Conductivity Of Nanofluids Research Articles

Nanoparticle‐enhanced dielectric oils for improved electrical insulation: Comparison of MgO, Al2O3, and SiO2‐based dielectric nanofluids

AbstractThis study provides comprehensive and quantitative assessments of the electrical insulation, viscosity, thermal conductivity, flash point, acidity, and stability of dielectric nanofluids. In the experiment, naphthenic mineral oil was chosen as the base fluid. MgO, Al2O3, and SiO2 were preferred as nanoparticles. In the dielectric breakdown voltage (BDV) tests performed, increased values were observed at certain concentrations for each nanofluid, with the highest value in the SiO2‐based nanofluid being 83.47 kV at a concentration rate of 0.05 g/L. Adding nanoparticles to the base oil increased the viscosity of all suspensions. Except for MgO‐based dielectric nanofluid, the flash points of other nanofluids increased as compared to pure oil. Total acid number (TAN) values, on the other hand, increased for SiO2‐ and Al2O3‐based nanofluids but decreased for MgO‐based nanofluids. However, all values are quite below the standard limit of 0.25 mgKOH/g. The percentage transmittance values calculated from the ultraviolet and visible light (UV–vis) spectrophotometry results differed for each nanofluid. However, they were all lower than the base oil. In general, the results indicate that the use of dielectric nanofluids in electrical systems will be beneficial, provided that the problem of long‐term stabilisation is solved.

Thermal conductivity of Janus nanofluids with hydroxylated carbon nanotubes

Thermal conductivity of Janus nanofluids with hydroxylated carbon nanotubes

Experimental and explainable machine learning approach on thermal conductivity and viscosity of water based graphene oxide based mono and hybrid nanofluids

This study explores the thermal conductivity and viscosity of water-based nanofluids containing silicon dioxide, graphene oxide, titanium dioxide, and their hybrids across various concentrations (0 to 1 vol%) and temperatures (30 to 60 °C). The nanofluids, characterized using multiple methods, exhibited increased viscosity and thermal conductivity compared to water, with hybrid nanofluids showing superior performance. Graphene oxide nanofluids displayed the highest thermal conductivity and viscosity ratios, with increases of 52% and 177% at 60 °C and 30 °C, respectively, for a concentration of 1 vol% compared to base fluid. Similarly, graphene oxide-TiO2 hybrid nanofluids achieved thermal conductivity and viscosity ratios exceeding 43% and 144% compared to the base fluid at similar conditions. This data highlights the significance of nanofluid concentration in influencing thermal conductivity, while temperature was found to have a more pronounced effect on viscosity. To tackle the challenge of modeling the thermophysical properties of these hybrid nanofluids, advanced machine learning models were applied. The Random Forest (RF) model outperformed others (Gradient Boosting and Decision Tree) in both the cases of thermal conductivity and viscosity with greater adaptability to handle fresh data during model testing. Further analysis using shapely additive explanations based on cooperative game theory revealed that relative to temperature, nanofluid concentration contributes more to the predictions of the thermal conductivity ratio model. However, the effect of nanofluid concentration was more dominant in the case of viscosity ratio model.

Measurement of Thermal Conductivity of ZnO and SiO2 Water Based Nanofluids

The preparation and definition of thermal characteristics of novel-type nanofluids are critical for understanding the fluidity mechanism of nanofluids and selecting appropriate nanofluids for application. This study seeks to give an alternative fluid for various applications and to fill a new type of nanofluid requirement in the literature that has been identified by many research groups. In this study, a water-based ZnO-SiO2 nanofluid is synthesized in two steps, and the thermal conductivity values are experimentally determined. It is found that thermal conductivity increases with the increase in the concentration of particles. The maximum deviation ofthermal conductivity of SiO2 nanofluid is found to be 1.30% whereas in the case of ZnO nanofluid it is found to be 2.65%.

Preparation, thermal and lubricant properties of paraffin based nanofluid containing boron nitride nanoplatelets

Herein, high thermal conductivity and good lubrication paraffin based nanofluid containing boron nitride nanoplatelets (BNNP) were prepared by ultrasonication method. The BNNP prepared by chemical assisted ball milling with size ranging from 400 nm to 1 µm were dispersed in paraffin oil to obtain nanofluid. The thermal conductivity of nanofluids is much improved compared to paraffin oil and paraffin oil containing as-received hexagonal boron nitride (hBN). Besides, the nanofluid containing 0.1 % BNNP exhibited an enhancement in lubricant with 71 % reduction in coefficient of friction compared to paraffin. This is attributed to the good lubricant, nanosizes of BNNP compared to as-received hBN.

