Experimental determination of thermal conductivity and viscosity of different nanofluids and its effect on a hybrid solar collector

In this research, three different volume concentrations (??=?0.05, 0.1 and 0.2%) of Al₂O₃/water, CuO/water and Al₂O₃–CuO/water (50:50) nanofluids are prepared by adopting a two-step nanofluid preparation method. Al₂O₃ and CuO nanoparticles with the average diameter of 50 nm and 27 nm were dispersed in distilled water. The thermal conductivity and viscosity of prepared nanofluids are measured for different temperatures by using KD2 Pro thermal property analyzed and Brookfield viscometer, respectively. The effects of nanofluids on the thermal, electrical and overall efficiency of photovoltaic thermal (PVT) solar collector are also studied. The experimental results revealed that the thermal conductivity and viscosity increase with the increase in percentage volume concentration and viscosity decreases with the increase in temperature. Furthermore, the obtained maximum thermal and electrical efficiencies of a PVT solar collector for 0.2% volume concentration of hybrid nanofluids are 82% and 15%, respectively, at peak solar radiation. The highest overall efficiency of a PVT collector with .2% volume concentration of hybrid nanofluid was 97% at peak solar radiation. Results recommend that nanofluids can be used as a heat transfer in PVT solar collector.

     

Thermal conductivity of Al2O3/water nanofluids

A considerable number of studies can be found on the thermal conductivity of nanofluids in which Al₂O₃ nanoparticles are used as additives. In the present study, the aim is to measure the thermal conductivity of very narrow Al₂O₃ nanoparticles with the size of 5 nm suspended in water. The thermal conductivity of nanofluids with concentrations up to 5 % is measured in a temperature range between 26 and 55 °C. Using the experimental data, a correlation is presented as a function of the temperature and volume fraction of nanoparticles. Finally, a sensitivity analysis is performed to assess the sensitivity of thermal conductivity of nanofluids to increase the particle loading at different temperatures. The sensitivity analysis reveals that at a given concentration, the sensitivity of thermal conductivity to particle loading increases when the temperature increases.     

Microwave synthesis of silver nanofluids with polyvinylpyrrolidone (PVP) and their transport properties

Microwave synthesis has been applied to prepare stable silver nanofluids in ethanol by reduction of AgNO₃ with polyvinylpyrrolidone (PVP), used as stabilizing agent, having Ag concentrations of 1% by volume. The nanofluids were characterized by UV-vis spectroscopy, Fourier transform infrared, energy-dispersive X-ray spectroscopy, and transmission electron microscopy and systematically investigated for refractive index, electrical and thermal conductivity, and viscosity for different polymer concentrations. The size of nanoparticles was found to be in the range of 30–60 nm for two different salt-to-PVP ratios. For higher concentration of polymer in nanofluid, nanoparticles were 30 nm in size showing increase in thermal conductivity but a decrease in viscosity and refractive index, which is due to the polymer structure around nanoparticles. Thermal conductivity measurements of nanofluids show substantial increment in the thermal conductivity of nanofluid relative to the base fluid and nonlinear enhancement over the 283–323 K temperature range. Rheology of nanofluids was studied at room temperature showing effect of polymer on viscosity and confirming the Newtonian behavior of nanofluid.     

Enhanced thermal properties of Li2CO3–Na2CO3–K2CO3 nanofluids with nanoalumina for heat transfer in high-temperature CSP systems

Nanofluids of Li₂CO₃–Na₂CO₃–K₂CO₃ improved by three nano-Al₂O₃ samples are firstly prepared by means of two-step aqueous method to enhance thermal properties for high-temperature heat transfer, when used as heat transfer fluids and thermal energy systems for concentrating solar power systems. Specific heat of ternary carbonates containing Al₂O₃ of 0.2, 0.4, 0.8, 1.0, 1.4 and 2.0 mass% is measured, and nanofluids with 1.0 mass% of 20-nm Al₂O₃, 1.0 mass% of 50-nm Al₂O₃ and 0.8 mass% of 80-nm Al₂O₃ are selected as superior candidates. The maximum enhancement of specific heat is 18.5% in solid and 33.0% in liquid, 17.9% in solid and 22.7% in liquid, 13.2% in solid and 17.5% in liquid for nanofluids containing 20-, 50- and 80-nm Al₂O₃. Thermal conductivity is, respectively, improved by 23.3, 28.5 and 30.9% under the addition of Al₂O₃. New chemical bonds and crystals are scarcely formed in composites through FT-IR and XRD determination. SEM images certify that nano-Al₂O₃ are homogeneously mixed into nanofluids and this structure may be a critical incentive for enhancing thermal properties. There are no significant changes with respect to the heat flow, melting/freezing point and latent heat after the 30 circles of determination. Briefly, it can be speculated that these nanofluids will exhibit tremendous potential in the coming applications of heat transfer and thermal storage for concentrating solar power systems.

