Energy security refers to a country’s capacity to provide the energy resources essential to its wellbeing, including a reliable supply at an affordable costs. Economic growth and development cannot occur without access to reliable energy sources. Energy availability is a proxy for a country’s standard of living and a key factor in its economic development and technical progress. Solar power is the most reliable and cost-effective option when it comes to meeting the world’s energy needs. Solar-powered cooling systems are one example of how solar energy may be used in the real world. Solar-powered air conditioners have become more popular in recent years. The problems caused by our reliance on fossil fuels may be surmounted with the help of solar cooling systems that use solar collectors. Solar cooling systems may utilize low-grade solar energy, making them popular in the construction industry. Solar cooling systems powered by photovoltaic–thermal (PVT) collectors have been the subject of much research to improve the thermodynamic and economic performance of solar cooling systems. This research focuses on exploring the potential of solar-generated heat for use in cooling systems. This study will also examine the current challenges involved with using solar energy in cooling applications, as well as the possible benefits that may help pave the way for more research and greater employment of heat gain from the solar system in various cooling applications.

Drinking water production has been thrust to the forefront of global issues as a direct result of the critical need for access to clean water and the expanding environmental difficulties. Solar stills are becoming an increasingly popular technology for the purification of water since they provide a greener and more cost-effective alternative to the production of distilled water of a high standard. Recent research has focused on the incorporation of nanofluids, which are suspensions of metallic or non-metallic nanoparticles, into base fluids such as water and oil in the hopes of further increasing the effectiveness of solar distillation. This novel technique intends to improve thermophysical and evaporation parameters, which will eventually lead to greater production in solar stills. In this paper, a complete overview of the most recent developments in the use of nanofluids in solar still technology is presented. This research investigates the potential of nanofluid-filled solar still systems by focusing on their one-of-a-kind qualities. These qualities include increased thermophysical properties, better thermal conductivity, and enhanced thermal absorptivity. The innovative nature of this method is highlighted by the fact that the use of nanofluids in active solar stills has proven a decrease in the amount of pumping power that is required. For instance, it has been ascertained that the inclusion of carbon quantum dots nanofluids to a solar still can expressively improve the water production, boosting the output by 57.9% to 823 mL compared to the 521 mL produced by a conventional still. Also, using a concentration of 0.9%, Al₂O₃, TiO₂, CuO nanofluids and multiwall carbon nanotubes can boost the water production by 11.57%, 7.16%, 6.32%, and 4.66%, respectively, if compared to a solar still without nanofluids. This study serves as a pioneering examination of the future possibilities of nanofluid-enabled solar still systems, shining light on a transformational route toward environmentally friendly and effective water purification technologies. In light of these astonishing discoveries, this research serves as a pioneering exploration of the future prospects of nanofluid-enabled solar desalination units.

Interpreting the complex interaction of nanostructured fluid flow with a dipole in a duct, with peripherally uniform temperature distribution, is the main focus of the current work. This paper also sheds light on the changes in the Nusselt number, temperature profiles, and velocity distributions for the fully developed nanofluid flow in a vertical rectangular duct due to a dipole placed near a corner of the duct. A finite volume approach has been incorporated for the numerical study of the problem. It is interesting to note the unusually lower values of the Nusselt number for the higher values of the ratio Gr/Re. Due to the nanostructure in the fluid, an enhancement in the Nusselt number has been noted, which is strongly supported by the magnetic field caused by the dipole. However, as the duct shape is transformed from rectangular to square, the Nusselt number is reduced remarkably. Further, as the dipole is brought nearer to the duct corner, the Nusselt number increases significantly. On the other hand, the flow reversal in the middle of the duct has been noted at higher values of the ratio Gr/Re. The dipole is noted to have a low impact on the reversal flow as well as on the temperature distribution.

Nanoparticle-mediated drug delivery offers a promising approach to targeted cancer therapy, leveraging the ability of nanoparticles to deliver therapeutic agents directly to cancerous tissues with minimal impact on surrounding healthy cells. The presence of these nanoparticles is governed by a concentration equation, which accounts for the diffusion, convection, and reaction of the nanoparticles with the blood components. It is well-known that whenever a disease or infection occurs in a human, in 80% of cases a rise in the concentration of hydrogen peroxide in the blood occurs. This is the reason why blood is assumed to contain hydrogen peroxide (in the present study), which is a biomarker of oxidative stress and inflammation. This study explores the integration of machine learning (ML) techniques into the optimization of drug delivery processes within the human cardiovascular system, focusing on the enhancement of these processes through the application of magnetic fields. By employing ML algorithms, we analyze and predict the behavior of nanoparticles as they navigate the complex fluid dynamics of the cardiovascular system, particularly under the influence of an external magnetic field. The predictive power of ML models enables the precise control of nanoparticle trajectories, optimizing their accumulation in cancerous tissues and improving the efficacy of the drug delivery system. The findings of this study demonstrate that ML-enhanced magnetic targeting can significantly enhance the precision and effectiveness of nanoparticle-mediated drug delivery, offering a new paradigm in cancer treatment strategies. This approach has the potential to revolutionize the field by providing personalized and highly efficient therapeutic solutions for cancer patients.