Optical properties, thermal conductivity, and viscosity of graphene-based nanofluids for solar collectors

Nanofluids based on graphene and water are promising working fluids for use in solar collectors. In this study, the optical properties, thermal conductivity, and viscosity of nanofluids based on water and graphene material, with the addition of sodium dodecyl sulfate (SDS) surfactant, were experimentally investigated. To obtain these nanofluids, graphene nanoparticles were synthesized using a plasma-chemical method and were later characterized by scanning electron microscopy, transmission electron microscopy, and Raman spectroscopy. The relationships between the concentrations of graphene in the nanofluids and the geometric parameters of vessels for effective absorption of solar energy were determined. The spectral dependences of the extinction coefficient for the nanofluids and for aqueous solutions with black aniline dye were compared. It was found that the application of graphene-based nanofluids is more effective than aqueous solutions based on aniline dye in photothermal energy conversion. Additionally, it was noted that the addition of graphene and the SDS surfactant does not lead to an increase in viscosity or a significant change in the thermal conductivity of the nanofluids for concentrations up to 0.02 wt%. The results showed that the studied nanofluids are effective absorbers of solar energy and, at the same time, do not require additional energy consumption to move through the solar harvesting circuit.

Atomistic Investigation of Viscoelastic Nanofluids as Heat Transfer Liquids for Immersive-Cooling Applications.

A comparative assessment of the thermal properties and heat transfer coefficients achieved by viscoelastic nanofluids suitable for immersion cooling is presented, with the candidate samples exhibiting distinct differences based on the nanoparticle chemistry and shape. Molecular dynamics simulations of different nanoparticles such as copper nanosphere, two-dimensional pristine graphene, and single-walled carbon nanotube (CNT) dispersed in PAO-2 of concentrations of approximately equal to 2.6% by weight are performed in the present investigation. While carbon-based nanoparticles increase the specific heat capacity of the nanofluids, copper-based nanofluids show a decrease in the corresponding values. Moreover, the heat conduction in copper-based nanofluids is dependent on the higher degree of phonon density of states (DOS) matching between the copper and solvent atoms, whereas the high intrinsic thermal conductivity of graphene and CNT compensates for the lower degree of DOS matching. The addition of an OCP polymer chain to impart viscoelasticity in the nanofluids exhibits a heat transfer coefficient enhancement of more than 80% during Couette flow as a result of chain expansion, indicating their suitability for immersive-cooling applications.

Stability and thermo-physical characteristics of EG/H2O-based nanofluid with graphene nanoplatelets for secondary coolant applications

In the present article, the thermophysical properties of an EG-H2O dispersed with GNP nanofluid are studied. The graphene nanoplatelets were dispersed in a 50:50 volume ratio (1113.2:1000 by mass in g per litre) of EG and H2O along with Gum Arabic surfactant to create the stable nanofluid dispersions by varying vol% of GNP from 0.1% to 0.5% in steps of 0.1%. The stability of proposed GNP-EG/H2O nanofluid was found using the zeta potential distribution method. A thermal properties analyzer, densitometer and rheometer were used to measure the thermal conductivity (k) (heat conduction), specific heat capacity (Cp), density (ρ) and viscosity (µ) of the nanofluid. All the properties were measured with various temperatures ranging from −15 °C to 15 °C with interval of 5 °C. The outcomes of steadiness test performed and reveal that the GNP-EG/H2O nanofluid was stable and exhibits a zeta potential distribution of −33.7 mV at 0.5 vol% of GNP. The thermal conductivity and thermal diffusivity of nanofluid enhanced by about 8.6% and 10.43% respectively when compared to the base fluid while the specific capacity decreased by 8.96% at 15 °C for 0.5 vol%. The proposed nanofluid favorable for all volume concentration under laminar flow regime while it was favorable up to 0.1% under turbulent regime which observed from the predicted effectiveness.

