Nanoparticle Mass Research Articles

Experimental investigation of thermal energy storage in shell-and-multi-tube unit with nano-enhanced phase change material

This paper deals with thermal energy storage with use of nanoparticle enhanced phase change material in shell-and-multitube unit. The experiments are conducted under atmospheric pressure. Paraffin wax and two different fatty acids are used as base phase change material. Graphite and multi-walled carbon nanotubes serve as nanoparticles. Graphite nanoparticles are tested at the concentrations of 0.1 %, 1 % and 5 % by weight, while multi-walled carbon nanotubes only at 0.1 %wt. Ultrasonic vibration and homogenizer are used in order to stabilize the dispersion of the nanoparticles. Polyvinylpyrrolidone surfactant is used to stabilize the suspension and the tested nano-enhanced phase change material exhibit satisfactory stability. Experimental measurements are performed for a bundle of 7 tubes with outside diameter of 6 mm in a staggered arrangement and a pitch ratio of 4.5. It is found that, regardless of the tested base phase change material, the addition of graphite nanoparticles with mass concentration of 0.1 % does not significantly affect the charging and discharging times compared to base phase change material. The differences in charging and discharging times did not exceed 11 %. For a graphite nanoparticles mass concentration of 5 %, an increase in the charging time by up to 21 % and a reduction in the discharging time by 24 % was observed, depending on the type of base phase change material. An addition of multi-walled carbon nanotubes with mass concentration of 0.1 % shows an increase in charging time regardless of the type base phase change material up to 144 % with negligible influence on the discharging time. It was also observed that adding a surfactant to the produced nano-enhanced phase change material results in a reduction in charging time by up to 83 % depending on the type of base phase change material.

Enhanced Biocidal Activity of Heterophase Zinc Oxide/Silver Nanoparticles Contained within Painted Surfaces

Today, one of the biggest challenges is infections in the painted walls of hospitals. Acrylic-based paints are a target of antibiotic-resistant microorganisms since they contain cellulosic compounds as thickeners. The aim of this study was to synthesize and investigate the biocidal activity and toxicity of heterophase ZnO-Ag nanoparticles fixed in water-based acrylic paint layers in reference to a nontreated water-based paint. The ZnO-Ag nanoparticles with average particle sizes of about 80 nm were simply obtained by electrical explosion of two twisted wires in an oxygen-containing atmosphere. The nanoparticles and modified paint were characterized using SEM, TEM, XPS, and XRD techniques. The antimicrobial activity of the nanoparticles and modified paint layers was tested against P. aeruginosa, S. aureus, MRSA, E. coli bacteria, and C. albicans using ISO 22196. The antiviral activity against smallpox virus was tested according to ISO 21702. Flow cytometry tests were used to investigate the toxicity of the modified paint coating. As-synthesized nanoparticles had “Janus-like” morphology, with a clear interface inside the nanoparticle. Nanoparticles had enhanced antibacterial activity, which is based on the nanoparticle photocatalytic activity in water decomposition and reactive oxygen species generation. The paint coating with a ZnO-Ag nanoparticle mass ratio of 1.0 wt.% displayed significant antibacterial activity (more than a 99% reduction) and 100% antifungal activity. In addition, this coating inactivates >99% of the virus after 2 h of contact relative to a nontreated control paint. The paint coating showed low toxicity against the sensitive 3T3 fibroblast cell line. More than 90% cell viability was observed after 24 h of incubation with the sample extract. Therefore, heterophase ZnO-Ag nanoparticles have high biocidal activity and low toxicity use and can be applied to other commercial water-based paints to improve their performance against pathogens.

Nanostructured Pd/Ag/Ni electrocatalysts for the Hydrogen Evolution Reaction

As palladium is the one of the most effective electrocatalyst for the hydrogen evolution reaction, it is crucial the development of new catalysts that require small amounts of palladium to perform, but that are highly active. In this work, the electrochemical characterization of a novel electrode with low palladium content is reported, where Pd nanoparticles are supported on macroporous nickel electrodes that contain silver nanoparticles previously electrodeposited on the surface, which after heat-treatment become rich in corners and edges. The values of η100 (overpotential needed to produce a fixed amount of hydrogen) and jm (indicative of catalytic activity per unit mass of metal nanoparticles) improved (for example, at 80 °C, a η100 of 109.9 mV and a jm of 12587 A·g−1) those of other authors who applied bimetallic AgPd nanoparticles for the HER, showing that the incorporation of nanostructures (Pd over Ag) significantly reduced the energy investment required to produce hydrogen due to synergistic effects between the deposited Pd particles and the electrodeposited silver, enhancing the catalytic activity.

