Effect Of Nanoparticle Aggregation Research Articles

The nanoparticles aggregation aspects on the chemically reactive unsteady flow of alumina-water based nanofluid: A Keller box approach with applications of wavelet physics inspired neural networks

The present study explores the unsteady flow of a nanoliquid past a stretching cylinder with the consequence of heat source/sink and chemical reaction. Additionally, the effect of nanoparticle aggregation, convective boundary conditions, and magnetic field on the liquid flow is taken into consideration. Utilizing similarity variables, the modeled equations are transformed into dimensionless ordinary differential equations (ODEs). Further, the obtained ODEs are numerically solved by using the Keller box method. Moreover, the physics-informed neural network (PINN) is applied to analyze the flow, heat, and mass transport features. Graphical illustrations are used to display the influence of various parameters on the velocity, concentration, and temperature profiles for aggregation and without aggregation cases. As the value of the magnetic parameter increases, the temperature and concentration profile upsurge, but the reverse trend can be seen in the velocity profile. The concentration and temperature profiles rise as the unsteadiness parameter increases, but the velocity profile declines. The concentration, velocity, and temperature profiles are strengthened by an improvement in the curvature parameter value. The intensification in the values of the chemical reaction parameter declines the concentration.

Significance of nanoparticle aggregation for thermal transport over magnetized sensor surface

Abstract This article explores the dynamics of nanofluids consisting of copper (TiO2) nanoparticles suspended in water, as they interact with sensor surfaces between two parallel squeezing plates with porous characteristics. This research specifically targets applications involving enhanced heat transfer and magnetohydrodynamic (MHD) control in nanofluid systems. The primary aim is to analyze the effects of nanoparticle aggregation and non-aggregation on sensor surfaces, considering MHD formations and heat transfer in the energy and momentum equations. The research adopts a steady-state fluid condition and utilizes similarity transformations to convert partial differential equations into more manageable ordinary differential equations. The methodology involves shooting methods for solving these nonlinear ordinary differential equations and employs graphical analyses to study the impacts of various parameters such as permeability, magnetic influence, squeeze flow, and radiation on the temperature and velocity profiles of the nanofluid. The results reveal significant dependencies of temperature and velocity profiles on the studied parameters, illustrating varied behaviors in scenarios of both aggregation and non-aggregation of nanoparticles. The findings emphasize how each parameter distinctively influences the heat and flow characteristics of the nanofluid, offering insights into optimizing conditions for better performance and control in practical applications. Future research could focus on extending the model to include transient fluid states and exploring the effects of other nanoparticle materials and shapes. There is also potential to investigate the interactions under different environmental conditions and to incorporate more complex boundary conditions to simulate real-world applications more accurately. Further experimental validation of the theoretical predictions would be beneficial to enhance the reliability and applicability of the findings.

Aggregation of magnetized nanoparticles (TiO2-EG) across stretching disc with pollutant concentration

In recent years, there has been a growth in demand for improved heat transfer and control over the transportation of pollutants in complex systems. Understanding the interconnected effects of multiple aspects is critical for developing efficient techniques and ensuring ecological stability in disciplines such as environmental engineering, materials production, and nanostructures. Despite the significance of this finding, the current study investigates the combined effects of nanoparticle aggregation and non-aggregation on magnetohydrodynamics and pollutant concentration in the Bödewadt flow of a stretching disc. By applying suitable similarity criteria, the controlling partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs). The Runge-Kutta Fehlberg fourth and fifth-order technique is applied to solve these ODEs. Graphical representations of the numerical results are provided, and key engineering parameters are examined both with and without nanoparticle aggregation. The results indicate that the azimuthal velocity will be reduced by stretching and magnetic constraints while the concentration will be increased by induced pollutant concentration and external pollution source variation parameters. Moreover, compared to non-aggregated nanoparticles, aggregated nanoparticles show increased surface drag force and heat transmission rate.

