Thermal conductivity of ethylene glycol and water mixture based Fe3O4 nanofluid

Thermal conductivity of ethylene glycol and water mixture based Fe₃O₄ nanofluid has been investigated experimentally. Magnetic Fe₃O₄ nanoparticles were synthesized by chemical co-precipitation method and the nanofluids were prepared by dispersing nanoparticles into different base fluids like 20:80%, 40:60% and 60:40% by weight of the ethylene glycol and water mixture. Experiments were conducted in the temperature range from 20 °C to 60 °C and in the volume concentration range from 0.2% to 2.0%. Results indicate that the thermal conductivity increases with the increase of particle concentration and temperature. The thermal conductivity is enhanced by 46% at 2.0 vol.% of nanoparticles dispersed in 20:80% ethylene glycol and water mixture compared to other base fluids. The theoretical Hamilton–Crosser model failed to predict the thermal conductivity of the nanofluid with the effect of temperature. A new correlation is developed for the estimation of thermal conductivity of nanofluids based on the experimental data.     

Investigation of thermal conductivity and viscosity of Fe3O4 nanofluid for heat transfer applications

Experimental investigations and theoretical determination of effective thermal conductivity and viscosity of magnetic Fe₃O₄/water nanofluid are reported in this paper. The nanofluid was prepared by synthesizing Fe₃O₄ nanoparticles using the chemical precipitation method, and then dispersed in distilled water using a sonicator. Both experiments were conducted in the volume concentration range 0.0% to 2.0% and the temperature range 20 °C to 60 °C. The thermal conductivity and viscosity of the nanofluid were increased with an increase in the particle volume concentration. Viscosity enhancement was greater compared to thermal conductivity enhancement under at same volume concentration and temperature. Theoretical equations were developed to predict thermal conductivity and viscosity of nanofluids without resorting to the well established Maxwell and Einstein models, respectively. The proposed equations show reasonably good agreement with the experimental results.     

Experimental determination of thermal conductivity and dynamic viscosity of Ag–MgO/water hybrid nanofluid

The main goal of this experimental work is to investigate the effect of nanoparticle volume fraction on thermal conductivity and dynamic viscosity of Ag–MgO/water hybrid nanofluid with the particle diameter of 40(MgO) and 25(Ag) nm and nanoparticle volume fraction (50% Ag and 50% MgO by volume) range between 0% and 2% and presenting new correlations. Several existing theoretical and empirical correlations for thermal conductivity (four correlations) and dynamic viscosity (five correlations) of nanofluids have been examined for their accuracy in predicting the value of thermodynamics properties by comparing the predicted values with experimental data. The examined correlations were found to present inaccuracies (under predictions) in the range of nanoparticle volume fraction under study. Predictions of the new developed correlations by comparing the predicted values with experimental data showed that the new correlations are within a very good accuracy.     

Experimental study of Fe2O3/water and Fe2O3/ethylene glycol nanofluid heat transfer enhancement in a shell and tube heat exchanger

Heat transfer characteristics of Fe₂O₃/water and Fe₂O₃/EG nanofluids were measured in a shell and tube heat exchanger under laminar to turbulent flow condition. In the shell and tube heat exchanger, water and ethylene glycol-based Fe₂O₃ nanofluids with 0.02%, 0.04%, 0.06% and 0.08% volume fractions were used as working fluids for different flow rates of nanofluids. The effects of Reynold's number, volume concentration of suspended nanoparticles and different base fluids on the heat transfer characteristics were investigated. Based on the results, adding nanoparticles to the base fluid causes a significant enhancement of the heat transfer characteristics and thermal conductivity. This enhancement was investigated with regard to various factors; concentration of nanoparticles, types of base fluids, sonication time and temperature of fluids. In this paper, the effect of Fe₂O₃ nanoparticles on the thermal conductivity of base fluids like ethylene glycol and water was studied. The thermal conductivity measurement was made for different concentrations and temperatures. As the concentration of the nanoparticles increased, there was a significant enhancement in thermal conductivity and overall heat transfer due to more interaction between particles. It was also observed that there was an improvement in the thermal conductivity of the base fluid as the temperature increased. The measurements also showed that the pressure drop of nanofluid was higher than that of the base fluid in a turbulent flow regime. However, there was no significant increase in pressure drop at laminar flow.     

