Concentration Of SiO2 Nanoparticles Research Articles

Thermophysical Properties of Silicon Oxide Nanoparticles in Water and Ethylene Glycol–Water Dispersions

Measurements of transmission as well as thermophysical properties have been carried out for different concentrations of SiO2 nanoparticles (0, 1, 2, 5, 10, and 20 wt.%) in pure water (W) and ethylene glycol–water mixture (EG/W) in a weight ratio of 25/75, from 298 to 323 K at 100 kPa. In particular, the density, specific heat capacity, and thermal diffusivity are measured by a density meter, differential scanning calorimetry, and the laser flash method. In the case of 20 wt.% SiO2, transmission in the visible range is reduced by 9.3%. Simultaneously, the density rises linearly to 12.3% (in W) and 11.3% (in EG/W). The specific heat capacity decreases to 15.9% (in W) and 17.3% (in EG/W), while the thermal diffusivity rises to 16.4% (in W) and 20.4% (in EG/W). While the density measurements are in very good agreement with the literature, the measured values of the specific heat capacity deviate more than 5%, especially for concentrations below 5 wt.% SiO2. Moreover, it is shown that the thermal conductivity increases less for fluids in small gaps compared to other authors, which could be due to the suppression of the Brownian motion. Based on the measurement results, temperature- and concentration-dependent correlations for the investigated thermophysical properties are developed using two adjustable parameters. In general, these correlations show deviations of less than 4% from the experimental results, which will help to fill the gaps in the variation of experimental results due to size, SiO2 nanofluid production, and different measurement devices, and thus optimize solar thermal applications with SiO2 nanofluid.

A Novel Technique in Determining Mud Cake Permeability in SiO2 Nanoparticles and KCl Salt Water Based Drilling Fluid using Deep Learning Algorithm

The permeability of the mud cake formed at the formation-wellbore interface is an important factor in the designing of water-based drilling fluids. This study presents a novel approach to utilizing experimental thixotropic and rheological parameters of polymeric water-based drilling fluids having varying concentrations of SiO2 nanoparticles and KCl salt. A fully connected feed-forward multi-layered neural network, more commonly known as a Multilayer Perceptron (MLP) was developed to predict the mud cake permeability using input parameters such as SiO2 & KCl concentration, differential pressure, temperature, mud cake thickness, API LPLT and HPHT filter loss volume and spurt loss volume. The results suggested that the developed Multilayer Perceptron model effectively determined the mud cake permeability based on the input parameters of the WBDF mentioned above. The model converged on the global minima, minimizing the loss function using the Gradient descent algorithm. A higher Coefficient of Determination (R2) value i.e., 0.8781, and a lesser Root Mean Square Error (RMSE) value i.e., 0.04378 indicates the higher accuracy of the model. Pearson’s Coefficient of Correlation obtained via the heatmap indicates that mud cake permeability is strongly influenced by the differential pressure followed by filter loss volume, spurt loss volume, mud cake thickness, and temperature. Previous similar studies have focused on using machine learning algorithms, this study utilized a robust deep learning algorithm i.e., Multilayer Perceptron (MLP) neural network to simultaneously model the combined effects of SiO2 nanoparticles and KCl salt concentrations on mud cake permeability, offering an unprecedented level of accuracy in predicting key WBDF performance parameters

Characteristics of Fast-Growing Wood Impregnated Using Monoethylene Glycol and SiO Nanoparticles Against Fungal Attacks

Jabon (Anthocephalus cadamba) and Sengon (Falcataria moluccana) were fast-growing wood species widely planted in the community forest. Both kinds of wood have low durability even though they can potentially be used in the carpentry material industry. Therefore, this research aimed to analyze the vacuum-pressure impregnation effect using monoethylene glycol (C2H6O2) or MEG and silica dioxide (SiO2) nanoparticles on wood resistance to fungal decay. The results showed that impregnation treatment with MEG and SiO2 nanoparticles significantly improved the durability of Jabon and Sengon against fungal attacks. Furthermore, MEGSiO2 with 24-hour polymerization had a better impact on durability compared to both the control and MEGSiO2 with 12-hour polymerization. The 24-hour polymerization using 1% SiO2 nanoparticles resulted in the lowest weight loss for Jabon (5.86% ) and Sengon (5.21%). In addition, the variation of SiO2 nanoparticle concentration did not significantly affect the weight loss and durability of Jabon and Sengon against fungal decay.