Method of moments solution to ethylene glycol based [formula omitted] nanofluid flow through expanding/contracting rectangular channel

In this study, we present a comprehensive analysis of the laminar time-dependent magnetohydrodynamic (MHD) flow of ethylene glycol-based aluminum oxide nanofluid through a rectangular channel with contracting/expanding porous walls. We investigate the influence of aggregation/non-aggregation of nanoparticles, as well as the presence of thermal radiation. By imposing self-similarities in space and time, we obtain a system of nonlinear ordinary differential equations governing the flow. To solve these equations, we employ a well-known semi-analytical technique known as the Method of Moments (MoM). Additionally, we compare our results with the outcomes achieved through an application of another commonly utilized numerical approach (shooting technique with the Runge-Kutta-Fehlberg scheme). The comparison shows an excellent agreement that endorses the accuracy of the calculated solutions. The velocity and temperature profiles obtained from our analysis exhibit variations due to the changes in involved dimensionless parameters. We present these variations through graphical representations along with their explanations. Interestingly, our study reveals that the aggregation of nanoparticles influences the fluctuations caused by other parameters, and to some extent, suppresses them. Consequently, we observe less deviation among the velocity and temperature curves for the aggregation case compared to the non-aggregation case. These findings have significant implications in real-world engineering and industry. The understanding of the flow behavior of nanofluids through expanding/contracting rectangular channels can aid in the design and optimization of various engineering systems, such as heat exchangers and microfluidic devices. Additionally, our study provides valuable insights into the effects of nanoparticle aggregation and thermal radiation in such systems, offering opportunities for enhancing their efficiency and performance.

Numerical investigation of the effect of nanoparticle aggregation on the performance of concentrated photovoltaic-solar thermal collectors with spectral filtering

Solar energy, particularly solar thermal technology, has gained popularity as a possible long-term replacement to fossil fuels. The application of concentrated photovoltaic-solar thermal (CPV/T) collectors, which are improved by spectral filter fluids (SFF) and nanotechnology, has the potential to provide both higher thermal power for heating and cooling as well as improved electrical power generation. This work contributes new insight by quantifying the influence of nanoparticle agglomeration on collector performance and highlighting the challenges associated with the heterogeneous distribution of nanoparticles in CPV/T systems. The study employed coupled Eulerian multiphase modeling and discrete ordinate (DO) radiation modeling to examine slip velocity, nanoparticle diameter (including agglomeration), and suspension concentration. Population balance modeling (PBM) was utilized to determine the nanoparticle size distribution, and the obtained results were validated through comparison with experimental and numerical studies. When neglecting the effect of agglomeration and breakage of the non-solar participating media, the maximum error for this configuration was found to be 3.58% when compared to experimental work. From the solar participating study, in terms of electrical energy production, the best performance obtained was 16.64% with a volume fraction of 0.005% when considering agglomeration and breakage. It was also found that the Sauter diameter increases with volume fraction as the tendency for nanoparticle agglomeration increases. This study provides a broader view of the application of multiphase modeling in solar participating and non-solar participating media and, additionally, provides insight on the effect of various boundary conditions on the key system performance indicators. To extend this work, the flow Reynolds number can be increased in addition to varying the type of working fluid.

A molecular dynamics study of thermal conductivity and viscosity in colloidal suspensions: From well-dispersed nanoparticles to nanoparticle aggregates

This study investigates the microscopic transport behavior of nanofluids addressing some debatable points including the anomalous thermal conductivity (κ), against the predictions of classical effective medium theories. International Nanofluid Property Benchmark Exercise (INPBE) [J. Buongiorno et al., J. Appl. Phys. 106 (2009) 094312] has shown that no such anomaly found in well-dispersed nanofluids after conducting experiments for range of different types of nanofluids. However, a number of molecular dynamics based studies reported otherwise making inconsistent conclusion with INPBE. In this work, it is argued that the over predicted κ values reported in previous computational studies can be attributed to the ill-defined partial enthalpy formulation of the Green-Kubo method for multicomponent systems. Present study begins by addressing this issue via non-equilibrium molecular dynamics and shows that the results are in agreement with the conclusions of INPBE. Further, it is shown that the contribution of potential micro-mechanisms such as micro-convection due to Brownian motion, and the solid-like liquid layering are either absent or suppressed by the interface thermal resistance. The observed decreasing trend of viscosity enhancement to thermal conductivity enhancement ratio (Cη/Cκ) with increasing particle size indicates the improved heat transfer performance in nanofluids with larger nanoparticles. The effect of nanoparticle aggregation, the proposed originative mechanism of anomalous κ, is evaluated arranging nanoparticles as chain-like structures. A 67% improvement in κ is achieved with negligible viscosity variation. This rapidly reduces Cη/Cκ indicating better heat transfer performance with the presence of conductive paths due to the aggregation or in general extended nanostructures.