Numerical investigation of conjugate heat transfer in a partitioned cavity using NiO nanofluid and firefly algorithm

The fluid's heat transfer properties must be effectively utilized to create efficient heat exchangers. In various existing studies, the application of forced convection leads to pressure drops in conjugate heat transfer systems due to the nanoparticles used. To overcome this issue an efficient heat transfer enhancement using a new approach based on NiO with Cu clad metalcore in a partitioned cavity is introduced. NiO scoria nanofluid minimizes pressure drops, pumping powers enhances stability, saves energy, and allows for smooth heat transfer. Numerical simulation results show that when the concentration of NiO scoria is 4%, the thermal conductivity is at 46.024 W/mK. At a heat transfer coefficient of 175 W/m2K, the maximum heat flux is 39,000 W/m2. Then, to simulate the viscosity and thermal conductivity of nanofluids and also to reduce the number of iterations and the computational time K-Adam Hybrid Enhanced Attractive Automata Firefly algorithm has been used. The numerical solution of the ordinary differential equations associated with conjugate heat transfer is achieved using a Predictor–Corrector Method. The study’s novel integration of advanced algorithms and nanofluid composition offers practical applications in power generation, electronic cooling, and HVAC systems, demonstrating the method's relevance and the need.

Thermal conductivity of Al2O3 nanofluid utilizing cross-linked polyacrylic acid (PAA) as the base fluid: An experimental study

Thermal conductivity of Al2O3 nanofluid utilizing cross-linked polyacrylic acid (PAA) as the base fluid: An experimental study

Thermal and rheological behavior of aluminium-doped zinc oxide nanofluids: Experimental study and application of artificial neural network model

In this study, the influence of Al-doping concentration on the thermal and rheological characteristics of pristine zinc oxide (ZnO) nanofluids was investigated across a range of temperatures and nanoparticle concentrations. A multilayer perceptron (MLP) artificial neural network (ANN) with an optimized topology was employed to model the thermal conductivity and viscosity of nanofluids. The addition of 0.13 M of Al-doped zinc oxide nanoparticles at 1 % rate led to a remarkable 64 % increase in the thermal conductivity of the base fluid (50:50 ratio water + ethylene glycol mixture). Furthermore, incorporating 1 % of these Al-doped nanoparticles outperformed pure zinc oxide, resulting in a 44 % boost in thermal conductivity. The enhanced heat transfer capabilities of Al-doped zinc oxide were evident across different doping and nanoparticle concentrations. The viscosity of nanofluids increases with an increase in nanoparticle concentration and decreases with an increase in temperature. ZnO and Al-doped ZnO nanoparticles have been prepared and studied their structural, morphological and elemental properties using XRD, SEM and EDS respectively. The predicted thermal and rheological behaviours are in close agreement with the experimental values.

WITHDRAWN: The enhanced heat transfer and flow dynamics of tangent hyperbolic and Newtonian nanofluids under inclined variable magnetic field

This paper aims to analyze the thermal conductivity of tangent hyperbolic non-Newtonian fluids and Newtonian nanofluids over a porous, inclined, stretching sheet with motile microorganisms. It also examines the impact of inclined variable magnetic field, activation energy, thermal radiation, thermophoresis and Brownian motion. The novelty of this research lies in the simultaneous use of inclined geometry and an inclined variable magnetic field. The findings optimize environmental and food processing applications, drug delivery, thermal management, lubrication, and enhanced oil recovery. A far-reaching analysis compares the behaviors of tangent hyperbolic fluid with Newtonian fluid. Appropriate similarity functions are used to convert the governing system of nonlinear PDEs for tangent hyperbolic fluid to dimensionless ODE. MATLAB’s boundary value solver BVP4C is then used to solve these ODEs numerically. This study explores various characteristics, including temperature, velocity, concentration, and microorganism distribution. In the essence of this computational study, the impacts of inclined angle, porosity, mixed convection, Hartmann number and Weissenberg number on the velocity of the fluid are analyzed. The main findings are that higher Prandtl numbers reduce heat transfer rates, while thermophoresis and Brownian motion enhance heat flow. Lewis and Peclet numbers show declining tendencies in motile microorganisms, with magnetic fields influencing their distribution within the fluid; this is useful in biotechnology and environmental applications. Consequently, the effect is greater in the case of non-Newtonian fluids which depend more on the inclination angle, inclined variable magnetic field strength, thermal conductivity and activation energy when compared with the Newtonian fluids.