Optimization,modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids by NSGA-II using ANN

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.     

Thermal conductivity of Cu/TiO2–water/EG hybrid nanofluid: Experimental data and modeling using artificial neural network and correlation

In the present paper, the thermal conductivity of hybrid nanofluids is experimentally investigated. The studied nanofluid was produced using a two-step method by dispersing Cu and TiO₂ nanoparticles with average diameter of 70 and 40 nm in a binary mixture of water/EG (60:40). The properties of this nanofluid were measured in various solid concentrations (0.1, 0.2, 0.4, 0.8, 1, 1.5, and 2%) and temperatures ranging from 30 to 60 °C. Next, two new correlations for predicting the thermal conductivity of studied hybrid nanofluids, in terms of solid concentration and temperature, are proposed that use an artificial neural network (ANN) and are based on experimental data. The results indicate that these two new models have great ability to predict thermal conductivity and show excellent agreement with the experimental results.     

Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid

This paper focuses on designing an artificial neural network which can predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluids from input experimental data including temperature, diameter of particles, and solid volume fraction. The experimental data were extracted and they were used as learning dataset to train the neural network. To find a proper architecture for network, an iteration method was used. Based on the results, there was no over-fitting in designed neural network and the neural network was able to track the data. ANN outputs showed that the maximum errors in predicting thermal conductivity and dynamic viscosity are 2% and 2.5%, respectively. Based on the ANN outputs, two sets of correlations for estimating the thermal conductivity and dynamic viscosity were presented. The comparisons between experimental data and the proposed correlations showed that the presented correlations were in an excellent agreement with experimental data.     

CFD modeling (comparing single and two-phase approaches) on thermal performance of Al2o3/water nanofluid in mini-channel heat sink

CFD modeling of laminar forced convection on Al₂O₃ nanofluid with size particles equal to 33 nm and particle concentrations of 0.5, 1 and 6 wt.% within 130 < Re < 1600 in mini-channel heat sink is executed by four individual models (single phase, VOF, mixture, Eulerian). Three-dimensional steady-state governing partial differential equations was discretized using finite volume method.Influences of some important parameters such as nanoparticle concentration and Reynolds number on the enhancement of nanofluid heat transfer have been investigated. The difference between the two-phase models results was marginal, and they were more precise by comparison with experimental reference data than single phase model. Besides with regard to the most precise and less CPU usage and run time, mixture model was chosen to obtain a correlation based on dimensionless numbers for the Nusselt number and friction factor estimation.     

Influence of Coulomb forces on Fe3O4–H2O nanofluid thermal improvement

Influence of Coulomb forces on Fe₃O₄–H₂O nanofluid thermal improvement in a cavity with moving wall is examined. The final formulas are solved via Control Volume based Finite Element Method. The influences of volume fraction of Fe₃O₄, supplied voltage and Reynolds number on the hydrothermal characteristics are considered. Results indicate that existence of electric field can alter the nanofluid flow style. As Coulomb force augments temperature gradient along hot wall enhances. Nusselt number enhances with augment of supplied voltage.     

