Recent developments in the controlled-release fertilizer (CRF) have led to the new modern agriculture industry, also known as precision farming. Biopolymers as encapsulating agents for the production of controlled-release fertilizers have helped to overcome many challenging problems such as nutrients’ leaching, soil degradation, soil debris, and hefty production cost. Mechanistic modeling of biopolymers coated CRF makes it challenging due to the complicated phenomenon of biodegradation. In this study, a machine learning model is developed utilizing Gaussian process regression to predict the nutrient release time from biopolymer coated CRF with the input parameters consisting of diffusion coefficient, coefficient of-variance of coating thickness, coating mass thickness, coefficient of variance of size distribution and surface hardness from biopolymer coated controlled-release fertilizer. The developed model has shown greater prediction capabilities measured with $R^2$ equalling 1 and a Root Mean Square Error ($RMSE$) equalling 0.003. The developed model can be utilized to study the nutrient release profile of different biopolymers’-coated controlled-release fertilizers.

The objective of this research is to evaluate the heat and mass transfer in a water-based Darcy–Forchheimer hybrid nanofluid (HNF) flow across an expanding cylinder. The fluid flow has been studied under the influence of a magnetic field, viscous dissipation, heat source, thermal radiation, concentration stratification, and chemical reaction. Carbon nanotubes (CNTs) and iron ferrite (Fe₃O₄) nanoparticles (NPs) are added to the water, for the purpose of synthesizing the HNF. The fluid flow has been induced in the presence of gyrotactic microorganisms and the non-Fick’s model. Microorganisms are used to stabilize scattered nanoparticles through the hybrid nanofluid. The phenomena have been modeled in the form of a nonlinear system of partial differential equations (PDEs). The modeled equations are reduced to a dimensionless system of ODEs by using similarity substitution. The numerical solution of the derived sets of nonlinear differential equations is obtained by using the parametric continuation method. The impact of physical constraints on temperature, velocity, concentration, and microorganism profiles is presented through figures and tables. It has been observed that the heat and mass transport rates increase with the rising effect of the curvature parameter, while declining with the effect of the thermal stratification parameter.

The output of the latent heat storage devices (LHSDs), based on some phase change materials (PCMs), depends upon the thermophysical properties of the phase change material used. In this study, a paraffin-based nanofluid, blended with aluminum oxide (Al₂O₃) nanoparticles, is used as PCM for performance evaluation. A three-dimensional (3D) numerical model of regenerative type shell-and-tube LHSD is prepared using COMSOL Multiphysics^® 4.3a software to estimate the percentage of melt and the average temperature of the analyzed nanofluids. The results of this study are in close agreement with those reported in the literature, thereby ensuring the validation of the numerically predicted results. The effects of adding the nanoparticles on the rate of melting, as well as solidification and rate of stored/liberated energy, are studied. The results revealed that, by adding 10% nanoparticles of Al₂O₃, the melting rate of pure-paraffin-based LHSD improved by about 2.25 times. In addition, the rate of solidification was enhanced by 1.8 times. On the other hand, the heat of fusion and specific heat capacities were reduced, which, in turn, reduced the latent and sensible heat-storing capabilities. From the outcomes of the present research, it can be inferred that combining LHSD with a solar water heater may be used in technologies such as biogas generation.

Chitosan-capped silver nanoparticle (CS-capped AgNPs)-incorporated Poly(vinyl alcohol) (PVA) hybrid membranes were prepared by a solution-casting technique for ethanol dehydration via pervaporation. The incorporation of CS-capped AgNPs into the PVA membrane and its influence on membrane properties and pervaporation-separation process of azeotropic water/ethanol mixture was studied. The addition of CS-capped AgNPs into the PVA membrane reduced the crystallinity, thereby increasing the hydrophilicity and swelling degree of the hybrid membrane, supported by contact angle (CA) analyzer and swelling degree experiments, respectively. Fourier transform infrared spectroscopy (FTIR) demonstrated the formation of polymeric matrix between PVA and CS and also the binding of AgNPs onto the functional group of CS and PVA, which was also reflected in the microstructure images demonstrated by scanning electron microscopy (SEM) and by 2θ angle of wide-angle X-ray diffraction (WAXD). The effect of CS-capped AgNPs on the thermal stability of the hybrid membrane was demonstrated by differential scanning calorimetry (DSC) and thermogravimetric analyzer (TGA). These characteristics of the hybrid membrane positively impact the efficiency of the dehydration of ethanol, as indicated by pervaporation experiments. The best performances in total flux (12.40 ± 0.20 × 10⁻² kg/m² h) and selectivity (3612.33 ± 6.03) at 30 °C were shown for CS-capped AgNPs PVA hybrid membrane containing 2 wt.% CS-capped AgNPs (M-4). This confirms that the developed hybrid membranes can be efficiently used to separate water from azeotropic aqueous ethanol.

The performance of heat sink has been investigated as using rods through its fins. The SST k-ω model is selected to carry out this study. Two different flow directions have been studied. Four cases are represented including the baseline case which has no rods through the fins. Two, four, and six rods are used through the fins. Thermal resistance, pumping power, and Nusselt number have been represented and discussed through this study. The results show that, as the number of rods increases, the thermal resistance decreases while the required pumping power increases. The impinging flow direction shows higher performance as compared with the suction flow direction. As the Reynolds number increases, Nusselt number increases for all studied cases. The optimum case along with the studied range of Reynolds number and number of rods is Case-2 (has four rods through fins).