Isobaric heat capacity and density of ethylene glycol based nanofluids containing various nitride nanoparticle types: An experimental study

Toward empirical correlations for estimating the specific heat capacity of nanofluids utilizing GRG, GP, GEP, and GMDH

When nanoparticles are dispersed and stabilized in a base-fluid, the resulting nanofluid undergoes considerable changes in its thermophysical properties, which can have a substantial influence on the performance of nanofluid-flow systems. With such necessity and importance, developing a set of mathematical correlations to identify these properties in various conditions can greatly eliminate costly and time-consuming experimental tests. Hence, the current study aims to develop innovative correlations for estimating the specific heat capacity of mono-nanofluids. The accurate estimation of this crucial property can result in the development of more efficient and effective thermal systems, such as heat exchangers, solar collectors, microchannel cooling systems, etc. In this regard, four powerful soft-computing techniques were considered, including Generalized Reduced Gradient (GRG), Genetic Programming (GP), Gene Expression Programming (GEP), and Group Method of Data Handling (GMDH). These techniques were implemented on 2084 experimental data-points, corresponding to ten different kinds of nanoparticles and six different kinds of base-fluids, collected from previous research sources. Eventually, four distinct correlations with high accuracy were provided, and their outputs were compared to three correlations that had previously been published by other researchers. These novel correlations are applicable to various oxide-based mono-nanofluids for a broad range of independent variable values. The superiority of newly developed correlations was proven through various statistical and graphical error analyses. The GMDH-based correlation revealed the best performance with an Average Absolute Percent Relative Error (AAPRE) of 2.4163% and a Coefficient of Determination (R2) of 0.9743. At last, a leverage statistical approach was employed to identify the GMDH technique's application domain and outlier data, and also, a sensitivity analysis was carried out to clarify the degree of dependence between input and output variables.

Water-Based Graphene Oxide-Silicon Hybrid Nanofluids-Experimental and Theoretical Approach

In the current paper, a new hybrid nanofluid based on graphene oxide sheets and silicon nanoparticles is proposed for thermal applications. GO sheets and Si nanoparticles with different mixture ratios are dispersed in distilled water. Dynamic viscosity is measured at temperatures within the range 20–50 °C and the values are compared to the results available in the literature. The results indicated that the viscosity increases with increasing the mixture ratio of graphene oxide. A new correlation for the dynamic viscosity based on the experimental findings is proposed. Finally, the criteria for the performance of new hybrid nanofluid for thermal applications are analyzed.

Recent Developments on the Thermal Properties, Stability and Applications of Nanofluids in Machining, Solar Energy and Biomedicine

In this review work, the recent progress made in the use of nanofluids (NFs) applied in three specific areas will be presented: machining, solar energy, and biomedical engineering. Within this context, the discussions will be guided by emphasizing the thermal and stability properties of these fluids. In machining, NFs play a prominent role in the processes of turning, milling, drilling, and grinding, being responsible for their optimization as well as improving the useful life of the tools and reducing costs. In the solar energy field, NFs have been used in the thermal management of the panels, controlling and homogenizing the operating temperature of these systems. In the biomedical area, the advantages of using NFs come from the treatment of cancer cells, the development of vaccines before the improvement of diagnostic imaging, and many others. In all lines of research mentioned in this study, the main parameters that have limited or encouraged the use of these fluids are also identified and debated. Finally, the discussions presented in this review will inspire and guide researchers in developing new techniques to improve the applications of NFs in several fields.

A Comprehensive Physical Profile for Aqueous Dispersions of Carbon Derivatives as Solar Working Fluids

The application of nanofluids in direct solar absorption, heat transfer or direct solar steam generation entails carrying out a comprehensive study taking into account several physical quantities. Long-term stability, rheological, thermophysical and optical properties of dispersions must be known to assess their potential for envisaged applications. Two low-concentration nanofluids, 0.005 and 0.05 wt%, of sulfonic acid-functionalized and polycarboxylate chemically modified graphene nanoplatelets in water were considered in this work. Elemental analyses of the nanopowders and pH evaluations of the colloids were carried out. The rheological behaviour of dispersions at different temperatures was studied by rotational rheometry. Thermal conductivities were measured by the transient hot wire method and densities by the oscillating U-tube technique. Additionally, a brief report of the optical properties was included to provide a comprehensive physical analysis.

