“…The maximum recorded thermal conductivity was 33.9% with 1% volume fraction and 50˚c [92] . Graphene nanoplatelets are dispersed in 30 PPT saline media using SDS as a stabilizer agent and the ultrasonic homogenization is done by using probe sonicator for 1 h and the TEM analysis revealed that big sized agglomeration is decreased to small size [93] . Fig.…”
Section: Effect Of Ultrasonication On Graphene Nanofluidsmentioning
“…The maximum recorded thermal conductivity was 33.9% with 1% volume fraction and 50˚c [92] . Graphene nanoplatelets are dispersed in 30 PPT saline media using SDS as a stabilizer agent and the ultrasonic homogenization is done by using probe sonicator for 1 h and the TEM analysis revealed that big sized agglomeration is decreased to small size [93] . Fig.…”
Section: Effect Of Ultrasonication On Graphene Nanofluidsmentioning
“…An ultrasonic homogenizer (probe), (Biologics 150V/T, USA), is used with frequency 20 kHz. The optimized ultrasonic parameters are taken from previous studies [41,44,45], i.e., 1 hr operation, 30% pulse and 70% power. This indicates that each nanofluid sample is ultrasonicated with a 70% power of the equipment's total ultrasonic frequency.…”
Section: Preparation and Stability Of Nanofluidsmentioning
confidence: 99%
“…It has proven to be a significant agent for high-frequency nanoelectronics, supercapacitors, chemical sensors, EOR, etc. [39][40][41].…”
Recent advancements in thermo-fluid technology assisted with highly thermal conductive nanomaterials have shown assuring outcomes. It is also proven that thermal conductivity alone cannot define the overall heat transfer characteristics, and the viscous properties are equally significant towards thermal management. Therefore, this research involves investigating the rheological behavior of hybrid nanosuspensions containing high thermally conductive diamond and graphene nanoplatelets (1:1). These nanomaterials are dispersed in mineral oil using a two-step technique. Hybrid nanofluids' stability is achieved using a non-ionic stabilizer Span85, exhibiting no sedimentation for a minimum of five months. Nanomaterial characterizations are performed to study morphology, purity, and chemical analysis. The flow behavior of hybrid nanosuspensions is investigated at varying nanomaterial mass concentrations (0-2 %), temperatures (298.15-338.15 K), and shear rates (1-2000 s -1 ). Hybrid nanofluids exhibit shear-thinning behavior, which is also correlated with the Ostwald-de-Waele model. The temperature-viscosity relationship is well predicted using the Vogel-Fulcher-Tammann model. Hybrid nanofluids show a maximum enhancement of 35% viscosity at 2% concentration. A generalized twovariable correlation is used to express viscosity as a function of temperature and nanofluid concentration with an excellent agreement. Three different machine learning methods, i.e., Artificial Neural Network (ANN), Gradient Boosting Machine (GBM), and Random Forest (RF) algorithms are also introduced to predict the viscosity of hybrid nanofluids based on the three input parameters (temperature, concentration, and shear rate). The parity plots conclude that all algorithms can predict big-data viscous behavior with high precision.
“…As a result, adding surfactants to graphene-based nanofluids improves their stability [ 24 , 25 ]. Although the incorporation of surfactants in nanofluids of carbon-based nanomaterials has demonstrated improving their stability [ 26 ], surfactants may decrease the performance of these nanofluids through the reduction in their thermal conductivity [ 27 , 28 ], the low-temperature degradation of surfactants, and their tendency to produce foam, which implies additional thermal resistance [ 29 , 30 ].…”
Carbon-based nanomaterials have a high thermal conductivity, which can be exploited to prepare nanofluids. Graphene is a hydrophobic substance, and consequently, graphene-based nanofluid stability is improved by adding surfactants. An attractive alternative is the decoration of reduced graphene oxide (rGO) with metallic materials to improve the thermal conductivity without affecting the stability of nanofluids. This study focuses on the synthesis and characterization of rGO/Ag (0.1 wt.%) aqueous nanofluids. Moreover, the effects of the Ag concentration (0.01–1 M) on the thermal conductivity and viscosity during the synthesis of rGO/Ag composite are analyzed. The nanofluid thermal conductivity showed increases in relation to the base fluid, the most promising being 28.43 and 26.25% for 0.1 and 1 M of Ag, respectively. Furthermore, the nanofluids were Newtonian in the analyzed range of shear rates and presented a moderate increase (<11%) in viscosity. Aqueous nanofluids based on rGO/Ag nanocomposites are a potential alternative for applications as heat transfer fluids.
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