An efficient Fe2O3/FeS heterostructures water oxidation catalyst

Slow kinetics and insufficient understanding of the perceptual design of oxygen evolution reaction (OER) electrocatalysts are major obstacles. Overcoming these challenges, heterostructures have recently attracted attention because they encourage alternative OER electrocatalysts with active structural features. In this study, synthesis, characterization and electrochemical evaluation of the heterostructure of iron oxide/iron sulfide (Fe₂O₃/FeS) and its counterparts, iron oxide (Fe₂O₃) and iron sulfide (FeS) are reported. The structural features of as-synthesized electrocatalysts have been evaluated by infrared spectroscopy, powder X-ray diffraction study and scanning electron microscopy. Fe₂O₃/FeS was found to be a stable electrocatalyst for efficient water splitting, which initiates OER at a surprisingly low potential of 1.49 V (vs RHE) in 1 M potassium hydroxide. The Fe₂O₃/FeS electrocatalyst drives OER with a current density of 40 mA cm^?2 at overpotential of 370 mV and a Tafel slope of 90 mV dec^?1. Its performance is better than its counterparts (Fe₂O₃ and FeS) under similar electrochemical conditions. At an applied potential of 1.65 V (vs RHE), continuous oxygen production for several hours revealed the long-term stability and effective activity of the Fe₂O₃/FeS electrocatalyst for OER. The as-developed Fe₂O₃/FeS heterostructure provides an effective alternative low-cost metal-based electrocatalysts for OER.     

Natural convection in a rectangular enclosure containing an oval-shaped heat source and filled with Fe3O4/water nanofluid

This work concerns with the study of natural convection heat transfer in rectangular cavities with an inside oval-shaped heat source filled with Fe₃O₄/water nanofluid. The finite element method is employed to solve the governing equations for this problem. Average Nusselt numbers are presented for a wide range of Rayleigh number (10³ ≤ Ra ≤ 10⁵), volume fraction of nanoparticles (0 ≤ ϕ ≤ 14%), and four different size and shapes of the heat source. Depending on concentration of the nanoparticle, geometry of the heat source, and the value of Rayleigh number different behaviors are monitored for average Nusselt numbers. Configuration of the heat source dictates a significant change on the behavior of the average Nusselt number, while addition of the nanoparticles has a negative effect on the magnitude of Nusselt number for this problem.     

Cu/Fe3O4 catalyst for water gas shift reaction: Insight into the effect of Fe2+ and Fe3+ distribution in Fe3O4

Two precursors, namely, p-CFO-T (tetragonal) and p-CFO-C (cubic), were fabricated by a sol-gel method via citric acid and poly(vinyl alcohol) complexation, respectively. After H₂-reduction, the two were converted to Cu/Fe₃O₄ catalysts of different complexions, which are named as CFO-CA and CFO-PVA, respectively. The distribution of Fe²⁺ and Fe³⁺ in the Cu/Fe₃O₄ catalysts was studied by Raman and XPS techniques. It was disclosed that the distribution of Fe²⁺ and Fe³⁺ in Fe₃O₄ has an effect on Cu–Fe₃O₄ interaction and catalyst surface basicity. Compared to CFO-PVA, CFO-CA has a larger amount of Fe³⁺, which mostly sits at the octahedral sites, leading to stronger Cu–Fe₃O₄ interaction, and a larger amount of catalyst surface sites that are of weak basicity. As a result, the critical elementary steps of WGS reaction, viz. water dissociation, –COOH decomposition and CO₂ desorption are promoted as reflected in the lower E_a and higher catalytic activity of CFO-CA.     

The effect of alumina/water nanofluid particle size on thermal conductivity

This study examines the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of alumina(Al₂O₃)/water nanofluids. A Al₂O₃/water nanofluid produced by the direct synthesis method served as the experimental sample, and nanoparticles, each of a different nominal diameter (20, 50, and 100 nm), were dispersed into four different concentrations (0.5, 1.0, 1.5, and 2.0 wt%). This experiment measured the thermal conductivity of nanofluids with different particle sizes, weight fractions, and working temperatures (10, 30, 50 °C). The results showed a correlation between high thermal conductivity ratios and enhanced sensitivity, and small nanoparticle size and higher temperature. This research utilized experimental data to construct a new empirical equation, taking the nanoparticle size, temperature, and lower weight fraction of the nanofluid into consideration. Comparing the regression results with the experimental values, the margin of error was within ?3.5% to +2.7%. The proposed empirical equation showed reasonably good agreement with our experimental results.     