Darcy-Forchheimer flow of Ag–ZnO–CoFe2O4/H2O Casson ternary hybrid nanofluid induced by a rotatory disk with EMHD

This study comprehensively inspects the steady, three-dimensional electromagnetohydrodynamics Darcy-Forchheimer slip flow upon a Casson ternary hybrid nanofluid through a porous rotatory disk. The study plunges into the repercussions of key factors namely thermophoresis, chemical reaction, viscous dissipation, Brownian movement, thermal radiation, and activation energy attributes of the ternary hybrid nanofluid. The current endeavour is inspired by the flourishing requirement in several energy-related and industrial applications. A mathematical configuration is formed to express the fluid flow system and heat and nanoparticle mass transpiration processes. Then partial differential equations administrating our mathematical model, are reformed into ordinary differential equations with the assistance of specific similarity conversions and eventually interpreted numerically using the noteworthy bvp4c scheme. The consequences of discrete flow factors upon temperature, concentration, and velocity profiles and Nusselt number, skin friction’s coefficient, and Sherwood number are investigated. The achieved outcomes disclose the electric parameter aids in upgrading the tangential velocity and temperature profiles. The outcomes reveal that for Casson ternary hybrid nanofluid, the heat and mass transpiration rates elevate by 19.23% and 51.28%, respectively, compared to Casson nanofluid whereas skin friction coefficient is retrogressed by approximately 8.96% for Casson ternary hybrid nanofluid compared to ternary hybrid nanofluid.

Ultrafine industrial aerosol as a risk factor for the health of smelting shop workers at a machine-building enterprise

Aim. To evaluate the amount and physicochemical properties of ultrafine industrial aerosol (UIA) in the work zone air (WZA) of smelting shop workers at a machine-building enterprise during various technological processes (melting, welding, and metal machining). Materials and methods. The physical properties of UIA particles were evaluated with NanoScan 3910 scanning spectrometer: the number of particles (number/cm3), particle surface volume (nm3/cm3), particle surface area (nm2/cm2), and nanoparticle mass concentration (μg/cm3) in the WZA of a furnace operator (n = 416), a welder (n = 315), a cutter (n = 286), a grinder (n = 78), and workers of the control group (n = 315). The chemical composition of the air samples was determined by inductively coupled plasma optical emission spectrometry (ICP-OES) using an Optima 2100 DV device. Results. It has been found that the highest concentration of UIA nanoparticles was recorded during metal melting at the workplaces (WP) of furnace operators (4.28 × 104 to 2.41 × 105 particles/cm3) and welders (3.01 × 104 to 3.34 × 105 particles/cm3). During mechanical metal processing, a much smaller number of nanoparticles was produced (for grinders, the number varied from 9.81 × 104 to 1.44 × 105 particles/cm3; for cutters, it varied from 2.71 × 104 to 1.94 × 105 particles/cm3). Indicators of surface area, surface volume and mass concentration at the WPs of furnace operators, welders, grinders and cutters exceeded the corresponding indicators of the control group for almost all sizes of suspended particles with statistically significant differences (p ≤ 0.05). It has been estimated that such metals as Al, Cu, Mg, Mo, Fe, and Ni were present in the workers’ WZA but their content did not exceed the current maximum permissible concentrations. Conclusions. The presence of suspended particles of UIA with a maximum concentration in the range from 20 nm to 70 nm has been confirmed in the WZA during melting, welding of metals and machining. Indicators of concentration, surface area, surface volume, and mass concentration at the workplaces of melting shop workers at the machine-building enterprise significantly exceeded the corresponding indicators in the control group without dust formation processes, showing statistically significant differences (p ≤ 0.05). The evidence of metals in the WZA has suggested their presence in the form of nanoparticles, which are more active and dangerous, thus increasing the risk of their adverse effects on the workers. Ультрадисперсний