Synergistic enhancement of oil recovery: Integrating anionic-nonionic surfactant mixtures, SiO2 nanoparticles, and polymer solutions for optimized crude oil extraction

Enhanced oil recovery (EOR) methods are essential for optimizing oil extraction from modern reservoirs. This research delved into the synergistic impact of combining anionic and nonionic surfactant mixtures with silica (SiO2) nanoparticles (NPs) in sodium chloride (NaCl) solutions, alongside the added enhancement of polymers, to improve crude oil recovery. The study comprehensively evaluated stability, rheological characteristics, interfacial tension (IFT) behavior, wettability alterations, and EOR experiments using mixtures of sodium dodecyl sulfate (SDS) and triton X-100 (TX-100) surfactants. Scenarios both with and without SiO2 NPs in a base solution containing 3000 ppm NaCl and 2000 ppm xanthan gum (XG) polymer were examined. Core flooding tests were carried out on San-Saba sandstone core specimens with low permeability. The stability tests and dynamic light scattering (DLS) analysis were performed to assess the stability of NPs in low saline-surfactant-polymer solution. It was observed that NPs significantly reduced the IFT between the test solutions and crude oil, with nanofluids exhibiting satisfactory stability at a 0.4 wt% SiO2 NPs concentration. Core flooding studies demonstrated a synergistic interaction between NPs and the binary surfactant-polymer mixture, resulting in substantially greater incremental recovery of oil in comparison with the case of using binary surfactant-polymer combination alone. The mechanisms contributing to EOR with nanofluids, such as IFT reduction and wettability alteration, were explored. Incorporating NPs at concentrations of 0.1, 0.2, and 0.4 wt% led to incremental oil recoveries of 4.01 %, 12.35 %, and 12.73 % of the original oil in place (OOIP), respectively, as opposed to the recovery achieved using only SDS + TX-100 + XG. Consequently, these findings advance the understanding of the potential application of SiO2 NPs in combination with the binary surfactant-polymer mixture as effective chemical EOR agents. Additionally, these insights aid in identifying suitable sandstone reservoirs for nanofluid application, contributing to the optimization of oil recovery strategies.

Elucidation on Abnormal Capacity Increase in SiO2@C Core-Shell Nanospheres Anode for Lithium-Ion Battery.

An abnormal capacity increase stage has been observed in nanostructured SiO2 after the initial capacity drop stage. To investigate the Li+ storage kinetic mechanism for each stage, SiO2@C core-shell nanospheres with a total diameter of ∼108 to 170 nm but an adjustable C shell thickness of ∼4 to 31 nm have been fabricated. First, the existence form and specific content of SiO2 nanoparticles with a size of ∼6-10 nm, which are embedded in the outer C shell of SiO2@C core-shell nanospheres, were confirmed by SEM, TEM, BET, and TGA, respectively. It was found that the initial stage for capacity drop happens at 15-43 cycles and is followed by an enhancement stage, which presents an increase of ∼120 to 180% in capacity relative to the lowest capacity value during cycling. Among them, the sample of P-1 with a diameter of 109 nm for the SiO2 core and thickness of 31 nm for the C shell delivers the highest specific capacity of 1060 mAh/g at 100 mA/g and a capacity increase rate of ∼180% through 300 cycles. XPS analysis for the delithiation process indicates that the capacity drop and increase stage involves the partial oxidation of Li silicate, which is correlated to the formation of Li2Si2O5. Our study can be used to explain the mechanism of the abnormal capacity increase phenomenon for the SiO2 anode and provide a high-capacity anode material for LIB application.