Current advancements in fluid-flow Problems: A brief review

This specific article is a compilation of a few current studies on fluid flow issues. This article provides an overview of current research on the experimental and theoretical analysis of various nanofluids' thermal conductivity. The current study examines a number of variables that have a significant impact on a nanofluid's ability to transfer heat, including temperature, solid volume fraction, type, size, shape, magnetic field, pH, ultrasonic time, and surfactant. In addition, some plausible and appealing theories that enhance the thermal conductivity of nanofluids are mentioned. The final important heat transmission mechanisms that play a significant part in improving thermal conductivity are Brownian motion, thermophoresis, nanoclustering, interfacial nano-layer, and osmophoresis. Thus, consideration is given to the heat transmission properties of nanofluids. And also discussed some Numerical method to solve fluid flow problems.

Boost heat transfer efficiency through thermal radiation and electrical conductivity in nanofluids

AbstractThermal radiation and electrical conductivity in nanofluids are crucial for their heat transfer characteristics, especially in applications with elevated temperatures or significant radiative heat transfer. The suspension of nanoparticles in suspension contributes to the fluid's electrical conductivity, which is essential for efficient heat dissipation in electronic cooling systems. Understanding the behavior of electroconductive nanofluids is particularly important in electronic cooling applications, where effective heat dissipation is crucial to prevent overheating. A study using a similarity parameter transformed a system of coupled PDEs into a set of nonlinear ordinary differential equations, revealing significant changes in key physical characteristics, such as temperature distribution, cubic concentration field, and velocity field. The study also examined the effects of parameters like Brownian motion, Rayleigh number, Peclet number, thermophoresis parameter, and buoyancy ratio parameter. The research provides valuable insights into the complex dynamics of magnetized non‐Newtonian nanofluids and offers practical implications for applications like microbial fuel cells and heat transmission equipment.

Numerical Study on Heat Transfer Characteristics of Jet Impingement by using MgO Nanofluid

Liquid impingement jet can provide high local heat transfer coefficients between the impinged liquid and the targeted surface. Jet impingement is utilized in the applications which is related to rapid cooling and better control of high temperature in many applications. The studies are carried out numerically by using ANSYS Workbench 18.2. Hexagonal meshing and Shear-Stress Transport (SST) turbulence model is used in the numerical simulation. By using SST turbulence model, the effect of jet Reynolds number, nanofluid volume concentration on the average heat transfer coefficient of the target plate is analysed and discussed. For the effect of varying the Reynolds number, it is observed that the surface average heat transfer coefficient increases at least 76.18% as the Reynolds number increases from 5000 to 10000. Moreover, the heat transfer coefficient increases as the volume concentration increases from 0% to 5%. It is also observed that when the nanofluid with higher thermal conductivity will results in higher heat transfer coefficient where the MgO nanofluid showed the highest heat transfer coefficient. As a conclusion, by increasing Reynolds number, volume concentration and thermal conductivity of nanofluid, the heat transfer coefficient can be enhanced.

Heat Transfer in Carbon-Nanotube Dispersions: A Simulation Study of the Role of Nanotube Morphology and Connectivity

Simulation of the behavior of carbon nanotubes (CNTs) can become a very challenging task considering their complicated shape and large aspect ratio. This study aims to elucidate the role of CNT shape, length, and connectivity during heat transfer in CNT dispersions through a three-dimensional (3D) simulator. Three characteristic shapes for the CNTs are considered, namely, straight, moderately curved, and strongly curved. The results reveal that the commonly used assumption of viewing CNTs as straight cylinders leads to significant overestimation of the overall medium conductivity. The CNT length has an important effect on the nanofluid conductivity for all types of CNT shapes considered here. In addition, use of CNTs with higher conductivity than a certain value appears to have no further beneficial effect, thus relaxing the need for extremely pure or single-wall CNTs. On the contrary, the conductivity remains a strong function of the CNT concentration and may be even increased upon organization of CNTs into loose clusters. The overall approach and concept can be extended to CNT composites in a straightforward manner.