Molecular dynamics simulation of heat, mass and phonon transport performances of nanoparticle enhanced Na2SO4·10H2O

Nanoparticles are widely used to prepare nanocomposite phase change materials for higher thermal conductivity (TC). To elucidate the enhancing mechanism of Cu nanoparticles in salt hydrate phase change materials, molecular dynamics simulations are employed to investigate the TC, diffusion coefficient, especially the phonon density of states (PDOS) of pure SSD (sodium sulfate decahydrate) and NSSD (nanoparticle-enhanced SSD). Due to the complex structure of SSD - consisting of two types of ions and water molecules, not only the PDOS of the whole system, but also the PDOS of each component in SSD are separately calculated to reveal the internal phonon transport relationships. The results show that, compared with the pure SSD, the TC of NSSD with 5.94–24.57 wt% Cu nanoparticles increases by 8.19% to 28.73%, while the mass transfer rate decreases by 31.60% to 69.86% due to the increase of the distances between atoms. Furthermore, dispersed Cu nanoparticles may lead to a decrease in TC by 2.64–4.91% by comparison with the single Cu nanoparticle. Prominently, Cu nanoparticles can not only centralize the PDOS of components, but also increase the proportion of PDOS in low frequency for components; meanwhile, the average phonon resonances of Na+/SO42−, SO42−/H2O and Na+/H2O are promoted by 5.1%, 15.2%, and 26.0%, respectively. It is suggested that the reduction of phonon scattering as well as enhancing phonon resonance between different components is an important mechanism for increasing TC. Moreover, the addition of Cu nanoparticles will reduce the Debye temperature of the system. This work reveals the variation mode of phonon distributions in the SSD lattice caused by the addition of Cu nanoparticles, which helps to understand the relationship between nanoparticle-enhanced heat transfer and phonon transport in salt hydrate PCMs.

Single particle inductively coupled plasma mass spectrometry and its variations for the analysis of nanoparticles.

Single particle inductively coupled plasma mass spectrometry (spICPMS) can count and weigh metal-containing nanoparticles (NPs), enabling their sizing if their geometry, density, and composition are known. With a nebulizer and a spray chamber for sample introduction, both the sample uptake rate and the transport efficiency must be determined when calibrating with solutions. In contrast, flow injection (FI) and mono-segmented flow analysis (MSFA) coupled to spICPMS do not need determination of the transport efficiency and sample uptake rate for accurate NP mass measurement. Correcting for the significant settling time on some instruments is also discussed, as well as calibration through signal integration instead of averaging, which eliminates the need to measure the transport efficiency when seeking NP mass. Nitrogen added to the outer plasma gas can reduce the background for the determination of P, S, Ca and Fe. Infrared heating of the sample introduction system provides 100% transport efficiency, enabling accurate particle mass and concentration measurements without measurement of transport efficiency.

Numerical study using hybrid nanofluid to control heat and mass transfer in a porous media: Application to drying of building bricks

This paper?s main objective is to perform a numerical analysis of the heat and mass transfer that occurs during the mixed convective drying of porous walls containing hybrid nanofluid. The porous wall, used to dry the brick, is positioned in a vertical channel and has three different phases: a solid phase, a hybrid nanofluid phase, and a gas phase. In order to accomplish this, we created a 2-D code using COMSOL Multiphysics to resolve the equations relating mass, momentum, species, and energy. The impact of various parameters, including ambient temperature, initial hybrid nanofluid saturation, and nanoparticle volume percent, on heat and mass transmission was examined after this numerical code?s validity. As the volume percentage of nanoparticles rises, it is discovered that the temperature of the porous medium is significantly lowered. The heat and mass transfer of the water-Al2O3-MgO hybrid nanofluid has been discovered to be much less than that of pure water and the water-Al2O3-SiO2. As the ambient temperature rises, it takes less time for the second phase to dry.

Assessment of urine sample collection and processing variables for extracellular vesicle-based proteomics.