Integrated physiological, transcriptomic, and metabolomic analyses of drought stress alleviation in Ehretia macrophylla Wall. seedlings by SiO2 NPs (silica nanoparticles).

With environmental problems such as climate global warming, drought has become one of the major stress factors, because it severely affects the plant growth and development. Silicon dioxide nanoparticles (SiO2 NPs) are crucial for mitigating abiotic stresses suffered by plants in unfavorable environmental conditions and further promoting plant growth, such as drought. This study aimed to investigate the effect of different concentrations of SiO2 NPs on the growth of the Ehretia macrophylla Wall. seedlings under severe drought stress (water content in soil, 30-35%). The treatment was started by starting spraying different concentrations of SiO2 NPs on seedlings of Ehretia macrophyla, which were consistently under normal and severe drought conditions (soil moisture content 30-35%), respectively, at the seedling stage, followed by physiological and biochemical measurements, transcriptomics and metabolomics analyses. SiO2 NPs (100 mg·L-1) treatment reduced malondialdehyde and hydrogen peroxide content and enhanced the activity of antioxidant enzymes under drought stress. Transcriptomic analysis showed that 1451 differentially expressed genes (DEGs) in the leaves of E. macrophylla seedlings were regulated by SiO2 NPs under drought stress, and these genes mainly participate in auxin signal transduction and mitogen-activated protein kinase signaling pathways. This study also found that the metabolism of fatty acids and α-linolenic acids may play a key role in the enhancement of drought tolerance in SiO2 NP-treated E. macrophylla seedlings. Metabolomics studies indicated that the accumulation level of secondary metabolites related to drought tolerance was higher after SiO2 NPs treatment. This study revealed insights into the physiological mechanisms induced by SiO2 NPs for enhancing the drought tolerance of plants.

Foliar application of SiO2 nanoparticles to increase shallot production under water stress as an effort to mitigate climate change

Global climate change has resulted in environmental stress which has the potential to reduce the production of various agricultural commodities. One of the reasons for the low production of shallot is because cultivated in land with limited water. An effort to minimize the impact of water stress on shallots is to use SiO2 nanoparticles. This study aims to determine the role of SiO2 nanoparticles to increase production of shallot under water stress. This research was conducted at the greenhouse of the Faculty of Agriculture from December 2022 to March 2023, using randomized block design. The first factor is water stress (80%, 60% and 40% field capacity) and the second factor is the concentration SiO2 nanoparticles (0 g/l, 6 g/l, 12 g/l and 18 g/l). The results showed the water stress treatment had significant effect reduced number of tubers and fresh and dry weight of tubers, the application of SiO2 nanoparticles had significant effect increased the number of tubers and fresh and dry weight of tubers. Interaction of application SiO2 nanoparticles and water stress conditions had a significant effect on increased the number of tubers in the combination of 80% field capacity with SiO2 nanoparticles concentration 12 g/l.

"Advanced Materials in Refrigeration Systems: An In-depth Analysis of Novel Additives and Their Influence on Heat Transfer Efficiency and Energy Consumption"

Abstract: This study explores the cutting-edge domain of nano refrigerants, aiming to boost the cooling performance of the widely used refrigerant R-134a by integrating a precisely balanced blend of CuO and SiO2 nanoparticles. The primary motivation for this research is the imperative to transform refrigeration systems, making them more energy-efficient and environmentally sustainable. The research methodology involves systematically creating a nano refrigerant by dispersing varying concentrations of CuO and SiO2 nanoparticles in R-134a. Selected for their exceptional thermal conductivity and stability, these nanoparticles have the potential to significantly enhance the heat transfer properties of the refrigerant. Initial stages encompass rigorous assessments of thermal conductivity improvements compared to the base R-134a, laying the groundwork for practical evaluations in a heat exchanger setup. In heat exchanger experiments, crucial parameters such as heat transfer coefficient, pressure drop, and overall heat transfer rate are precisely measured, providing a comprehensive understanding of the nano refrigerant’s real-world performance. The objective is not only to enhance thermal conductivity but also to optimize the nano refrigerant for effective and efficient heat exchange, thereby elevating the cooling capacity of R-134a. Stability studies are integral, ensuring the long-term viability of the nano refrigerant. Scrutinizing compatibility with commonly used refrigeration system materials and monitoring potential degradation over extended periods are essential.