Finite element analysis of the impact of particles aggregation on the thermal conductivity of nanofluid under chemical reaction

A theoretical investigation is being conducted to determine the impact of nanoparticle aggregation (NPA) and thermal radiation on the radiant heat of nanofluids along with the vertical cylinder. An efficient thermal conductivity model for nanofluids is constructed based on the fractal distributive properties of nanoparticle aggregation. In view of two alternative methods of heat conduction, comprising particle aggregation and convection, the model is represented as a function of the fractal size and concentration. The contemporary models for nanofluid thermal conductivity include a significant role in nanoparticle aggregation. The impact of particle diffusion in the temperature field on aggregation and transport has yet to be investigated. The controlling boundary value problem is transformed into a system of nonlinear ordinary differential conditions, which are then solved numerically by utilizing the finite element technique with similarity transformations. The exceptional features of nanoparticles, such as high thermal conductivity, are highly significant in advancing nanotechnology, heat exchangers, material sciences, and electronics. The temperature field is observed higher in the presence of nanoparticle aggregation. The concentration gradient decreases the viscosity of water-based nanofluids, resulting in an increasing velocity. It is observed that the effect of nanoparticles aggregation on the boundary is descending by the including parameters causing an increment in heat transfer rate. The numerical approach to optimal meshing has reached convergence, and the accuracy of the presented results is supported by the fact that they are close to the results found in the relevant research.

Time-resolved laser-induced incandescence on metal nanoparticles: effect of nanoparticle aggregation and sintering

This work examines the excessive absorption and anomalous cooling phenomena reported in laser-induced incandescence measurements on metal nanoparticles by considering the effects of aggregate structure and sintering. Experimental investigations are conducted on iron and molybdenum aerosols, which have different melting points, and thus respond differently to the laser pulse. Although aggregation enhances the absorption cross-section of the nanoparticles and allows for higher peak temperatures, this enhancement does not fully explain the observed excessive absorption. Furthermore, as the aggregates of refractory metals such as molybdenum cool, they may sinter through gradual grain boundary diffusion; this change in structure alters their absorption cross-section, manifesting as a rapid drop in the pyrometric temperature, which could explain the anomalous cooling reported for this metal.

The crucial features of aggregation in TiO2-water nanofluid aligned of chemically comprising microorganisms: A FEM approach

The main objective of this investigation is to reveal the effects of nanoparticle aggregation aligned to thermal radiation with the prescribed heat flux. The Cattaneo–Christov heat flux (non-Fourier) and mass flux (non-Fick's) approaches in the optimized Buongiorno's model have been used to analyze the nanofluid magneto-transport mechanisms over the surface impacted by the gyrotactic behavior of microbe dispersion. The partial differentials are transformed into the set of nonlinear differential equations through boundary layer estimations and similarity substitutions, then computed by applying a variational finite element strategy. Researchers are looking into tiny nanoparticles because they have amazing properties, such as excellent thermal conduction, which are needed in advanced nanotechnology, heat exchangers, materials engineering, and technologies. The significance of this extensive study is to enhance the heat transition. Various aspects of the aggregation parameters on nanofluid velocity and temperature patterns are investigated and visually illustrated concerning the involved physical parameters. The effect of nanoparticle aggregation on the boundary is descending by the including parameters causes an increment in heat transfer rate. A significant correlation has been observed between the sets of results, which represents the accuracy of the finite element method used herein. The computations have been done by reducing the size of the mesh so that the numerical analysis can be used to ascertain convergence in the results.