     

A new semi-analytical model for effective thermal conductivity of nanofluids

A new theoretical model for thermal conductivity of nanofluids is developed incorporating effective medium theory, interfacial layer, particle aggregation and Brownian motion-induced convection from multiple nanoparticles/aggregates. The predicated result using aggregate size, which represents the particle size in the actual condition of nanofluids, fits well with the experimental data for water-, R113- and ethylene glycol (EG)-based nanofluids. The present model also gives much better predictions compared to the existing models. A parametric analysis, particularly particle aggregation, is conducted to investigate the dependence of effective thermal conductivity of nanofluids on the properties of nanoparticles and fluid. Aggregation is the main factor responsible for thermal conductivity enhancement. The dynamic contribution of Brownian motion on thermal conductivity enhancement is surpassed by that of static mechanisms, particularly at high volume fraction. Predication also indicated that the viscosity increases faster than the thermal conductivity, causing the highly aggregated nanofluids to become unfavourable, especially for d_f = 1.8.     

Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network

The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25–55 °C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids.     

Thermal performance of stable SiO2 nanofluids and regression correlations to estimate their thermophysical properties

The present work investigates the best mix ratio of Glycerol in Water as a medium to prepare a stable nanofluid. Increasing the proportion of glycerol enhances the aqueous mix's dynamic viscosity and improves the prepared nanofluid's stability. The thermal conductivity and viscosity of the Glycerol and Water mixtures determination were undertaken at various Glycerol ratios. The best percentage of glycerol in the mixture is found to have the least amount of thermal conductivity loss and the optimum viscosity gain. Silica (SiO₂) nanofluid of 0.25%, 0.5%, 1%, and 1.5% weight concentrations was prepared with this optimal mixture of Glycerol and Water. The stability of these SiO₂ nanofluids is evaluated by determining the zeta potential at different time intervals. The nanofluids prepared were observed to be stable for one month. The thermal conductivity and viscosity of the nanofluids are measured between the temperature limits of 30°–70°C. A peak increment of 32.1%and 46.3% in thermal conductivity and viscosity is observed. Furthermore, when the percentage enhancement ratio (PER) and Mouromtseff ratio of these nanofluids is examined, it is observed that they have more excellent thermal performance at higher temperatures. Regression correlations are developed to estimate the thermal conductivity and viscosity of the prepared nanofluids with a maximum deviation of 9%.     

Synthesis and thermo-physical properties of water-based novel Ag/ZnO hybrid nanofluids

The comparative study on the thermo-physical properties of water-based ZnO nanofluids and Ag/ZnO hybrid nanofluids is reported in the present study. The outer surface of ZnO nanoparticles was modified with a thin coating of Ag nanoparticles by a wet chemical method for improved stability and heat transfer properties. The ZnO and Ag/ZnO nanofluids were prepared with varying volume concentration (??=?0.02–0.1%). The synthesized nanoparticles and nanofluids were characterized with different characterization methods viz., scanning electron microscopy, X-ray diffraction, dynamic light scattering, thermal conductivity measurement, and viscosity measurement. Results show that thermal conductivity of Ag/ZnO hybrid nanofluids is found to be significantly higher compared to ZnO nanofluids. The maximum thermal conductivity an enhancement for Ag/ZnO nanofluid (??=?0.1%) is found to 20% and 28% when it compared with ZnO nanofluid (??=?0.1%) and water, respectively.     

A simple economic and heat transfer analysis of the nanoparticles use

In this paper, a review of the impact of most common nanoparticles on the Leidenfrost temperature T _Leid in heat transfer applications is delivered. Moreover, a simple economic analysis of the nanoparticles use is proposed. When coolant is distilled water, T _Leid can range 150–220 °C; occasionally, it can even amount to over 400 °C. When the base liquid is modified by additives, considerable changes in the character of heat transfer are observed. Out of five nanofluids under consideration in this study, the best thermal effect (up to 50%) is obtained when Al₂O₃ nanofluid having particle sizes ~39 nm and volume concentration of 0.1% is used. Conversely, the fluid containing TiO₂ particles, 20–70 nm in size, seems to be the worst of the analysed fluid, giving only 7% heat transfer enhancement in comparison with water. However, when TiO₂ nanoparticles are far smaller, very good thermal effects are obtained (23–25%). In a majority of the cases analysed, the temperature that marks the onset of film boiling is inversely proportional to concentrations of nanoparticles, which is relevant from the economic standpoint.     