Elektrokimyasal Olarak Çöktürülmüş Metal Oksit Takviyelendirilmiş Ni Nanokompozit Kaplamaların Korozyon Performansı

The properties of traditional nickel coatings were enhanced by preparing Ni nanocomposite coatings reinforced with metal oxide nanoparticles by using electrodeposition technique. The impact of applied current density was investigated by changing SiO2 nanoparticle concentration. Phase structure study and morphological investigation of the samples were performed by X-Ray Diffractometer and Scanning Electron Microscopy, respectively. Vickers indentation method was utilized to determine the mechanical properties of obtained nanocomposite coatings. Potentiodynamic polarization technique was performed to evaluate electrochemical behavior of nanocomposite coatings. As a result, introducing SiO 2 nanoparticles to Ni matrix improves both mechanical and electrochemical properties of produced nanocomposite coatings.

Holographic Properties of Irgacure 784/PMMA Photopolymer Doped with SiO2 Nanoparticles.

To enhance the holographic properties, one of the main methods is increasing the solubility of the photosensitizer and modifying the components to improve the modulation of the refractive index in the photopolymer. This study provides evidence, through the introduction of a mutual diffusion model, that the incorporation of SiO2 nanoparticles in photopolymers can effectively enhance the degree of refractive index modulation, consequently achieving the objective of improving the holographic performance of the materials. Different concentrations of SiO2 nanoparticles have been introduced into highly soluble photosensitizer Irgacure 784 (solubility up to 10wt%)-doped poly-methyl methacrylate (Irgacure 784/PMMA) photopolymers. Holographic measurement experiments have been performed on the prepared samples, and the experiments have demonstrated that the Irgacure 784/PMMA photopolymer doped with 1.0 × 10-3wt% SiO2 nanoparticles exhibits the highest diffraction efficiency (74.5%), representing an approximate 30% increase in diffraction efficiency as compared to an undoped photopolymer. Finally, we have successfully achieved the recording of real objects on SiO2/Irgacure 784/PMMA photopolymers, demonstrated by the SiO2/Irgacure 784/PMMA photopolymer material prepared in this study, which exhibits promising characteristics for holographic storage applications. The strategy of doping nanoparticles (Nps) in Irgacure 784/PMMA photopolymers has also provided a new approach for achieving high-capacity holographic storage in the future.

Effect of Al2O3, SiO2, and ZnO Nanoparticle Concentrations Mixed with EG–Water on the Heat Transfer Characteristics through a Microchannel

Nanofluids have gained attention for their potential to solve overheating problems in various industries. They are a mixture of a base fluid and nanoparticles dispersed on the nanoscale. The nanoparticles can be metallic, ceramic, or carbon based, depending on the desired properties. While nanofluids offer advantages, challenges such as nanoparticle agglomeration, stability, and cost effectiveness remain. Nonetheless, ongoing research aims to fully harness the potential of nanofluids in addressing overheating issues and improving thermal management in different applications. The current study is concerned with the fluid flow and heat transfer characteristics of different nanofluids using different types of nanoparticles such as Al2O3, SiO2, and ZnO mixed with different base fluids. Pure water and ethylene glycol–water (EG–H2O) mixtures at different EG–H2O ratios (ψ = 0%, 10%, 30%, 40%) are used as the base fluid. Furthermore, a rectangular microchannel heat sink is used. Mesh independent study and validation are performed to investigate the current model, and a good agreement is achieved. The numerical analysis evaluates the influence on the heat transfer coefficient and flow characteristics of nanofluids for Reynolds numbers 500 to 1200 at a 288 K inlet flow temperature. The results show that ZnO nanofluid and 40% EG–H2O increase the heat transfer coefficient by 63% compared to ZnO–H2O nanofluid obtained at Re = 1200 and φ = 5%. Conversely, the pressure drop by ZnO is nearly double that obtained by Al2O3 and SiO2.