Thermal conductivity measurement of methanol-based nanofluids with Al2O3 and SiO2 nanoparticles

In this study, the methanol-based nanofluids with Al₂O₃ and SiO₂ nanoparticles are prepared by dispersing nanoparticles in pure methanol using an ultrasonic equipment. The main objective of this paper is to measure the thermal conductivity of the methanol-based nanofluids. We have also measured the zeta potential, particle size and Tyndall effect for the present nanofluids. The transient hot-wire method is applied for measuring the thermal conductivity of methanol-based nanofluids. The measurement uncertainty in repeatability is obtained as 1.95% for deionized (DI) water and 1.34% for pure methanol, respectively. The effective thermal conductivity of methanol-based nanofluids is measured at a temperature of 293.15 K. The results show that the thermal conductivity increases with an increase of the nanoparticle volume fraction, and the enhancement is observed to be 10.74% and 14.29% over the basefluid at the volume fraction of 0.5vol% for Al₂O₃ and SiO₂ nanoparticles, respectively. Clustering of nanoparticles is considered to be the main reason for the thermal conductivity enhancement.     

The performance evaluation of Al2O3/water nanofluid flow and heat transfer in microchannel heat sink

The numerical modeling of the conjugate heat transfer and fluid flow of Al₂O₃/water nanofluid through the microchannel heat sink is presented in the paper. The laminar flow regime was considered along with viscous dissipation effect. The microchannel heat sink with square microchannels and D_h = 50 μm is considered. The heat flux was fixed to q = 35 W/m² with heating and cooling cases. The water based Al₂O₃ nanofluid was encountered with various volume concentrations of Al₂O₃ particles $?=1''–''9\%$ and three diameters of the particle d_p = 13, 28 and 47 nm. The analysis is performed on the results obtained for the local heat transfer coefficients based on a fixed pumping power. The results reveal a different local heat transfer behavior compared to the analysis made on a basis of the constant Re.     

Investigation of thermal conductivity and viscosity of Al2O3/water–ethylene glycol mixture nanocoolant for cooling channel of hot-press forming die application

Hot-press forming process is widely used to produce lightweight chassis in automotive industries. The hot-press forming process currently uses water as coolant to quench boron steels in a closed die with a cooling channel. However, to enhance performance of hot-press forming die, the fluid with better thermal properties will be used instead of normal water. This study dispersed Al₂O₃ nanoparticles with an average diameter of 13 nm in three volume percentages base ratios of water (W) to ethylene glycol (EG) (i.e. 60:40, 50:50, and 40:60) by two-step preparation. The two main parameters in cooling rate performance are thermal conductivity and viscosity. The nanocoolant of Al₂O₃/water–ethylene glycol mixture is prepared for the volume concentration range of 0.2 to 1.0%. The thermal conductivity and viscosity are then measured at temperature range of 15 to 55 °C. The highest enhancement of thermal conductivity was observed to be 10% higher than base fluid for 1.0% volume concentration at 55 °C in 60:40 (W/EG). However, the highest enhancement of viscosity was measured to be 39% for 1.0% volume concentration in 40:60 (W/EG) at 25 °C. The convective heat transfer coefficient of 1.0% concentration in 60:40 (W:EG) at 25 °C is enhanced by 25.4% better than that of 50:50 and 40:60 (W:EG) base fluid. Therefore, this study recommends the use of Al₂O₃ in 60:40 (W:EG) mixture with volume concentration of less than 1.0% for application in cooling channel of hot-press forming die. Nanocoolant as cooling agent with higher heat transfer coefficient compared to the base fluid can reduce the cycle time and increase the productivity of hot-press forming process.     

Numerical simulation of mixed convection in a porous medium filled with water/Al2 O3 nanofluid

The present work encloses the application of a Brinkman–extended Darcy model in a problem concerning mixed convection ina lid–driven porous cavity using nanofluids. The transport equations are solved numerically by the finite volume method on a co–located grid arrangement using the Quadratic Upstream Interpolation for Convective Kinematics (QUICK) scheme. The effects of governing parameters, namely, Grashof number (Gr), Darcy number (Da), and solid volume fraction $(\chi )$ , on the streamlines and the isotherms are studied. The present results are validated by favorable comparisons with previously published results and are in good agreement with them. The present numerical results show that the addition of nanoparticles to a base fluid has produced an augmentation of the heat transfer coefficient and it is found to increase significantly with an increase of the particle volume concentration. It is observed from the results that at the higher value of the Grashof number (Gr = 10⁴ ), the average Nusselt number increases with an increase in the Darcy number for a constant solid volume fraction. The detailed results are reported by means of streamlines, isotherms, and Nusselt numbers. © 2012 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21029     

