Numerical simulation of effect of hybrid nanofluid on heat transfer and flow of the Newtonian pulsatile blood through 3D occluded artery: Silver and gold nanoparticles.

The study of blood flow in obstructed arteries is a significant focus in computational fluid dynamics, particularly in the field of biomedicine. The primary objective of this research is to investigate the impact of pulsating blood velocity on heat transfer within biological systems, with a specific focus on blood flow in obstructed arteries. To achieve this goal, a comprehensive 3D model representing a straight, constricted blood vessel has been developed. This model incorporates periodic, unsteady, Newtonian blood flow along with the presence of gold and silver nanoparticles. Leveraging the Finite Element Method (FEM), the Navier-Stokes and energy equations have been rigorously solved. Through the investigation, it is aim to shed light on how alterations in the pulsation rate and the volume fraction of nanoparticles influence both temperature distribution and velocity profiles within the system. The present study findings unequivocally highlight that the behavior of pulsatile nanofluid flow significantly impacts the velocity field and heat transfer performance. However, it is imperative to note that the extent of this influence varies depending on the specific volume fractions involved. Specifically, higher volume fractions of nanofluids correlate with elevated velocities at the center of the vessel and decreased velocities near the vessel walls. This pattern also extends to the temperature distribution and heat flux within the vessel, further underscoring the paramount importance of pulsatile flow dynamics in biomedicine and computational fluid dynamics research. Besides, results revealed that the presence of occlusion significantly affects the heat transfer and fluid flow.

Analytical development and optimization of a graphene-solution interface capacitance model.

Graphene, which as a new carbon material shows great potential for a range of applications because of its exceptional electronic and mechanical properties, becomes a matter of attention in these years. The use of graphene in nanoscale devices plays an important role in achieving more accurate and faster devices. Although there are lots of experimental studies in this area, there is a lack of analytical models. Quantum capacitance as one of the important properties of field effect transistors (FETs) is in our focus. The quantum capacitance of electrolyte-gated transistors (EGFETs) along with a relevant equivalent circuit is suggested in terms of Fermi velocity, carrier density, and fundamental physical quantities. The analytical model is compared with the experimental data and the mean absolute percentage error (MAPE) is calculated to be 11.82. In order to decrease the error, a new function of E composed of α and ß parameters is suggested. In another attempt, the ant colony optimization (ACO) algorithm is implemented for optimization and development of an analytical model to obtain a more accurate capacitance model. To further confirm this viewpoint, based on the given results, the accuracy of the optimized model is more than 97% which is in an acceptable range of accuracy.