PDMS/TiO2 and PDMS/SiO2 Nanocomposites: Mechanical Properties' Evaluation for Improved Insulating Coatings.

The use of nanoparticles (NPs) as reinforcements in polymeric coatings allows for direct interaction with the polymeric chains of the matrix, resulting in a synergistic process through physical (electrostatic forces) and chemical interactions (bond formation) for the improvement of the mechanical properties with relatively low weight concentrations of the NPs. In this investigation, different nanocomposite polymers were synthesized from the crosslinking reaction of the hydroxy-terminated polydimethylsiloxane elastomer. Different concentrations (0, 2, 4, 8, and 10 wt%) of TiO2 and SiO2 nanoparticles synthesized by the sol-gel method were added as reinforcing structures. The crystalline and morphological properties of the nanoparticles were determined through X-ray diffraction (XRD), Raman spectroscopy, and transmission electron microscopy (TEM). The molecular structure of coatings was through infrared spectroscopy (IR). The crosslinking, efficiency, hydrophobicity, and adhesion degree of the study groups were evaluated with gravimetric crosslinking tests, contact angle, and adhesion tests. It was observed that the crosslinking efficiency and surface adhesion properties of the different nanocomposites obtained were maintained. A slight increase in the contact angle was observed for the nanocomposites with 8 wt% compared to the polymer without reinforcements. The mechanical tests of indentation hardness and tensile strength following the ASTM E-384 and ISO 527 standards, respectively, were performed. As the nanoparticle concentration increased, a maximum increase of 157% in Vickers hardness, 71.4% in elastic modulus, and 80% in tensile strength was observed. However, the maximum elongation remained between 60 and 75%, ensuring that the composites did not become brittle.

Green preparation of 3D micronetwork eugenol-encapsuled porous starch for improving the performance of starch-based antibacterial film

In order to find a non-enzymatically treated alternative wall material with effective encapsulation properties, and to reduce the use of conventional non-biodegradable plastics, a novel 3D-micronetwork porous starch (3D-MPS) was created via a modified sacrificial template method to encapsulate eugenol (3D-EMPS) and used to incorporate with TiO2-starch film, for significantly improving the performance of starch-based antibacterial film. At the template SiO2 nanoparticles concentration of 0.1 %, the 3D-MPS exhibited anticipated alveolate structure with internal aperture of approximately 10 μm confirmed by SEM. With addition of 3D-EMPS, higher tensile strength (29.70 Mpa) and water barrier property (924 g/cm2·24 h) of the composite film was obtained. Moreover, molecular docking technique was used to model the intermolecular forces, which showed that the major forces maintaining the internal bonding of the composite film were hydrogen bonding and the interaction between eugenol and 3D-MPS skeleton in 3D-EMPS. Meanwhile, the composite film demonstrated the expected eugenol retardation and antimicrobial capacity against S. aureus, E. coli, and B. subtilis. Finally, the composite films were used for evaluating the feasibility in the actual food, which largely extended its shelf life compared to the negative control. This high-performance film revealed their potential for packaging materials application.