Significance of nanoparticles aggregation on the dynamics of rotating nanofluid subject to gyrotactic microorganisms, and Lorentz force

The significance of nanoparticle aggregation, Lorentz and Coriolis forces on the dynamics of spinning silver nanofluid flow past a continuously stretched surface is prime significance in modern technology, material sciences, electronics, and heat exchangers. To improve nanoparticles stability, the gyrotactic microorganisms is consider to maintain the stability and avoid possible sedimentation. The goal of this report is to propose a model of nanoparticles aggregation characteristics, which is responsible to effectively state the nanofluid viscosity and thermal conductivity. The implementation of the similarity transforQ1m to a mathematical model relying on normal conservation principles yields a related set of partial differential equations. A well-known computational scheme the FEM is employed to resolve the partial equations implemented in MATLAB. It is seen that when the effect of nanoparticles aggregation is considered, the temperature distribution is enhanced because of aggregation, but the magnitude of velocities is lower. Thus, showing the significance impact of aggregates as well as demonstrating themselves as helpful theoretical tool in future bioengineering and industrial applications.

Core-shell SERS nanotags-based western blot

Western blot (WB) is the most commonly used scheme for protein identification in life science, but it still faces great challenges in the accurate quantitative detection of low-abundance proteins. Here, we proposed a novel surface-enhanced Raman scattering-based Western blot (SERS-WB) to solve this challenge. SERS nanotags were used as quantitative labels of proteins, which were composed of gold-silver core-shell nanoparticles, and Nile blue A (NBA) molecules were anchored on the interface of the core and shell. The results show that the SERS-WB possessed excellent sensitivity with detection limit of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) protein of 0.15 pg, as well as wide linear dynamic range (LDR) of 382 fg to 382 ng. In addition, the target protein on nitrocellulose (NC) membrane could be directly identified by colorimetric signal due to the aggregation effect of nanoparticles, which greatly simplifies the procedure. This as-proposed strategy will bring new thoughts to technological innovation of WB.

The effects of nanoparticle aggregation and radiation on the flow of nanofluid between the gap of a disk and cone

The heat transfer in three-dimensional coordinates is the main focus of the present article. The cone-disk (CND) apparatus is presumed to include a stationary cone (SCN) and a rotating disk (RTD), or counter-rotating, or both of them co-rotating, along with Titanium dioxide-ethylene glycol-based nanofluid. The accommodative impact of nanopaprticles aggregation and thermal radiation is considered in the modelling equations for the flow pattern available in the literature. The modelling equations are converted into ordinary differential equations (ODEs) using similarity transformations. The behaviour of flow profiles is readily understood by employing the Runge Kutta Fehlberg fourth fifth-order (RKF45) method and the shooting approach, which is strategized and explained using graphs. The outcomes reveal that the dynamics of flow with nanoparticles aggregation case shows better-quality heat transport for increased values of radiation parameter. Furthermore, the fluid flow with aggregation shows the developed heat transfer rate at cone surface for increased values of radiation parameter.

On-site detection of As(III) based on silver nanoparticles aggregation mediated by phosphates using surface-enhanced Raman scattering (SERS).

Aportable and simple method was developed for on-site selective determination of As(III) based on the SERS signal of As(III)-O vibration. The method relies on the synergistic effect of nanoparticles aggregation and analyte adsorption. Experimental results demonstrated that phosphate replaced the ligands of HH@Ag NPs, which in turn facilitated the adsorption of As(III) on the surface of HH@Ag NPs. The phosphate was introduced as an agglomerating agent to improve the detection ability of the method for As(III). The method shows good selectivity and linear relationship between 5 × 10-8 and 0.8 × 10-6 M, with the detection limit of 1.8 × 10-9 M. The method was appliedto actual water samples and successfully detected As(III), indicating that the method could have application potential in actual detection scenarios.