Extracellular vesicles (EVs) in urine are a promising source for developing non-invasive biomarkers. However, urine concentration and content are highly variable and dynamic, and actual urine collection and handling often is nonideal. Furthermore, patients such as those with prostate diseases have challenges in sample collection due to difficulties in holding urine at designated time points. Here, we simulated the actual situation of clinical sample collection to examine the stability of EVs in urine under different circumstances, including urine collection time and temporary storage temperature, as well as daily urine sampling under different diet conditions. EVs were isolated using functionalized EVtrap magnetic beads and characterized by nanoparticle tracking analysis (NTA), western blotting, electron microscopy, and mass spectrometry (MS). EVs in urine remained relatively stable during temporary storage for 6 hours at room temperature and for 12 hours at 4 °C, while significant fluctuations were observed in EV amounts from urine samples collected at different time points from the same individuals, especially under certain diets. Sample normalization with creatinine reduced the coefficient of variation (CV) values among EV samples from 17% to approximately 6% and facilitated downstream MS analyses. Finally, based on the results, we applied them to evaluate potential biomarker panels in prostate cancer by data-independent acquisition (DIA) MS, presenting the recommendation that can facilitate biomarker discovery with nonideal handling conditions.

Micro-ballistic response of thin film polymer grafted nanoparticle monolayers.

Self-assembled polymer grafted nanoparticles (PGNs) are of great interest for their potential to enhance mechanical properties compared to neat polymers and nanocomposites. Apart from volume fraction of nanoparticles, recent experiments have suggested that nanoscale phenomena such as nanoconfinement of grafted chains, altered dynamics and relaxation behavior at the segmental and colloidal scales, and cohesive energy between neighboring coronas are important factors that influence mechanical and rheological properties. How these factors influence the mechanics of thin films subject to micro-ballistic impact remains to be fully understood. Here we examine the micro-ballistic impact resistance of PGN thin films with polymethyl methacrylate (PMMA) grafts using coarse-grained molecular dynamics simulations. The grafted chain length and nanoparticle core densities are systematically varied to understand the influences of interparticle spacing, cohesion, and momentum transfer effects under high-velocity impact. Our findings show that the inter-PGN cohesive energy density (γPGN) is an important parameter for energy absorption. Cohesion energy density is low for short grafts but quickly saturates around entanglement length as adjacent coronas interpenetrate fully. The response of γPGN positively influences specific penetration energy, , which peaks before chain entanglement starts (<Ne). We further divide the ballistic response into three regimes based on grafted chain length: short graft, intermediate graft, and entangled graft. The short grafted PGNs show fragmentation due to almost no cohesion between particles, and the rigid body motion of the nanoparticles absorbs most of the energy. When chains are in the intermediate graft length regime, the film fails by chain pull-out, and unraveling of grafts is the primary dissipation mechanism. The Ashby plot of penetration energy, Ep, indicates ballistic processes are inelastic collisions when grafted chains are short and vary with density in a power law fashion as expected from momentum transfer. The response indicates that a lower nanoparticle weight fraction, ϕwtNP, leads to higher energy absorption per mass, that is, the added mass of nanoparticles does not warrant proportionate increases in energy absorption in the parametric range studied. However, the peak deceleration, Ab, shows a clear positive effect of adding NPs. Finally, PGNs with intermediate chain lengths simultaneously show relatively higher and Ab.

Entropy generation analysis for convective flow of aqua Ag-CuO hybrid nanofluid adjacent to a warmed down-pointing rotating vertical cone

