Nano Hybrids and Composites Vol. 49

Abstract: Designing a model that utilizes previously reported experimental data on graphene and metal oxide nanoparticle-based hybrids and nanocomposites to predict the gas sensor response can be a promising approach for developing innovative and effective gas sensors. In this work, experimental data were extracted from published reviews and research articles to build a dataset for training various machine learning (ML) models. The compiled dataset focuses on the rGO-SnO₂ nanohybrid-based chemiresistive sensor and includes features such as gas concentration (ppm), operating temperature (°C), sensor response (%), response time (s), and recovery time (s). The sensor response and gas concentration were considered as target variables, one at a time. Several machine learning models, such as random forest regression (RFR), support vector regression (SVR), gradient boosting regression (GBR), and extreme gradient boosting regression (XGBR), were employed to predict target variables. Prediction accuracy was evaluated using the coefficient of determination (R² score), root mean squared error (RMSE), and mean absolute error (MAE). Among all the models, the XGBR ML model achieved the best performance, with a maximum R² score (0.93) and minimum RMSE (0.52) and MAE (0.23) values when predicting gas concentration and a highest R² score of 0.99 with RMSE and MAE values of 7.97 and 5.92 when predicting sensor response as the target variable. This study demonstrates the application of machine learning for the rational design of rGO-SnO₂ nanohybrid-based NO₂ gas sensors, supporting their potential use in various applications such as indoor and outdoor monitoring and industrial gas leakage detection.

Abstract: This paper presents a numerical study on the passive cooling of an electronic component inside a rectangular enclosure filled with phase change material (PCM). The electronic component is centrally located on a substrate and generates volumetric heat. The study utilizes the enthalpy-porosity approach and the thermal equilibrium model. Its goal is to enhance the performance of the PCM by incorporating metal foam and nanoparticles. The investigation examines the impact of varying metal foam porosity while keeping the nanoparticle volume fraction constant. The results indicate that a lower porosity (0.85) significantly improves the thermal conductivity of the PCM by 3 times, which increases the cooling efficiency of the PCM-based heat sink. Meanwhile, nanoparticles have a negligible effect when metal foam is present.

Abstract: This study investigates the in-situ synthesis of cordierite–mullite ceramic using stevensite rich-ghassoul (39.6 wt.%), bio-kaolin (24.7 wt.%) and andalusite (35.7 wt.%) as starting materials. Uni-axially pressed mixtures at 96 MPa were subjected to sintering at 1250, 1300, 1350 and 1380°C o determines the optimal temperature for cordierite–mullite composite formation. The phase evolution, microstructure, porosity and thermal expansion of samples sintered 1250 to 1380° C for 2 h were investigated. The behavior and mechanical properties were evaluated using 3-point bending and indirect tensile tests. Results revealed the crystallization of cordierite and mullitization of andalusite at temperatures of 1190°C and 1300°C, respectively. Cordierite and andalusite were the predominant phases observed at 1250°C, with a gradual mullitization of andalusite as the temperature increased up to 1380°C. Rietveld quantitative phase analysis results indicate that, at a sintering temperature of 1380°C, cordierite and mullite constitute 57.4 wt% and 31.4 wt%, respectively. The sample sintered at 1380°C exhibited the optimal performance with the following properties: maximum bending and indirect tensile strengths of 31.9 ± 1.1 MPa and 26.6 ± 2.8 MPa, respectively, a flexural modulus of 34.9±2.5 GPa, a coefficient of thermal expansion of 3.6±0.4x10^-6 and a porosity.

Abstract: Understanding how oil and water interact at the surface level is essential for enhancing crude oil recovery, particularly in Enhanced Oil Recovery (EOR) techniques. This study explores the effects of three types of nanoparticles, aluminum oxide (Al₂O₃), zinc oxide (ZnO), and silica-coated iron oxide (Fe₃O₄@SiO₂) on key interfacial properties such as wettability and interfacial tension. Using a sand pack displacement setup under controlled flow conditions, nanofluids were prepared at concentrations ranging from 0.1 wt% to 0.5 wt% and evaluated for their dynamic viscosity and permeability characteristics. Results showed that ZnO reached the highest viscosity at 1.694 cP (0.5 wt%), while Fe₃O₄@SiO₂ recorded the lowest at 0.995 cP (0.1 wt%). Interestingly, permeability increased with viscosity, contrary to conventional expectations, with ZnO achieving a peak of 90 mD. Oil recovery also improved with higher nanoparticle concentrations. Al₂O₃ delivered the best performance at 0.5 wt%, recovering 27 mL of oil, followed by ZnO (24 mL) and Fe₃O₄@SiO₂ (15 mL). These findings underscore the importance of selecting the right nanoparticle type and concentration to improve EOR performance, with Al₂O₃ showing the most promise for enhancing both permeability and displacement efficiency.

