Thermal analysis and optimization approach for ternary nanofluid flow in a novel porous cavity by considering nanoparticle shape factor.

This study focuses on the numerical investigation and optimization of the heat-fluid transfer process within a novel cavity containing a ternary nanofluid (Cu-MgO-ZnO/water) influenced by a magnetic field. The research is conducted within a circular cavity featuring a cold wall and a complex internal heat source. The governing equations, converted into dimensionless form, are solved using a computational code based on the finite volume approach. The analysis encompasses the effects of a wide range of physical parameters, including the Rayleigh number (Ra), Hartmann number (Ha), magnetic field angle (α), radiation (Ra), nanoparticle shape factor (Sf), and porosity (ԑ). The results revealed that increasing the nanoparticle shape factor leads to a significant 61 % enhancement in the outer Nusselt number. This finding underscores the substantial influence of the nanoparticle shape factor (Sf) on heat transfer compared to other controlled variables. Furthermore, the response surface method is employed to determine the optimal conditions that yield the highest Nusselt number, resulting in optimal values for Ra, Ha, ԑ, Rd, α, and Sf of 2876, 44.26, 0.75, 0.073, 54.21, and 16.15, respectively. Consequently, the highest average Nusselt number attained is 20.01. As a result, this optimization approach establishes valuable correlations among various control parameters to enhance thermal energy, offering valuable insights for designers in the development of thermal devices.

Highly sensitive label-free biosensor: graphene/CaF2 multilayer for gas, cancer, virus, and diabetes detection with enhanced quality factor and figure of merit.

One of the primary goals for the researchers is to create a high-quality sensor with a simple structure because of the urgent requirement to identify biomolecules at low concentrations to diagnose diseases and detect hazardous chemicals for health early on. Recently graphene has attracted much interest in the field of improved biosensors. Meanwhile, graphene with new materials such as CaF2 has been widely used to improve the applications of graphene-based sensors. Using the fantastic features of the graphene/CaF2 multilayer, this article proposes an improvement sensor in the sensitivity (S), the figure of merit (FOM), and the quality factor (Q). The proposed sensor is based on the five-layers graphene/dielectric grating integrated with a Fabry-Perot cavity. By tuning graphene chemical potential (µc), due to the semi-metal features of graphene, the surface plasmon resonance (SPR) waves excited at the graphene/dielectric boundaries. Due to the vertical polarization of the source to the gratings and the symmetry of the electric field, both corners of the grating act as electric dipoles, and this causes the propagation of plasmonic waves on the graphene surface to propagate towards each other. Finally, it causes Fabry-Perot (FP) interference on the surface of graphene in the proposed structure's active medium (the area where the sample is located). In this article, using the inherent nature of FP interference and its S to the environment's refractive index (RI), by changing a minimal amount in the RI of the sample, the resonance wavelength (interferometer order) shifts sharply. The proposed design can detect and sense some cancers, such as Adrenal Gland Cancer, Blood Cancer, Breast Cancer I, Breast Cancer II, Cervical Cancer, and skin cancer precisely. By optimizing the structure, we can achieve an S as high as 9000 nm/RIU and a FOM of about 52.14 for the first resonance order (M1). Likewise, the remarkable S of 38,000 nm/RIU and the FOM of 81 have been obtained for the second mode (M2). In addition, the proposed label-free SPR sensor can detect changes in the concentration of various materials, including gases and biomolecules, hemoglobin, breast cancer, diabetes, leukemia, and most alloys, with an accuracy of 0.001. The proposed sensor can sense urine concentration with a maximum S of 8500 nm/RIU and cancers with high S in the 6000 nm/RIU range to 7000 nm/RIU. Also, four viruses, such as M13 bacteriophage, HIV type one, Herpes simplex type 1, and influenza, have been investigated, showing Maximum S (for second resonance mode of λR(M2) of 8000 nm/RIU (λR(M2) = 11.2 µm), 12,000 nm/RIU (λR(M2) = 10.73 µm), 38,000 nm/RIU (λR(M2) = 11.78 µm), and 12,000 nm/RIU (λR(M2) = 10.6 µm), respectively, and the obtained S for first resonance mode (λR(M1)) for mentioned viruses are 4740 nm/RIU (λR(M1) = 8.7 µm), 8010 nm/RIU (λR(M1) = 8.44 µm), 8100 nm/RIU (λR(M1) = 10.15 µm), and 9000 (λR(M1) = 8.36 µm), respectively.

Optimization of wavy trapezoidal porous cavity containing mixture hybrid nanofluid (water/ethylene glycol Go-Al2O3) by response surface method.

Increasing thermal performance and preventing heat loss are very important in energy conversion systems, especially for new and complex products that exacerbate this need. Therefore, to solve this challenge, a trapezoidal cavity with a wavy top wall containing water/ethylene glycol GO-Al2O3 nanofluid is simulated using Galerkin finite element method. The effects of physical parameters affecting thermal performance and fluid flow, including porosity (ℇ), thermal radiation (Rd), magnetic field angle (α), Rayleigh number (Ra) and Hartmann number (Ha), are investigated in the determined ratios. The results of applied boundary conditions showed that the optimal values for Ra, Ha, ℇ, Rd and α are 1214.46, 2.86, 0.63, 0.24 and 59.35, respectively. Considering that changes in radiation have little effect on streamlines and isothermal lines. Optimization by RSM and Taguchi integration resulted in optimal Nu detection. It provided a correlation for the average Nu based on the investigated determinants due to the conflicting influence of the study factors, which finally calculated the highest average Nusselt number of 3.07. Therefore, the ideal design, which is the primary goal of this research, increases the thermal performance.

A comparative study of bone remodeling around hydroxyapatite-coated and novel radial functionally graded dental implants using finite element simulation.

This comparative study simulates bone remodeling outcome around titanium dental implants and compares the final bone configuration with the one around novel implants composed of radial functionally graded materials (FGMs) and the titanium implants with hydroxyapatite (HA) coating. A dental implant system embedded in 3D mandibular bone with masticatory loading was simulated by the finite element method. A bone remodeling algorithm was applied to cancellous and cortical bones. Young's modulus and von Mises stress were obtained to ensure bone homeostasis and evaluate the final bone configuration. Local stress distribution in the bone-implant interface was analyzed before and after bone remodeling. The average final Young's modulus of cancellous bone reached 2.68, 2.49, and 2.32 GPa for the FGM, HA-coated, and the titanium models, respectively. These values for cortical bone were 17.75, 16.86, and 17.20 GPa in the same order. Radial FGM implants generated the highest remodeling stimulus and bone density. Their superiority over the HA-coated models was confirmed by four implant surface stiffness values (10, 20, 30, and 40 GPa). Remodeling increased bone density around the implant, consistent with clinical data and reduced stress concentration in the cortical neck. The stress values were in the safe zone regarding overload-induced bone resorption. The findings of this study were substantiated by clinical images and bone density values from previous literature.