Ionic liquid-based stable nanofluids containing gold nanoparticles

A one-phase and/or two-phase method were used to prepare the stable ionic liquid-based nanofluids containing same volume fraction but different sizes or surface states of gold nanoparticles (Au NPs) and their thermal conductivities were investigated in more detail. Five significant experiment parameters, i.e. temperature, dispersion condition, particle size and surface state, and viscosity of base liquid, were evaluated to supply experimental explanations for heat transport mechanisms. The conspicuously temperature-dependent and greatly enhanced thermal conductivity under high temperatures verify that Brownian motion should be one key effect factor in the heat transport processes of ionic liquid-based gold nanofluids. While the positive influences of proper aggregation and the optimized particle size on their thermal conductivity enhancements under some specific conditions demonstrate that clustering may be another critical effect factor in heat transport processes. Moreover, the remarkable difference of the thermal conductivity enhancements of the nanofluids containing Au NPs with different surface states could be attributed to the surface state which has a strong correlation with not only Brownian motion but also clustering. Whilst the close relationship between their thermal conductivity enhancements and the viscosity of base liquid further indicate Brownian motion must occupy the leading position among various influencing factors. Finally, a promisingly synergistic effect of Brownian motion and clustering based on experimental clues and theoretical analyses was first proposed, justifying different mechanisms are sure related. The results may shed lights on comprehensive understanding of heat transport mechanisms in nanofluids.     

A new method of determining the thermal conductivities of energetic materials by microcalorimeter

A device of measuring the thermal conductivity of pellet of propellants and explosives has been constructed. A method and a calculation formula for determining the thermal conductivity of pellet of propellants and explosives under constant radial heat flow conditions by use of Joule effect is presented. Using this device and a microcalorimeter, type RD496-II, and two standard samples with known thermal conductivity, two instrument constant have been determined and the thermal conductivities of seven materials: plexiglass, teflon, DB propellant DB-2 (nitrocellulose(NC)/nitroglycerine(NG)/dinitrotoluene/dimethyl centralite/vaseline/PbO/CaCO₃, 59.6/25/8.8/3/1.2/1.2/1.2), DB propellant SQ(NC/NG/diethyl phthalate(DEP)/binder, 59/29/7/5), DB propellant RHN-149 (NC/NG/triacetin (TA)/binder-I, 52/25/8/15), DB propellant RHN-190 (NC/NG/TA/ binder-II, 52/26/7/15), 2, 4, 6-trinitrotoluene (TNT) at 298 K are measured. The results show that (1) the reproducibility of measurement for the heat (q) retained in investigated system after cutting the Joule current and the amount of heat flux through the wall of the investigated cylinder (Q _s) are less than 0.50% and within 0.10%, respectively; (2) the standard deviation of the thermal conductivity determined by using this method is less than 1.0%; (3) the values ofq, Q _s and internal radius of the cylinder are three principal factors affecting the magnitude of the thermal conductivity of these materials.     

Thermal conductivity and specific heat capacity measurements of Al2O3 nanofluids

Thermal conductivities and specific heat capacities of nanoparticles of Al₂O₃ dispersed in water and ethylene glycol as a function of the particle volume fraction and at temperatures between 298 and 338 K were measured. The steady-state coaxial cylinders method, using a C80D microcalorimeter (Setaram, France) equipped with special calorimetric vessels, was used for the thermal conductivities measurements. The heat capacities were measured with a Micro DSC II microcalorimeter (Setaram, France) with batch cells designed in our laboratory and the “scanning or continuous method.” The Hamilton–Crosser model properly accounts for the thermal conductivity of the studied nanofluids. Assuming that the nanoparticles and the base fluid are in thermal equilibrium, the experimental specific heat capacities of nanofluids are correctly justified.     