PurposeThis paper aims to study numerically the flow, heat transfer, and entropy generation of aqueous copper oxide-silver hybrid nanofluid over a down-pointing rotating vertical cone, with linear surface temperature (LST) and linear surface heat flux (LSHF), in the presence of a cross-magnetic field. In industrial applications, such as oil and gas plants, food industries, steel factories and nuclear packages, the real bodies may contain nonorthogonal walls and variable cross-section three-dimensional forms which this issue can clarify the importance of selective geometry in the present research.Design/methodology/approachThe mass-based scheme is accomplished for the simulation, and the entropy generation and Bejan number will be analyzed in conjunction with the aforementioned model. It has been hypothesized that two types of boundary conditions (LST and LSHF) as well as five nanoparticle shapes (sphere, brick, cylinder, platelet and disk) present a collection of crucial results. The overseeing PDEs are changed over completely to the dimensionless ODEs, and these are solved by Runge–Kutta–Fehlberg approach combined with a shooting methodology for certain values of physical parameters.FindingsSubsequent to the fantastic compromise of the computational outcomes with past reports, the outcomes are introduced to conduct the investigation of the hydrodynamics/thermal boundary layers, the skin friction and the Nusselt number, as well as entropy generation and Bejan number. A state of hybrid nanofluid, which exhibits a remarkable increase in heat transfer in comparison to the states of mono-nanofluid and regular fluid, has been found to have the highest Nusselt number; however, the skin friction values should always be taken into account and managed. The entropy generation improves with the mass of the second nanoparticle (silver), while the opposite pattern is exhibited for the Bejan number. Furthermore, the lowest value of entropy generation number belongs to the cylindrical shape of nanoparticles in the LST case. In final, a significant accomplishment of the current study is the accurate output of the mass-based scheme for an entropy analysis problem.Originality/valueTo the best of the authors’ knowledge, for the first time, in this study, a new development of natural convective flow of a hybrid nanofluid about the warmed (LST and LSHF) and down-pointing rotating vertical cone by the mass-based algorithm has been presented. The applied methodology considers the masses of base fluid (water) and nanoparticles (Ag and CuO) as an alternative to the first and second nanoparticles volume fraction. Indeed, the combination use of the Tiwari–Das nanofluid model and the mass-based hybridity algorithm for the entropy generation analysis can be the main novelty of this work.

Optimization of the Photodegradation of Metoclopramide Drug using Super Nanoparticles in Aqueous Solutions

In the present research carry out to remove pharmaceutical pollutants as a model metoclopramide (MCP) drug from an aqueous medium utilizing a photocatalytic degradation method with super nanoparticles called TiO2 nanoparticles (NP). synthesis of TiO2 nanoparticles by utilizing the hydrothermal processes. The physical characterizations of materials by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis (TGA), and transmission electron microscope (TEM). The results showed that the efficiency of the TiO2 nanoparticle increased by 88.88%. It also showed that the photocatalytic degradation rate increased with decreasing concentration of MCP drug increasing the intensity of the light led to an increase in the rate of photocatalytic degradation. Study effect of several factors, concentration on the drug, mass of nanoparticle, light intensity that the best conditions for the photocatalytic degradation of 0.3 g of the nanocomposite, MCP drug concentration of 50 m/L, pH solution 8, and light intensity 1.7 mW/Cm2, Thus, the photocatalytic degradation increased with decreasing the concentration of MCP drug. The obtained TiO2 nanoparticle exhibits best photocatalytic degradation than the commercial photo-catalysts TiO2 NPs. Finally, it is essential to evaluate the recycled photocatalytic degradation efficiency, which is one of the utmost significant factors towards photodegradation.

Homogeneous-heterogeneous reactions on Darcy-Forchheimer nanofluid flow system

The use of artificial neural networks (ANNs) to solve complex fluid dynamics problems has revolutionized computational approaches. This article explores novel ANN solutions for fluid problems. ANNs have demonstrated unmatched effectiveness in comprehending and forecasting fluidic behaviors, from mimicking complex fluid flow trends to optimizing structures for dynamics. This study emphasizes the significance of neural networks in revolutionizing our understanding and control of fluidic systems by using ANNs and Bayesian Regularization. This study examined the 3D Darcy-Forchheimer stretching flow (TDDFSF) of nanofluid under convective conditions along with homogeneous and heterogeneous reactions by employing the scheme of Bayesian Regularization with the procedure of backpropagation in neural networks (SBR-BNNs). The flow is influenced by Brownian diffusion, thermophoresis and zero nanoparticles mass flux condition. The PDEs given in this model are converted into nonlinear ODEs. Results from MSE, regression analysis, and error histogram are used to verify the performance of SBR-BNNs. The absolute errors lie in the ranges up to 10−9, which depict the worth of the solver SBR-BNNs. The absolute error measures the discrepancy between the values actually observed and those predicted by the SBR-BNNs model. SBR-BNNs' high precision in TDDFSF models can lead to more effective and reliable solutions.