Computational Study of Flow and Heat Transfer Characteristics of EG-Si3N4 Nanofluid in Laminar Flow in a Pipe in Forced Convection Regime

Laminar flow of ethylene glycol-based silicon nitride (EG-Si3N4) nanofluid in a smooth horizontal pipe subjected to forced heat convection with constant wall heat flux is computationally modeled and analyzed. Heat transfer is evaluated in terms of Nusselt number (Nu) and heat transfer coefficient for various volume fractions of Si3N4 nanoparticles in the base fluid and different laminar flow rates. The thermophysical properties of the EG-Si3N4 nanofluid are taken from a recently published experimental study. Computational modelling and simulation are performed using open-source software utilizing finite volume numerical methodology. The nanofluid exhibits non-Newtonian rheology and it is modelled as a homogeneous single-phase mixture, the properties of which are determined by the nanoparticle volume fraction. The existing features of the software to simulate single-phase flow are extended by implementing the energy transport coupled to the fluid flow and the interaction of the fluid flow with the surrounding pipe wall via the applied wall heat flux. In addition, the functional dependencies of the thermophysical properties of the nanofluid on the volume fraction of nanoparticles are implemented in the software, while the non-Newtonian rheological behavior of the nanofluid under consideration is also taken into account. The obtained results from the numerical simulations show very good predicting capabilities of the implemented computational model for the laminar flow coupled to the forced convection heat transfer. Moreover, the analysis of the computational results for the nanofluid reflects the increase of heat transfer of the EG-Si3N4 nanofluid in comparison to the EG for all the considered nanoparticle volume fractions and flow rates, indicating promising features of this nanofluid in heat transfer applications.

NePCM Based on Silver Dispersions in Poly(Ethylene Glycol) as a Stable Solution for Thermal Storage

The main objective of this study is to design and characterize silver suspensions based on poly(ethylene glycol) PEG400, Ag/PEG400, as energy storage media for low-temperature applications. A polyvinylpyrrolidone (PVP) treatment was applied to ~22 nm silver nanoparticles to ensure good stability in poly(ethylene glycol). An array of different experimental techniques was utilized to analyze the molecular mass and purity of base poly(ethylene glycol), morphology of dry PVP-capped Ag nanoparticles, hydrodynamic average size of dispersed Ag particles, as well as thermal stability of PEG400 and Ag/PEG400 dispersions. Samples exhibited good temporal stabilities with average hydrodynamic diameter around 50 nm according to dynamic light scattering analyses. Melting and solidification transitions were investigated in terms of temperature and enthalpy from differential scanning calorimeter (DSC) thermograms. The thermophysical characterization was completed with thermal conductivity (k), dynamic viscosity (η), isobaric heat capacity (Cp), density (ρ), and surface tension (σ) measurements of designed materials using a Hot Disk thermal conductivimeter, a rotational rheometer, a DSC calorimeter working with a quasi-isothermal modulated method, a U-tube densimeter and a drop shape analyzer, respectively. For a nanoparticle loading of only 1.1% in mass, sub-cooling reduced by 7.1% and thermal conductive improved by 3.9%, with almost no penalization in dynamic viscosity (less than 5.4% of increase). Maximum modifications in Cp, ρ, and σ were 0.9%, 2.2%, and 2.2%, respectively. Experimental results were compared with the values provided by using different theoretical or semi-empirical equations. In particular, good descriptions of dynamic viscosity as functions of temperature and nanoparticle volume concentration were obtained by using the Vogel-Fulcher-Tammann equation and a first-order polynomial η( ϕ v , n p ) correlation, with absolute average deviations of 2.2% and 0.55%, respectively.