Gas phase thermal diffusivities by a thermal lens technique

A simplified design of thermal lens apparatus is presented in which a chopped cw argon laser beam produces a transient thermal lens in a cylindrical gas cell. The axial intensity variation of a cw helium-neon laser probing this lens is analysed to yield the thermal diffusivities and thus the thermal conductivity coefficients of Kr, CO₂, CH₄, C₂H₆, C₃H₈, C₃H₆ and C₄H₁₀ as 9.4 × 10^?3 ± 4%, 1.6 × 10^?2 ± 3%, 2.98 × 10^?2 ± 4%, 2.03 × 10^?2 ± 4%, 2.05 × 10^?2 ± 7%, 1.6 × 10^?2 ± 8% and 1.9 × 10^?2 ± 8% respectively in W m^?1 K^?1 at 300 K. The method is rapid, requiring only that the sample be transparent at both laser frequencies used. A simplified mathematical analysis is shown to be adequate for this system. For the conditions specified, self-lensing of the argon laser beam is shown to be compensated by using an effective laser beam diameter.     

Co-doping effect on the properties of scandia stabilized ZrO2

The influence of low concentrations (1 mol %) of few co-dopants (Y₂O₃, La₂O₃, CeO₂, Gd₂O₃, Er₂O₃, ZnO) on the structure and characteristic of 10 mol % scandia stabilized zirconia was studied. Sintering kinetics and thermal expansion coefficients of synthesized solid eletrolytes were determined. It was found that co-doping increased the conductivity of electrolytes at temperature below 550°C. However, at high temperatures, the introduction of co-dopants decreased the conductivity; moreover, this reduction was more severe the more the ionic radii of Zr⁴⁺ and co-dopant differ.     

Transport Coefficients in Water Plasma: Part I: Equilibrium Plasma

Knowledge of the transport coefficients of steam water plasma is important for modeling plasma flow processes and heat transfer. In this study, calculations of these properties were performed in a temperature range from 400 to 30,000 K and at pressures of 0.5, 1.0, 5.0 and 10 bar. Herein the composition of water plasma was determined at equilibrium. First, the most recent data on potential interactions and elastic differential cross sections for interacting particles were carefully examined in order to choose those most appropriate for determining the collision integrals. Second, we restricted the number of species to ten (e, H, O, H⁺, O⁺, O⁺⁺, H₂, O₂, OH and H₂O) and tested our collision integrals by comparing the thermal conductivity and viscosity to experimental data for water (at low temperatures). Finally, the total thermal conductivity, viscosity and electrical conductivity were calculated for different pressures.     

WSe2 nanowires-based nanofluids for concentrating solar power

Tungsten selenide belongs to the family of inorganic compounds denominated transition metal dichalcogenides (TMDCs). There is emerging interest in these compounds in the field of optoelectronics, catalysis, sensing or energy storage, among others. Most works focus on the use of these materials in their 2D form but there is scarce research on the study of TMDCs nanomaterials with one-dimensional morphology. In this work, we explore the thermophysical properties of nanofluids based on 1D-WSe₂ nanostructures with the aim of studying the feasibility of these nanofluids as heat transfer fluids in concentrating solar power plants. In this respect, nanofluids with a high heat transfer rate could increase the thermal efficiency of solar power plants, which would reduce the energy dependence on fossil fuels. Nanofluids of 0.02 wt%, 0.05 wt% and 0.10 wt% WSe₂ concentrations have been prepared by the two-step method considering a thermal fluid used in solar power plants as the base fluid. The results of extinction coefficient evolution, ζ potential and particle size in suspension show a high colloidal stability over time of the prepared nanofluids mainly because of the high aspect ratio of the 1D-WSe₂ nanomaterial. Additionally, the one-dimensionality and length of the synthesized nanowires favors the transport of heat in controlled directions, obtaining increases in thermal conductivity with respect to the base fluid of up to 16.8% in the highest concentration nanofluid. Improvements in isobaric specific heat of up to 15.7% and heat transfer of up to 20.8% compared to the base fluid have also been found. The results of this paper provide evidence that the presence of WSe₂ nanowires induces increases in the thermal properties of the fluid commonly used in concentrating solar power plants without inducing agglomeration or sedimentation problems. Therefore, the nanofluids based on 1D-WSe₂ nanostructures prepared in this work have a high potential to be used as heat transfer fluids in concentrating solar power plants based on parabolic trough collectors.     