A molecular dynamics study on thermal conductivity enhancement mechanism of nanofluids – Effect of nanoparticle aggregation

Aggregation of nanoparticles is crucial in enhancing the thermal conductivity of nanofluids, but the underlying mechanism remains unclear so far. This paper used the non-equilibrium molecular dynamics (NEMD) simulation method to compare the thermal energy transfer characteristics of Ar-Cu nanofluids containing non-aggregated and aggregated nanoparticles. Simulations of thermal conductivity and its component calculations were performed to elucidate how the energy transport terms of molecular motions and intermolecular interactions are related to the nanoparticle aggregation state. The simulation results illustrated that the interaction between Ar atoms dominates the thermal conductivity, and its contribution increases with the volume fraction of nanoparticles, which is mainly caused by the solid-liquid interaction at the interface. The thermal conductivity of nanofluids is closely related to the aggregation morphology. Radial distribution function (RDF) analysis shows that when the nanoparticles change from a fully dispersed state to a compact aggregation state, the density of the nanolayer near the nanoparticles decreases, thus reducing the contribution of Ar-Ar interaction to heat transfer. Nanoparticle aggregates with chain-like structures maximize the thermal conductivity of the nanofluids due to the increased interaction between the copper atoms providing a more efficient heat transfer. Our results will provide essential insights into understanding the effects of nanoparticle aggregation on the microscopic heat transfer of nanofluids.

Modelling Thermal Conduction in Nanoparticle Aggregates in the Presence of Surfactants.

Many theoretical and experimental studies have shown that the addition of nanoparticles into conventional fluids may generate nanofluids with significantly improved heat transfer properties. In the present work, the effect of nanoparticle aggregation on the thermal conductivity of nanofluids is studied, considering also the effect of surfactants that are typically added to stabilise the nanofluid. A method for simulating aggregate formation is developed here that allows tailoring of the fractal dimension and the number density of the nanoparticles to desired values. The method is shown to be computationally simple and fast. Data that are extracted from electron microscope images are compared with simulation results regarding surface porosity and the autocorrelation function. The surfactants are modelled as a layer around the particles, and the effective thermal conductivity is calculated with a meshless numerical technique. Significant increase in conductivity is observed for small values of the fractal dimension and for large number density of particles in the aggregate. The simulations are in good agreement with experimental results. It is also concluded that prediction of the conductivity of such nanofluids requires the knowledge of the type and the amount of the surfactant added.

Thermal Enhancement of Radiating Magneto-Nanoliquid with Nanoparticles Aggregation and Joule Heating: A Three-Dimensional Flow

This article studies the effect of nanoparticle aggregation on the 3D flow of titanium nanoliquid based on ethylene glycol $$ ( {\text{C}}_{ 2} {\text{H}}_{ 6} {\text{O}}_{2} - {\text{TiO}}_{2} ) $$ due to an exponentially elongated surface. Thermal analysis is carried out considering linear thermal radiation, Joule heating, and mechanisms of the heat source/sink, while the aspect of the homogeneous single-order chemical reaction is included in the analysis of the solute. The variable magnetic field is also accounted. The modified Maxwell model (Maxwell–Bruggeman) is implemented to estimate the effective conductivity of the nanoliquid. The displayed equations are moderated in quantities without dimensions. The 2-point nonlinear boundary value problem (BVP) is solved by the shooting procedure. The importance of effective parameters is described through graphs. Numerical data are presented to study the friction factor, the heat transfer rate, and the mass transfer rate. It has been established that the aggregation of nanoparticles significantly improves the thermal field. Furthermore, the effect of magnetism is more in ordinary fluid than in nanofluid.

Effect of nanoparticle aggregation on the thermal radiation properties of nanofluids: an experimental and theoretical study

Nanofluids show significant enhancement in the absorption of solar energy. However, little work has been done on the effect of nanoparticle aggregation on the thermal radiation properties of nanofluids up to now. In this work, we systematically investigate the thermal radiation properties of nanofluids with nanoparticle aggregation from experiment and theory. On the experimental side, titanium dioxide/silver (TiO2@Ag) plasmonic nanofluids are prepared in distilled water and the spectral transmittance of nanofluids with different degrees of aggregation is measured. The result shows that the size of aggregated nanoparticle cluster has a significant effect on the absorption of nanofluids. On the theoretical side, a theoretical model is developed to calculate the thermal radiation properties of nanofluids with nanoparticle aggregation. By applying the multiple sphere T-matrix (MSTM) method and the Monte Carlo (MC) method, we investigate the effects of nanoparticle aggregation, cluster fractal dimensions and cluster sizes on the thermal radiation properties of nanofluids. The results indicate that our theoretical model can predict the thermal radiation properties of nanofluids with nanoparticle aggregation more reasonably. This is of great significance to understand the mechanism that affects the thermal radiation properties of nanofluids and to actively design nanofluids.