Analysis of the interfacial tension of cationic imidazolium-based ionic liquid, twin-branched tailed anionic surfactant, and a non-ionic emulsifier in the presence of SiO2 nanoparticle and amphiphilic oleic components using response surface method

Although various surface active agents have been proposed, there is still no straightforward and clear understanding of the effect of cationic imidazolium-based ionic liquid (IL), twin-branched tailed anionic surfactant, and a non-ionic emulsifier in the presence of SiO2 nanoparticle and amphiphilic oleic components on the interfacial tension (IFT) reduction. So, in this work, the performance of cationic imidazolium-based IL ([C12mim][Cl], anionic surfactant (AOT)), and non-ionic surfactant (Tween 80) on the IFT value were studied through the design of experiment approach and the response surface method. Experiments were designed using a face-centered composite design (FCCD) with the independent variables of surfactant concentration (175–525 ppm) and nanoparticle concentration (25–75 ppm) as numerical ones, and surfactant type and synthetic oil (8 wt% of asphaltene and resin fractions dissolved in heptol (mixture of n-heptane: toluene with the volume ratio of 30:70)) with various volume ratios of asphaltene to resin (1:0, 2:1, 1:1, and 1:2) as categorical ones. According to the analysis of variance (ANOVA) and 156 measured IFT experimental data points, the effects of each factor were evaluated. As a result, the suggested quadratic model with R2 (0.9986) and adjusted R2 (0.9984) values indicated that the fitted model can accurately predict the response variable (IFT) values. The best performance (lower IFT and critical micelle concentration) was obtained for [C12mim][Cl] without being affected by the amphiphilic nature of asphaltene and resin fractions and the concentration of SiO2 nanoparticles. The appropriate surface activity of IL was attributed to the effective polar head group of imidazolium and the presence of nitrogen in the aromatic ring.

Effect of SiO2 nanoparticles on the hardness and corrosion resistance of NiW/SiO2 nano composite coating prepared by electrodeposition

In this paper, NiW/SiO2 composite coatings were prepared on Q235B steel using the electrodeposition technique. The relationship between the concentration of SiO2 nanoparticles in the plating solution and the properties of NiW/SiO2 composite coating was investigated. The results show that the addition of an appropriate amount of SiO2 nanoparticles in the plating solution can enhance the cathode current, increase the surface hardness, improve the corrosion resistance, and reduce the roughness of the composite coating. The SiO2 nanoparticles covered on the coating surface can penetrate the lattice of NiW alloy to induce heterogeneous nucleation, and play a role in refining grain. However, when the SiO2 nanoparticles in the plating solution reaches 8 g/L, the agglomeration phenomenon occurs due to excessive nanoparticles, which will increase the roughness and decrease the compactness, resulting in the decrease of hardness and corrosion resistance. The NiW/SiO2 composite coating electrodeposited from the solution containing 6 g/L SiO2 nanoparticles exhibits the best hardness (643.23 HV) and the greatest corrosion resistance with the smallest corrosion current density (9.7 μA/cm2).

Effect of Concentration of SiO2 Nanoparticles in the Electrolyte on the Composition and Properties of Oxide Layers Formed by Plasma-Electrolytic Oxidation on Silumin AK7

Effect of Concentration of SiO2 Nanoparticles in the Electrolyte on the Composition and Properties of Oxide Layers Formed by Plasma-Electrolytic Oxidation on Silumin AK7

Design and spraying-preparation of the gradient coatings with various diameters and contents of SiO2 nano-particles for the enhanced anti-impact and thermal insulation performance

Composites used in aircraft are vulnerable to mechanical and thermal damage during particle impact at high speeds. In this paper, a series of gradient polyurethane silica coatings with different silica particle sizes and concentration gradients were prepared on epoxy resin matrix composites by pneumatic spraying process. The results of corundum impact and thermal insulation performance experiments indicated that multi-layer gradient coatings improved the particle impact resistance and thermal insulation. The damage was reduced to <1 % of surface damage area and thickness loss under the protection of enhanced gradient coatings, showing excellent particle impact resistance. Under unidirectional heating conditions, the temperature difference between the heating plate and the sample surface was four times that of the unprotected sample, from 2.2 °C to 9.4 °C, and the total thermal conductivity of the protected sample was reduced by 91.73 %. The coatings remained intact under high-speed particle collision of 300 A plasma flow, which verified the protection performance of the coatings simulating the situation that the coatings were impacted by particles and heated simultaneously. The as-prepared gradient coatings can effectively enhance the anti-impact and thermal insulation performance of composites, exhibiting wide application prospects.