Abstract: The use of hybrid nanofluids aimed to improve the exceptional qualities of fluids, including adsorption, viscosity, stability, and interfacial tension. Although several surfactant changes utilizing hybrid nanomaterials have been documented, their wider application has been hindered by the material's stability and processing challenges. The purpose of this study is to use the liquid phase exfoliation technique and examine the properties of the recently created hybrid nanofluids. This paper investigates the mechanisms of how hybrid nanofluids (HNF) composed of Graphene nanoplatelet (GNP) & SiO₂ with various surfactants such as Gum Arabic (GA) and Sodium Carboxymethyl Cellulose (SCMC) could improve EOR through adsorption of nanoparticles, improve viscosity, Interfacial tension (IFT), and wettability contact angle. Based on the results, using the hybrid nanoparticles decreases the IFT between oil-water interface from 39.700 mN/m for brine to 38.466, 37.582, 35.609 mN/m, for Control HNF, GA HNF, and SCMC HNF respectively. The adsorption of nanoparticles mechanism occurs and peaks during a 12-hour to 24hour period. Furthermore, the findings on the performance of hybrid nanofluid have increased the viscosity from 0.317cP (brine) to 3.638cP (GA) and 3.556cP (SCMC) nanofluid. When nanoparticles are introduced into reservoirs, they interact with rocks and crude oil via rock absorption, potentially improving the recovery rate of oil by changing wettability and influencing the efficiency of water-transfer to oil in several improved oil recovery methods. The contact between the rock surface, nanofluid, and oil was shown to be reduced by 29.47% and 59.12%, as seen by the contact angle of the oil droplet on the rock surfaces. The phenomenon occurs because nanoparticles are attached to the interface of rock, oil, and brine.

Abstract: Foam flooding is a promising enhanced oil recovery (EOR) while improving the gas sweep efficiency problem of gas flooding. On the other hand, nanotechnology has paved the way for utilizing nanoparticles in surfactant foam while improving foam stability, lamella thickness, bubble size distribution, and oil recovery. The significant difference between nanoparticles and surfactants as foam stabilizers is the adsorption energy of nanoparticles at gas-liquid interfaces, which is thousands of times bigger than surfactants. However, previous studies on nanoparticles' foam adsorption energy are limited by using only nanoparticles (in the absence of surfactants), though it is hard to generate foam since it does not reduce surface tension significantly. Thus, the objective of this study is to determine the adsorption energy of hydrophilic silicon dioxide (SiO2) and partially hydrophobic silicon dioxide (PH SiO2) nanoparticles in the presence of anionic sodium dodecyl sulfate (SDS) and cationic cetyltrimethylammonium bromide (CTAB) surfactants. Another objective is to analyze and evaluate the effects of adsorption energy on foam stability. Consequently, the particle radius, surface tension, and particle surface wettability were all obtained from the maker, Du Noüy ring tensiometer, and particle surface contact angle. The result shows that the adsorption energy of PH SiO2 was a thousand times greater than hydrophilic SiO2 in the presence or absence of surfactants. Due to PH SiO2 having a slightly bigger particle radius, higher adsorption energy in the PH SiO2 system is mainly by particle hydrophobicity and surface tension. In all systems, the highest adsorption energy is achieved at the lowest concentration of nanoparticles because the increment in nanoparticle concentration reduces the surface tension, eventually lowering the adsorption energy. However, this trend is contradicted with half-life foam stability when it increases with the nanoparticles concentration until the optimum concentration is obtained, then reduced. To sum up, the evaluation of the nanoparticles' foam adsorption energy in this study supports the fundamentals of nanoparticles stabilizing foam that are also influenced by other parameters: the maximum capillary pressure, particle arrangements during film drainage, and growing aggregate and the ‘cork’ formation inside lamella.

Abstract: One of the emerging alternatives to surfactants in crude oil dehydration is the application of nanoparticles. This review aims to assess the recent progress in the application of nanoparticles for the chemical demulsification of water-in-oil and to provide knowledge gaps for future research. This review covers the nanomodification of commercial demulsifiers and the demulsification performance of magnetic and nonmagnetic nanoparticles, along with their possible mechanisms and factors that affect their dehydration efficiency. The addition of nanoparticles improves the dehydration performance of commercial demulsifiers by improving their wettability and interfacial activity. The advantage of magnetic nanoparticles is their rapid response to a magnetic field, which allows them to be recoverable. For nonmagnetic nanoparticles, their advantage is their environmental friendliness, biocompatibility, and cost-effectiveness. Nanoparticles were able to dehydrate emulsions by modifying the interfacial properties and possibly through adsorption of asphaltenes. Factors such as dosage, temperature, pH, salinity, water content, surfactant concentration; and nanoparticle wettability, and surface chemistry significantly affect the demulsification performance. The application of nanoparticles as demulsifiers is still on a laboratory scale. However, studies on toxicity and proper handling may increase interest for field application. Studies are encouraged on the exact mechanism on the reduction of interfacial tension.

Abstract: This study aims to improve the mechanical and thermal properties of clay-based ecological bricks. It explores the incorporation of wood ash or crushed pottery waste in environmentally-friendly bricks. Laboratory tests have determined the optimum dosages: 20% wood ash combined with clay and 5% pottery waste. These mixtures increase the thermal resistance of bricks, thus reducing their heating and cooling demand, in line with Morocco's Thermal Building Regulations (RTCM2015). The study also aims to examine the thermophysical behavior of clay blocks stabilized with these additives.