Sensitivity analysis of Marangoni convection in TiO2–EG nanoliquid with nanoparticle aggregation and temperature-dependent surface tension

The sensitivity analysis of the magnetohydrodynamic thermal Marangoni convection of ethylene glycol (EG)-based titania (TiO2) nanoliquid is carried out by considering the effect of nanoparticle aggregation. The rate of heat transfer is explored by utilizing response surface methodology and estimating the sensitivity of the heat transfer rate toward the effective parameters: radiation parameter (1 ≤ R ≤ 3), magnetic parameter (1 ≤ M ≤ 3) and nanoparticle volume fraction $$(1\% \le \phi \le 5\%$$ ). The heat transfer phenomenon is scrutinized with thermal radiation and variable temperature at the surface. The effective thermal conductivity and viscosity with aggregation are modeled by using the Maxwell–Bruggeman and Krieger–Dougherty models. The governing equations are solved by using the apposite similarity transformations. It is found that when the effect of aggregation is considered, the velocity profile is lower. A positive sensitivity of the Nusselt number toward thermal radiation is observed. Further, a negative sensitivity of the heat transfer rate is observed toward the magnetic field and nanoparticle volume fraction.

CFD simulation of nanofluid heat transfer considering the aggregation of nanoparticles in population balance model

The effect of nanoparticles aggregation on the heat transfer coefficient in a heat dissipation process of a circular tube is evaluated through computational fluid dynamics (CFD) technique, and the simulation results are compared to experimental data. The experimental data of MgO/CuO/Al2O3 water-based nanofluids which were obtained in our previous study under turbulent flow regime and Reynolds numbers ranging from 11,000 to 47,000 are used to validate the CFD results. Two-phase mixture and k-e RNG turbulence models are coupled with the population balance model (PBM) to consider the impact of nanoparticles aggregation in the flow domain using the commercial CFD software ANSYS Fluent 17.2. The particle size distribution (PSD) determined by conducting dynamic light scattering (DLS) analysis for nanoparticle concentrations of 0.02, 0.05, 0.07 and 0.09%v. is fed to solve the governing equations. The CFD model with aggregation results is in very good agreement with the experimental data, and the maximum relative absolute average deviation (RAAD) from the experiments is about 7.5%, while the CFD model without aggregation leads to less accurate results with maximum 17.56% deviation compared to experimental data. The consideration of the aggregation effect with accurate PSD data enhances the CFD simulation and makes its outcomes more reliable.

Aggregation Behavior of Nanoparticle-Peptide Systems Affects Autophagy.

The aggregation of nanoparticle colloidal dispersions in complex biological environments changes the nanoparticle properties, such as size and surface area, thus affecting the interaction of nanoparticles at the interface with cellular components and systems. We investigated the effect of nanoparticle aggregation on autophagy, the main catabolic pathway that mediates degradation of nanosized materials and that is activated in response to internalization of foreign nanosized materials. We used carboxylated polystyrene nanoparticles (100 nm) and altered the nanoparticle aggregation behavior through addition of a multidomain peptide, thus generating a set of nanoparticle-peptide mixtures with variable aggregation properties. Specifically, modulating the peptide concentration resulted in nanoparticle-peptide mixtures that are well dispersed extracellularly but aggregate upon cellular internalization. We monitored the effect of internalization of nanoparticle-peptide mixtures on a comprehensive set of markers of the autophagy pathway, ranging from transcriptional regulation to clearance of autophagic substrates. The nanoparticle-peptide mixtures were found to activate the transcription factor EB, a master regulator of autophagy and lysosomal biogenesis. We also found that intracellular aggregation of nanoparticle colloidal dispersions causes blockage of autophagic flux. This study provides important insights on the effect of the aggregation properties of nanoparticles on cells and, particularly, on the main homeostatic pathway activated in response to nanoparticle internalization. These results also point to the need to control the colloidal stability of nanoparticle systems for a variety of biomedical applications.