Graphene IoNanofluids, Thermal and Structural Characterization

Graphene is considered a promising substance in applications related to the capture and reduction of the environmental impact of fluorinated gases. However, further research is still required to explore all related possibilities. In this work, the potential use in this context of nanofluids (NFs), obtained by dispersing graphene nanosheets in fluorinated ionic liquids (FILs) is investigated. As a starting step, a thermal and structural characterization for this type of IoNanofluids (IoNFs) is presented. The highly nanostructured nature of FILs has been recently demonstrated. The presence of fluorinated moieties is responsible for enhancing the accommodation of solutes such as small gases. The strong tendency to self-assemble forming continuous and supramolecular structures, and the versatility to rearrange in several conformational features allows the stabilization of nano colloidal systems. It is essential to perform a comprehensive study of their structural features to understand the behavior of this type of heterogeneous systems. Therefore, we present screening on the phase and structural behavior of these novel IoNFs to discover and develop optimized systems where FILs turn out to be advantageous. Thermogravimetric analysis (TGA) was employed to evaluate IoNFs mass losses with temperature, and their solid–fluid phase transitions were located using a differential scanning calorimeter (DSC). Their rheological properties were also determined through oscillatory experiments, obtaining the viscous and loss moduli. In addition, the structural percolation transition was also identified.

Development of a predictive model for estimating the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids using support vector regression

The specific heat capacity of nanofluids ( C P n f ) is a fundamental thermophysical property that measures the heat storage capacity of the nanofluids.C P n f is usually determined through experimental measurement. As it is known, experimental procedures are characterised with some complexities, which include, the challenge of preparing stable nanofluids and relatively long periods to conduct experiments. So far, two correlations have been developed to estimate theC P n f . The accuracies of these models are still subject to further improvement for many nanofluid compositions. This study presents a four-input support vector regression (SVR) model hybridized with a Bayesian algorithm to predict the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids. The bayesian algorithm was used to obtain the optimum SVR hyperparameters. 189 experimental data collected from published literature was used for the model development. The proposed model exhibits low average absolute relative deviation (AARD) and a high correlation coefficient (r) of 0.40 and 99.53 %, respectively. In addition, we analysed the accuracies of the existing analytical models on the considered nanofluid compositions. The model based on the thermal equilibrium between the nanoparticles and base fluid (model II) show good agreement with experimental results while the model based on simple mixing rule (model I) overestimated the specific heat capacity of the nanofluids. To further validate the superiority of the proposed technique over the existing analytical models, we compared various statistical errors for the three models. The AARD for the BSVR, model II, and model I are 0.40, 0.82 and 4.97, respectively. This clearly shows that the model developed has much better prediction accuracy than existing models in predicting the specific heat capacity of metallic oxides/ethylene glycol-based nanofluids. We believe the presented model will be important in the design of nanofluid-based applications due to its improved accuracy.

Fabrication and Characterization of Short Silicon Nitride Fibers from Direct Nitridation of Ferrosilicon in N₂ Atmosphere

Short silicon nitride fibers were fabricated by direct nitridation of ferrosilicon in N₂ atmosphere, and their structure and possible growth mechanism were characterized and investigated. The rod-like fibers which were α-Si₃N₄ with a low degree of crystallization and a high aspect ratio had a diameter of about 4 μm and a length close to a few millimeters. Belt-like fibers with a width about 5 μm and a thickness about 1 μm were also found in the nitrides. Scanning electron microscope (SEM), transmission electron microscope (TEM), high resolution transmission electron microscope (HRTEM), and selected area electron diffraction (SAED) investigations indicated that the fibers were single-crystalline α-Si₃N₄ with few amorphous distributed in the edge region, and the fibers grew by vapor–liquid–solid (VLS) mechanism.

Mechanical and Dielectric Properties of Two Types of Si₃N₄ Fibers Annealed at Elevated Temperatures

The mechanical and dielectric properties of two types of amorphous silicon nitride (Si₃N₄) fibers prior to and following annealing at 800 °C were studied. The tensile strengths of the Si₃N₄ fiber bundles were measured using unidirectional tensile experimentation at room temperature, whereas the permittivity values were measured at 8.2–12.4 GHz using the waveguide method. The results demonstrated that the tensile strength and dielectric properties of Si₃N₄ fibers were correlated to the corresponding composition, microstructure, and intrinsic performance of electrical resistance. The Si₃N₄ fibers with a lower content of amorphous SiN_xO_y presented an improved thermal stability, a higher tensile strength, a higher conductivity, and a significantly stable wave-transparent property. These were mainly attributed to the highly pure composition and decomposition of less amorphous SiN_xO_y.