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This paper aims to establish a panoramic foundation for investigating the impact of sunlight on a recently formulated water-based tri-nano hybrid Sutterby liquid (TNHF) under provided magnetic field, directed through photovoltaic solar panels by exploiting the knacks of machine intelligent computing paradigm. The comparative performance of hybrid and tri-nano fluidic system with water as a base fluid is exhaustively analyzed and discussed. This research is unique, as it has a distinguished figurative comparison analysis between two different types of nanofluidic materials, which helps to choose the best one for use in agrivoltaics systems, and replace the materials already in use to enhance the efficiency and performance coefficients. Furthermore, the description of the composition scheme makes this research more feasible and applicable. A numerical dataset of nonlinear mathematical model is generated by employing finite difference scheme in the recently introduced Python bvp-solver algorithm, then it is embedded into artificial intelligence (AI)-based Levenberg Marquardt neural network algorithm (LMNNA). A significant outcome of the research indicates that the integration TNHF results in a notably faster enhancement of heat transfer rate and temperature framework as compared to traditional hybrid fluid. It is observed that introducing three distinct nanomaterials of specific thermophysical characteristics enhances the thermal exchanging profile and faces an obvious flow rate dissipation in solar plate channels. The standard numerical and AI-generated results are documented to portray the stability, accuracy and efficacy of scheme in terms of iterative learning curves on MSE, error analysis, histograms and regression statistics. Additional perquisites of the methodology include cost effectiveness, time-saving ability, robustness, stability and its extendibility.

We perform a constructal design of nanofluid particle volume fraction for four heat-conduction systems and four types of nanofluids to address whether nanofluids with uniformly-dispersed particles always offer the optimal global performance. The constructal volume fraction is obtained to minimize the system overall temperature difference and overall thermal resistance. The constructal thermal resistance is an overall property fixed only by the system global geometry and the average thermal conductivity of nanofluids used in the system. Efforts to enhance the thermal conductivity of nanofluids are important to reduce the constructal overall thermal resistance. The constructal nanofluids that maximize the system performance depend on both the type of nanofluids and the system configuration, and are always having a nonuniform particle volume fraction for all the cases studied in the present work. Nanofluids research and development should thus focus on not only nanofluids but also systems that use them.

The recent first-principle model shows that heat conduction in nanofluids can be diffusion-dominant or thermal-wave-dominant depending on their microscale physics (structures, properties and activities). As the first attempt of quantifying when and to what extent thermal waves become important, we numerically examine effects of particle–fluid conductivity ratio, particle shape, volume fraction and nondimensional particle–fluid interfacial area in the unit-cell on macroscale thermal properties for nanofluids consisting of in-line arrays of perfectly dispersed two-dimensional circular, square and hollow particles, respectively. In simple and perfectly dispersed nanofluids, the heat conduction is diffusion-dominant so the effective thermal conductivity can be predicted adequately by the mixture rule with the effect of particle shape and particle–fluid conductivity ratio incorporated into its empirical parameter. Thermal waves appear more likely at smaller particle–fluid conductivity ratio (< 1) and lower particle-volume-fraction, which agrees with the experimentally observed significant conductivity enhancement in the oil-in-water emulsion. The computed thermal conductivity predicts some experimental data in the literature very well and shows the sensitivity to the nondimensional particle–fluid interfacial area in the unit-cell.

The influence of particle size on density, ultrasonic velocity and viscosity of magnetite nanofluids have been determined at (298.15 K, 303.15 K, 308.15 K and 313.15 K). Two different sized nanoparticles (commercially procured D = 20–30 nm and synthesized D = 9 ± 3 nm in the laboratory by co-precipitation method) were dispersed in a citric acid base fluid. The desired parameters have been experimentally determined by loading different concentrations of nanoparticles. It has been found that the influence of particle size and temperature on measured physical parameters (density, ultrasonic velocity and viscosity) is not negligible and can also be taken into account in any practical application. The analyzed physical parameters can describe qualitatively and quantitatively the particle size distribution of nanofluids at a specific temperature. Results are interpreted in terms of particle–particle and particle–fluid interactions.

In the present study, the effect of particle concentration, particle diameter and temperature on the thermal conductivity and viscosity of Al₂O₃/water nanofluids was investigated experimentally using design of experiment approach (full factorial design). Variables were selected at two levels each: particle concentration (0.1–1%), particle diameter (20–40nm) and temperature (10–40${}^{\circ }$C). It was observed that the thermal conductivity of the Al₂O₃/water nanofluids increases with increasing concentration and temperature and decreases with increase in particle diameter, while viscosity increases with increasing particle diameter. Results showed that the interaction effect of concentration and temperature also has significant effect on the thermal conductivity of Al₂O₃/water nanofluids. For viscosity, the interaction of particle diameter and temperature was important. Utility concept was used to optimize the properties collectively for better heat transfer performance. The optimal combination for high thermal conductivity and low viscosity was obtained at higher level of particle concentration (1%), lower level of particle diameter (20nm) and higher level of temperature (40${}^{\circ }$C). At this condition the increment in thermal conductivity and viscosity compared to base fluid was 11.51% and 6.37%, respectively.

Solar steam generation is an efficient photo thermal conversion method, which has a wide range of applications in water purification and desalination. With an increasing requirement for technological advancements, the low efficiency of the working media has become a hindrance. In this work, ZrC nanofluid, which has good stability and broad-band absorption capability, was prepared to enhance the volumetric solar steam generation. The effect of ZrC nanoparticle concentration, within a large volume, on a solar steam generation was experimentally studied. It has been found that due to the unique optical absorption characteristics of ZrC nanoparticles, an advantageous temperature gradient with hot irradiation surface layer is attained and the irradiation energy is mostly absorbed by the top surface layer to generate steam. This reduces heat dissipation and improves the evaporation efficiency of the working media. Enhanced solar steam generation by using ZrC nanofluid in the base fluid reduces evaporation costs and expands its applicability in commercial production.

Nanofluids are promising in solar harvesting and solar thermal utilization. Ethylene glycol (EG) nanofluids have the advantages of high boiling point and low volatility, and therefore are highly desired in some circumstances. In this study, the solar harvesting and solar thermal conversion properties of EG were significantly enhanced by carbon chain nanostructures (CCNSs). The prepared CCNSs/EG nanofluids showed greater optical absorption compared to EG in the wavelength range from 250nm to 1400nm. The solar weighted absorption factor (Am) of the CCNSs/EG nanofluids was 95.9% at the mass fraction of 0.05 wt.%. The enhancement was 649.2% compared to that of EG. The photothermal conversion efficiency was determined to be 97.7% and the enhancement of 83.0% was achieved. An enhancement of 1.2% in thermal conductivity was also been observed. These enhancements can be ascribed to the special architectures of the CCNSs that provide fast transfer path for the generated heat.