Experimental exploration and theoretical certainty of thermal conductivity and viscosity of MgO-therminol 55 nanofluid

In this study, a combination of thermal conductivity, viscosity, and density characteristics are experimentally probed for attaining maximum heat transfer using MgO-Therminol 55 as nanofluid is reported. Recent studies proved that nanofluids have miserable properties that make them feasibly useful in many applications in heat transfer compared to base fluid.MgO-Therminol 55 nanofluid is synthesized by diffusion of MgO nanoparticles of size 160–190 nm in Therminol 55 at different concentrations (0.05%–0.3%). Thermal conductivity and viscosity are calculated at a temperature range of 30–60°C using kd₂ analyzer and Fenske viscometer. Data obtained from the experimental results reveals that when volume concentration is increased with respect to that thermal conductivity increases, viscosity decreases and density decreases at different temperatures. The proposed models were supportive to the experimental data.     

A time variant investigation on optical properties of water based Al2O3 nanofluid

Optical properties of nanofluids are vital for calculating performance of a Direct Absorption Solar Collector (DASC). Characteristics of nanofluids are not constant; they vary with time and growth of nanoparticles. For current investigation, nanofluids were prepared to obtain considerable stability. Stability ratio of our nanofluids was 100 times larger than the threshold limit. Here, we have investigated aggregation process and its effect on optical characteristics of the nanofluids using Transmission Electron Microscopy (TEM) imaging, Dynamic Light Scattering (DLS) approach and UV–visible spectroscopy. Steps of aggregation are broadly described with TEM images. Our results indicate that extinction coefficients of the nanofluids reduce rapidly with time within visible to near IR region. Quasi Crystalline (QC) and Rayleigh Approaches were used to compare the experimental behavior of optical properties of nanofluids. It was found that both of these approaches are weak to predict the optical behavior, especially at UV region and scattering of light is found responsible for high extinction with the experimental results. More experimental effort is still required to get an appropriate explanation.     

Cu‐Al2O3/H2O hybrid nanofluid flow past a porous stretching sheet due to temperatue‐dependent viscosity and viscous dissipation

The resent development of research in the field of nano technology introduced hybrid nanofluids which are advanced classes of fluids with augmented thermal properties and it gives better results comparing to regular nanofluid. The aim of the present work is to study the significant effects of variable viscosity and viscous dissipation on a porous stretching sheet in the presence of hybrid nanofluid and radiative heating. In this model, two types of nanoparticles, namely copper (Cu) and alumina oxide (Al₂O₃), are suspended in the base fluid H₂O to form a hybrid nanoliquid. The novelty of this study is to introduce variable viscosity along with natural convection in the momentum equation and viscous dissipation in the energy equation. Mathematical modeling is employed in this study, whereby partial differential equations for the fluid flow are constructed and transformed to a set of ordinary differential equations, and hence resolved computationally by Runge‐Kutta‐Fehlberg method along with shooting scheme. The most important results for relevant parameters concerning the flow heat measure, surface drag, and heat transfer coefficients are thoroughly examined and presented graphically for both Cu‐Al₂O₃/water hybrid nanofluids. There is an increase in hybrid nanofluid velocity profile with mounting values of $\lambda$, and the Cu‐water nanofluid converges to the boundary more quickly than the hybrid nanofluid due to the occurrence of variable viscosity. The results concluded that the Nusselt number of the viscous fluid is lower than that of the nanofluid and hence the hybrid nanofluid (ie, heat transfer rate: normal fluid < nanofluid < hybrid nanofluid). The outcomes of present investigations are in close agreement with the viscous fluid as a particular case.