Investigation on the Effects of Nanorefrigerants in a Combined Cycle of Ejector Refrigeration Cycle and Kalina Cycle

Abstract The main objective of this study is to carry out the thermodynamic analysis of a new power/refrigeration combined cycle which consists of an ejector refrigeration cycle (ERC) and a Kalina cycle. In ERC, nanorefrigerants are used as the working fluid. Used nanorefrigerants are homogenous mixtures of different base refrigerants (R134a, R152a, and R290) and nanoparticles (TiO2 and Al2O3) with 0–5 wt% nanoparticle concentration. The effects of variation in system operational parameters (nanoparticle mass fraction, evaporator pressure, condenser pressure) on energy efficiency and exergy efficiency of the combined cycle are reported. Additionally, net power production, refrigeration capacity, heat input to the combined cycle, and their exergy contents are given for the case of TiO2/R290 nanorefrigerant use in ERC. This study is the first ERC analysis in which the effect of R152a and R290 base refrigerants and TiO2 nanoparticle use on ERC performance is investigated. The results show that as the nanoparticle concentration and evaporator pressure increase and condenser pressure decreases, the energy and exergy efficiencies of the cycle increase. Under all the considered operational conditions of the combined cycle, the highest efficiency results are obtained for R290 and the lowest for R134a-based refrigerants.

Heterogeneity of nanoparticle deposition micro-structure and modeling deposition layer thickness variation underneath periodically growing single boiling bubbles in nanofluids

Nanoparticle deposition in nanofluid boiling can significantly impact heat transfer efficiency. However, there is still much to be uncovered regarding the heterogeneity of micro-structures in nanoparticle deposition and how to quantitatively model variations in deposition layer thickness. To gain a deeper understanding, we conducted experiments where single boiling bubbles were grown from an artificial micro-cavity in SiO2 nanofluids with varying concentrations and durations under a constant heat flux. Our results reveal that the nanoparticle deposition region increases with concentration and boiling duration. Notably, while the deposition morphology is irregular near the bubble nucleation site, it becomes more uniform further away from the bubble nucleation site. We believe that the heterogeneity in the micro-structure of the deposition layer is due to differences in the evaporation time of the liquid microlayer at different positions, variations in its thickness beneath a single boiling bubble, and dependency of nanoparticles Brownian motion on temperature. Additionally, the thickness of the deposition layer decreases as the distance from the nucleation site increases. To accurately describe this variation in thickness, we have proposed a semi-empirical correlation based on the liquid microlayer evaporation theory and the conservation of mass of nanoparticles beneath a single boiling bubble. The thickness of the nanoparticle deposition layer is determined by the number of growing bubbles, liquid density, initial thickness of the liquid microlayer, local nanoparticle concentration, and local nanoparticle stacking density. This study provides valuable insights into optimizing micro-structures or thickness of the deposition layer, leading to improved nanofluid boiling heat transfer.

A facile method to determine the molar mass of soft nanoparticles

The determination of the molar mass of soft nanoparticles is essential to estimate their (molar) concentration in dispersions. Measuring this quantity by conventional methods, however, often proves challenging. We describe a facile approach to determine the molar mass of (soft) nanoparticles via counting their number per volume using a widefield fluorescence microscope. The method is exemplified on a microgel dispersion as a model system, while it is applicable to other types of stainable nanoparticles. For this, covalent labeling or modification of the nanoparticles is not required. The dispersion is simply mixed with a Nile Red solution in a defined ratio and measured in an optical fluorescence microscope accessible to most researchers in the field.

Upgrading interferometric scattering microscopy with ensemble statistical analysis

AbstractInterferometric scattering (iSCAT) microscopy, label‐free high‐speed (up to ~1000 frames per second) imaging and tracking technique, has proven to be a versatile tool by measuring the mass and 3D position of nanoparticles and biomolecules as well as visualizing real‐time dynamics of nanoscale events in complex cellular environments. However, the quantification of iSCAT signals has not been straightforwardly defined in practical terms. We delve into several issues associated with signal processing in iSCAT: error‐prone post‐processing routine and lack of statistical reliability in the convention of iSCAT contrast. After providing a brief account of concepts and principles of correlation spectroscopy, we here discuss an alternative ensemble (higher number density of scatterers) statistical analysis that can be used to extract the dynamic information of scattering particles from fluctuating iSCAT signals. Finally, our perspective on the correlation approach toward time‐correlated iSCAT technique will be presented.

Exploring Quantum Dots Size Impact at Phase Diagram and Electrooptical Properties in 8CB Liquid Crystal Soft-Nanocomposites.

