthesized Cu nanoparticles were characterized using UV-Vis spectrophotometer and transmission electron microscope. TEM images show that the particles are well isolated and vary between 10 and 25 nm in size for both polyacrylamide-and xanthan gum-stabilized Cu nanoparticles. X-ray diffraction studies were also successfully performed to confirm the phase purity of synthesized Cu nanoparticles in terms of surface oxidation. Moreover, nanofluids and nanohydrogels were prepared from the as-synthesized Cu nanoparticles powder and thermophysical and rheological properties were explored successfully. Both polyacrylamideand xanthan gum-capped Cu nanofluids exhibit high stability in terms of aggregation and oxidation for at least 6 months. Approximately 33% enhancement in thermal conductivity was observed for both the nanofluids and the results were consistent with modified Maxwell model. Rheological behaviour of nanofluids and hydrogel was measured and the results suggest that the nanofluid exhibits shear thinning behaviour whereas the nanohydrogel shows viscoelastic behaviour with a gel time of ~2.5 h.

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Explaining the disparity in nanofluid results: Role of morphology, material, and state of aggregation of colloidal particles

Cited by 8 publications

References 43 publications

The Effects of Thermophoresis and Brownian Motion on the Flow of a Nanofluid in Rectangular Channels Using Buongiorno’s Model

The Effects of Thermophoresis and Brownian Motion on the Flow of a Nanofluid in Rectangular Channels Using Buongiorno’s Model

Experimental Performance Evaluation and Artificial-Neural-Network Modeling of ZnO-CuO/EG-W Hybrid Nanofluids

Biocompatible polymer-capped oxidation-resistant copper nanoparticles for nanofluid and hydrogel applications

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