Performance investigation on PVT collector with cerium oxide nano fluids

The constant temperature rise on the solar panel surface causes a deterioration of electrical power generation. This article is provided with the performance of photovoltaic thermal (PVT) collector through cerium oxide with water as a base fluid. A small percentage of incoming radiation is transformed into electricity and rest of them is wasted as hot energy, the panel surface temperature will confine the performance of PV module. The research's objectives were to develop and construct a photovoltaic/thermal collector and evaluate its thermal and electrical energy as an output. The experimental investigation of PVT collector with two different concentration of cerium oxide 0.5 and 1.0 LPM (litres per minute). As per the investigations on the PVT collector results were obtained as electrical performance of collector was attained about 18.56 %, 19.12 % for the flow rate of 0.5 and 1.0 LPM. Similarly, thermal performance was achieved 48.38 %, 54.03 % for the flow rate of 0.5 and 1.0 LPM. Thermal conductivity of cerium oxide nano fluid was much better than the air and water. It was observed that employing a nano fluid to the receiver might increase the efficiency around 5–10 %, compared to utilising water as a base fluid, water can only generate 3–7 %. As a cooling medium, air has a relatively low production capacity between 2 and 3 %.

Experimental determination of thermal conductivity of CNTs-H2O based nanofluids

Solar thermal collectors are being widely used for water heating applications in domestic, commercial, and industrial sectors. The main drawback of these collectors is their low thermal efficiency. The thermal efficiency of these collectors can be significantly increased by enhancing the heat transfer fluid’s thermal properties. This problem can be overcome by homogeneous mixing of nanoparticles in the base fluid such as water. The fluids with nanoparticles have better heat transfer efficiency and thermo-physical properties as compared to monofluid (water). In this study, the percent rise in thermal conductivity of the nanofluids is measured through experimentation by dissolving carbon nanotubes (CNTs) as nanoparticles in different concentrations (v/v %) inside the base fluid. The nanofluids are characterized by using the computer controlled thermal conductivity of liquids and gases unit, (TCLGC) by varying the CNTs sample composition from 0.01-0.05 v/v %. The results show that the inclusion of CNTs as nanoparticles significantly improves the thermal conductivity of nanofluids. Moreover, when CNTs are used at 0.05 v/v% inside a 100 ml sample solution, the highest increase in thermal conductivity is observed as 72%

Influence of Temperature and Nanoparticle Concentration on the Electrical Conductivity of Water-Based TiO2 Nanofluids: Experimental Study, Correlation, and Model Assessment

Different volume fractions of TiO2/water nanofluids were created using TiO2 nanoparticles synthesized via the chemical coprecipitation technique. The electrical conductivity (EC) of each nanofluid was then measured at specific temperatures, ranging from 10 to 60 °C. X-ray diffraction (XRD) analysis confirmed the presence of the TiO2 anatase phase and a minor presence of the rutile phase. Measurements from dynamic light scattering (DLS) and UV-Vis spectroscopy revealed that the nanoparticles exhibit an average diameter close to 26 nm, with an optical band gap estimated to be about 3.8 eV. Experimental findings demonstrated that both temperature and volume fraction play significant roles in enhancing the EC of nanofluids. These findings were evaluated compared to an earlier model for nanofluid conductivity that includes nanoparticle Brownian motion and electrophoretic effects, demonstrating a close alignment between the predicted and observed values. Furthermore, the long-term stability of the nanofluids was validated, and a reliable correlation was established between the nanofluid’s EC, temperature, and volume fraction.

Improvement of heat transfer within solar water heater’s tubes (SWH) using nanofluids

This research offers a numerical study of steady and laminar mixed convection flow in a circular pipe as part of a flat plate solar collector, which is crossed by nanofluids. The pipe is kept at a constant wall temperature and then at a constant heat flux, which represents the solar radiation received by the pipe. The governing coupled equations are solved with the finite volume approach. Computations are carried out using an in-house computer code, which has been satisfactorily validated by comparison to previous investigations. Empirical relations are used to predict the effective thermal conductivity and viscosity of nanofluids. The results are investigated using dynamic and thermal fields, with a special emphasis on the Nusselt number calculated along the active wall. They demonstrate that increasing the volume fraction of nanoparticles and Reynolds number improves heat transfer.