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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.

A mathematical model has been developed for steady-state boundary layer flow of a nanofluid past an impermeable vertical flat wall in a porous medium saturated with a water-based dilute nanofluid containing oxytactic microorganisms. The nanoparticles were distributed sufficiently to permit bioconvection. The product of chemotaxis constant and maximum cell swimming speed was assumed invariant. Using appropriate transformations, the partial differential conservation equations were non-dimensionalised to yield a quartet of coupled, non-linear ordinary differential equations for momentum, energy, nanoparticle concentration and dimensionless motile microorganism density, with appropriate boundary conditions. The dominant parameters emerging in the normalised model included the bioconvection Lewis number, bioconvection Peclet number, Lewis number, buoyancy ratio parameter, Brownian motion parameter, thermophoresis parameter, local Darcy-Rayleigh number and the local Peclet number. An implicit numerical solution to the well-posed two-point non-linear boundary value problem is developed using the well-tested and highly efficient Keller box method. Computations are validated with the Nakamura tridiagonal implicit finite difference method, demonstrating excellent agreement. Nanoparticle concentration and temperature were found to be generally enhanced through the boundary layer with increasing bioconvection Lewis number, whereas dimensionless motile microorganism density was only increased closer to the wall. Temperature, nanoparticle concentration and dimensionless motile microorganism density were all greatly increased with a rise in Peclet number. Temperature and dimensionless motile microorganism density were reduced with increasing buoyancy parameter, whereas nanoparticle concentration was increased. The present study found applications in the fluid mechanical design of microbial fuel cell and bioconvection nanotechnological devices.

Laminar magnetohydrodynamic Marangoni-forced convection boundary layer flow of a water-based biopolymer nanofluid containing nanoparticles from a non-isothermal plate is studied. Magnetic induction effects are incorporated. A variety of nanoparticles are studied, specifically, silver, copper, aluminium oxide and titanium oxide. The Tiwari–Das model is utilized for simulating nanofluid effects. The normalized ordinary differential boundary layer equations (mass, magnetic field continuity, momentum, induced magnetic field and energy conservation) are solved subject to appropriate boundary conditions using Maple shooting quadrature. The influence of Prandtl number (Pr), magnetohydrodynamic body force parameter (β), reciprocal of magnetic Prandtl number (α) and nanofluid solid volume fraction (φ) on velocity, temperature and magnetic stream function distributions is investigated in the presence of strong Marangoni effects (ξ i.e., Marangoni parameter is set as unity). Magnetic stream function is accentuated with body force parameter. The flow is considerably decelerated as is magnetic stream function gradient, with increasing nanofluid solid volume fraction, whereas temperatures are significantly enhanced. Interesting features in the flow regime are explored. The study finds applications in the fabrication of complex biomedical nanofluids, biopolymers, etc.

In this paper, the unsteady fully developed forced convective flow of viscous incompressible biofluid that contains both nanoparticles and gyrotactic microorganisms in a horizontal micro-channel is studied. Buongiorno’s model is employed. The upper channel wall is either expanding or contracting and permeable and the lower wall is static and impermeable. The plate separation is therefore a function of time. Velocity, temperature, nanoparticle species (mass) and motile microorganism slip effects are taken into account at the upper wall. By using the appropriate similarity transformation for the velocity, temperature, nanoparticle volume fraction and motile microorganism density, the governing partial differential conservation equations are reduced to a set of similarity ordinary differential equations. These equations under prescribed boundary conditions are solved numerically using the Runge–Kutta–Fehlberg fourth-fifth-order numerical quadrature in the MAPLE symbolic software. Excellent agreement between the present computations and solutions available in the literature (for special cases) is achieved. The key thermofluid parameters emerging are identified as Reynolds number, wall expansion ratio, Prandtl number, Brownian motion parameter, thermophoresis parameter, Lewis number, bioconvection Lewis number and bioconvection Péclet number. The influence of all these parameters on flow velocity, temperature, nanoparticle volume fraction (concentration) and motile microorganism density function is elaborated. Furthermore, graphical solutions are included for skin friction, wall heat transfer rate, nanoparticle mass transfer rate and microorganism transfer rate. Increasing expansion ratio is observed to enhance temperatures and motile microorganism density. Both nanoparticle volume fraction and microorganism increases with an increase in momentum slip. The dimensionless temperature and microorganism increases as wall expansion increases. Applications of the study arise in advanced nanomechanical bioconvection energy conversion devices, bio-nano-coolant deployment systems, etc.

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.