Thermal conductivity of dry anatase and rutile nano-powders and ethylene and propylene glycol-based TiO2 nanofluids

Thermal conductivity behaviour was studied for two TiO₂ nano-powders with different nanocrystalline structures, viz. anatase and rutile, as well as nanofluids formulated as dispersions of these two oxides up to volume concentrations of 8.5% in two different glycols, viz. ethylene and propylene glycol. Because it is known that titanium dioxide can exhibit three different crystalline structures, the dry nano-powders were analysed using X-ray Diffraction to determine the nanocrystalline structure of the powders. Two different techniques were employed in the thermal conductivity study of the materials. Dry nano-powders, with and without compaction, were analysed at room temperature by using a device based on the guarded heat flow meter method. Nanofluids and base fluids were studied with a transient hot wire technique over the temperature range from (283.15 to 343.15) K. The base fluid propylene glycol was measured by using both techniques in order to verify the good agreement between both sets of results. The experimental measurements presented in this work were compared with other literature data for TiO₂ nanofluids in order to understand the thermal conductivity enhancement as a function of nanoparticle concentration. Different theoretical or semi-theoretical approaches such as Maxwell, Peñas et al., Yu-Choi were evaluated comparing with our experimental values. A parallel model was used to predict thermal conductivities employing experimental values for dry nanopowder.     

Thermal analysis for heat transfer enhancement in electroosmosis-modulated peristaltic transport of Sutterby nanofluids in a microfluidic vessel

Viscosity plays a crucial role in the flow and heat transfer process of nanofluids. To effectively calculate and predict the changing characteristics of nanofluids viscosity, this study presents a theoretical model combining the static interface layer and dynamic Brownian motion mechanisms of spherical nanoparticles for water-based Newtonian nanofluids. The model describes the reasonable dependences of nanofluids viscosity on physical properties of nanoparticles (density, volume fraction, size) and base fluid (temperature, viscosity, density). Taking four kinds of typical water-based Newtonian nanofluids containing spherical oxide nanoparticles (Al₂O₃, CuO, SiO₂ and TiO₂) as examples, the prediction performance of different viscosity models is analyzed in detail. From the comparison studies, it is demonstrated that the new viscosity model developed in this paper can exhibit better prediction performance than many well-known theoretical models and empirical correlations. Not only do the predicted results of model agree well with the experimental data from various studies, but also the effects of different factors are reflected effectively.

     

Synthesis and ionic conductivity of polymer ionic liquids

Four vinyl monomers containing a covalently bonded cation ethylimidazolium and various anions—Br^?, (CF₃SO₂)₂N^?, (CN)₂N^?, and CF₃SO ₃ ^? —have been synthesized. High-molecular-mass polymers (M _w up to 1.84 × 10⁶) having the structure of ionic liquids have been prepared via the free-radical polymerization of 1-vinyl-3-ethylimidazolium in bulk and molecular and ionic solvents. The thermal stability and heat resistance of the resulting polymer salts have been estimated. It has been demonstrated that the thermal characteristics of these salts significantly depend on the nature of anions. The glass-transition temperatures of the polymers range from 19 to 235°C. The ionic conductivity of the polymer salts and their compositions with individual ionic liquids has been studied in the frequency range 50–10⁶ Hz. The highest conductivity (1.5 × 10^?5 S/cm) is exhibited by the polymer containing the (CN)₂N^? anion.     

Forecasting of water thermal conductivity enhancement by adding nano-sized alumina particles

Operating fluids play an important role in heat transfer equipment. Water is inexpensive popular operating fluid with extensive applications, but its thermophysical properties are not good enough, especially for high temperature processes. Therefore, modification of its inherent characteristics by adding nano-sized solid particles found high popularities. Thermal conductivity is one of the most important thermophysical properties of an operating fluid in relatively all energy-based processes. Variation of thermal conductivity of nanofluids with different operating conditions is required to be understood in such processes. Therefore, the focus of this study is concentrated on modeling of thermal conductivity of water-alumina nanofluids using four different smart paradigms. Multilayer perceptron, radial basis function, cascade feedforward, and generalized regression neural networks are employed for the considered task. The best structure of these paradigms is determined, and then, their accuracies are compared using different statistical indices. Accuracy analyses confirmed that the generalized regression neural network outperforms other considered smart methodologies. It predicted more than 280 experimental datasets with excellent absolute average relative deviation?=?0.71%, mean square error?=?0.0006, root mean square error?=?0.023 and regression coefficient (R²)?=?0.9675. In the final stage, the proposed paradigm is used for investigation of the effect of influential parameters on the thermal conductivity of water-alumina nanofluids. This type of accurate and straightforward paradigm can broaden our insight about thermal behavior of homogeneous suspension of nano-size alumina particles in water.