We explore the influence of functionalized core-shell CdSe/ZnS quantum dots on the properties of the host liquid crystal compound 4-cyano-4'-octylbiphenyl (8CB) through electrooptical measurements. Two different diameters of quantum dots are used to investigate the size effects. We assess both the dispersion quality of the nanoparticles within the mixtures and the phase stability of the resulting anisotropic soft nanocomposites using polarizing optical microscopy. The temperature-mass fraction phase diagrams of the nanocomposites reveal deviations from the linear behavior in the phase stability lines. We measure the birefringence, the threshold voltage of the Fréedericksz transition, and the electrooptic switching times of the nanocomposite systems in planar cell geometry as functions of temperature, mass fraction, and diameter of the quantum dots. Beyond a critical mass fraction of the dopant nanoparticles, the nematic order is strongly reduced. Furthermore, we investigate the impact of the nanoparticle size and mass fraction on the viscoelastic coefficient. The anchoring energy at the interfaces of the liquid crystal with the cell and the quantum dots is estimated.

Detailed experimentation and prediction of thermophysical properties in lauric acid-based nanocomposite phase change material using artificial neural network

The thermal conductivity (TC) of a nanocomposite phase change material (NPCM) may be improved by adding nanostructured materials to a Phase Change Material (PCM). To assess the heat transfer rate during the process of phase change, such as melting and freezing, an accurate TC prediction of NPCM is required. A Field Emission Scanning Electron Microscope (FESEM) was utilized to examine the nanoparticle morphological study, and X-Ray Diffraction (XRD) analysis evaluated the crystalline structure. NPCMs were verified using Fourier Transform Infrared Spectroscopy (FTIR). The goal of this research is to create an Artificial Neural Network (ANN) that guesses the TC and viscosity of Lauric Acid (LA) embedded with dispersed copper oxide (CuO) and aluminium oxide (Al2O3). A multi-layered feed-forward ANN (MLFFANN) is trained using the Levenberg-Marquardt (LM) backpropagation algorithm. There are 130 experimental datasets in total, obtained from experiments with nanoparticle mass fractions ranging from 1.25 to 10 wt%. The minimum mean square error (MSE) for TC and viscosity is 4.6815 × 10−5 and 2.4681 × 10−5, respectively. The average absolute deviation (AAD) for TC and viscosity is 0.004249 and 0.003596, respectively, while the mean absolute percentage error (MAPE) is 2.1835 % and 4.8197 % for TC and viscosity, and the correlation coefficients(R) are 0.992 and 0.975, respectively. The largest percentage variation between experimental values and ANN computed values for the liquid and solid phases, respectively, is 3.54 % and 0.832 %. It demonstrates that the constructed ANN prediction model predicts the increased TC and viscosity of NPCM for different nanoparticle loadings, temperatures, and oxide nanoparticles.

Experimental investigation of usage of POE lubricants with Al2O3, graphene or CNT nanoparticles in a refrigeration compressor.

In this study, the use of nanolubricants containing Al2O3, graphene, and carbon nanotubes (CNTs) at different mass fractions in a refrigeration compressor was experimentally investigated. The required electrical power of the compressor was measured to determine the effect of the use of nanolubricants. Nanoparticles used in the preparation of nanolubricants were gradually added to the lubricant to determine the optimum nanoparticle mass fraction for each nanoparticle type. Thus, it was found that the compressor operated safely and efficiently with nanolubricants. Furthermore, the optimum mass fractions were determined to be 0.750% for Al2O3, 0.250% for graphene, and 0.250% for CNTs for operating conditions of this study. As a result, the required electrical power of the compressor decreased by 6.26, 6.82, and 5.55% with the addition of Al2O3, graphene, and CNT nanoparticles at optimum mass fractions of 0.750, 0.250, and 0.250% to the lubricant, respectively, compared to the compressor using pure oil. Moreover, density and dynamic viscosity of the nanolubricant samples used in the experiments were also measured, and their kinematic viscosity, which is an important parameter for lubricants, was calculated. It was determined that the kinematic viscosity continuously increased with increasing nanoparticle fraction. In conclusion, nanolubricants containing nanoparticles above the optimum mass fraction increase the required electrical power of the compressor. It is concluded that nanoparticle fractions should not be used above the optimum value in nanolubricant applications.