SiO2 nanoparticles-containing slippery-liquid infused porous surface for corrosion and wear resistance of AZ31 Mg alloy

A slippery liquid-infused porous surface (SLIPS) was developed, based on MgAl-layered double hydroxide (LDH), in order to improve the corrosion and wear resistance of AZ31 Mg alloys. In particular, different concentrations of SiO2 nanoparticles were incorporated into the silicone oil to further ameliorate the performances of Mg alloys, which can effectively seal the nanopores constructed by MgAl-LDH. With increasing SiO2 nanoparticle concentration, the nanosheet microstructure of MgAl-LDH was gradually covered by the hierarchical structure of SiO2 nanoparticles. The formed composite SiO2-SLIPSs exhibited good surface hydrophobicity and superior corrosion and wear resistance. When the concentration of SiO2 nanoparticle was 10 mg mL−1, the composite SLIPS showed the best performances, with the lowest corrosion current density of 2.43 × 10-10 A cm−2 and wear volume of 0.041 mm3. The developed composite SLIPSs could find wide applications in effective corrosion and wear protection of Mg alloys in industry.

Thermal and Tribological Properties Enhancement of PVE Lubricant Modified with SiO2 and TiO2 Nanoparticles Additive

The addition of nanoparticles may have a positive or negative impact on the thermal and tribological properties of base lubricant. The objective of this paper is to investigate the effect of nanoparticle dispersion in lubricant base in relation to its application in refrigeration system compressors. An investigation of tribological and thermal properties of nanolubricants for rolling piston rotary systems was carried out through four-ball tribology tests and thermal conductivity measurements. Nanolubricants dispersed with SiO2 and TiO2 nanoparticles were tested at various concentrations and temperatures. The changes in thermal conductivity and coefficient of friction (COF) were analyzed while wear weight loss was also calculated from wear scar size. A regression model of thermal conductivity enhancement was proposed for both types of nanoparticles. Zeta potential results show that nanolubricants have excellent stability. The thermal conductivity increases by the increment of nanoparticle concentration but decreases by temperature. The R-square for the regression model is more than 0.9952 with an average deviation not more than 0.29%. The COF for SiO2/PVE nanolubricant at 0.003 vol.% reduced 15% from the baseline. The COF for nanolubricants exceeds the result for base lubricants when the concentration is more than the threshold value. The optimum concentration of SiO2 and TiO2 nanoparticles improved the thermal and tribological properties of PVE lubricant and may offer an advantage when applied to refrigeration systems.

Application of machine learning to determine the shear stress and filtration loss properties of nano-based drilling fluid

A detailed understanding of the drilling fluid rheology and filtration properties is essential to assuring reduced fluid loss during the transport process. As per literature review, silica nanoparticle is an exceptional additive to enhance drilling fluid rheology and filtration properties enhancement. However, a correlation based on nano-SiO2-water-based drilling fluid that can quantify the rheology and filtration properties of nanofluids is not available. Thus, two data-driven machine learning approaches are proposed for prediction, i.e. artificial-neural-network and least-square-support-vector-machine (LSSVM). Parameters involved for the prediction of shear stress are SiO2 concentration, temperature, and shear rate, whereas SiO2 nanoparticle concentration, temperature, and time are the inputs to simulate filtration volume. A feed-forward multilayer perceptron is constructed and optimised using the Levenberg–Marquardt learning algorithm. The parameters for the LSSVM are optimised using Couple Simulated Annealing. The performance of each model is evaluated based on several statistical parameters. The predicted results achieved R2 (coefficient of determination) value higher than 0.99 and MAE (mean absolute error) and MAPE (mean absolute percentage error) value below 7% for both the models. The developed models are further validated with experimental data that reveals an excellent agreement between predicted and experimental data.