The use of neural computational analysis for drug delivery applications results in hybrid nanofluid flow between the uniform gap of two concentric tubes

Abstract

AbstractThe blood-based Ag and TiO2 Hybrid nanofluids (HNFs) flow between the two tubes are used for drug delivery applications. Ag and TiO2 hybrid nanofluids have immense potential as drug delivery agents due to their unique properties, controlled release capabilities, targeting abilities, and synergistic effects. Extensive research is being conducted to optimize their design and maximize their effectiveness in various therapeutic applications using experimental approaches. The recent work has been focused on theoretical analysis using the existing experimental data. These HNFs are functionalized with ligands or antibodies to specifically target and deliver drugs to diseased tissues or cells. This targeted approach enhances drug accumulation at the desired site, minimizing systemic toxicity and improving treatment outcomes. An external magnetic field is applied to control the release of drugs from the nanofluids. Magnetic nanoparticles such as iron oxide nanoparticles are incorporated into the nanofluids, which respond to the magnetic field and release the drug at a specific location and time. This offers a controlled and targeted drug delivery system. The graphical and numerical outcomes of the dimensionless momentum and thermal boundary layers are investigated and discussed. It is observed that hybrid nanofluids (HNFs) often exhibit superior heat transfer (HT) properties, primarily due to the high thermal conductivity of nanoparticles. Improving heat transfer helps reduce skin friction by maintaining a more uniform temperature distribution near the surface. Also, this acts in the optimization of the blood flow analysis. In terms of drug delivery applications, hybrid nanofluids are more prominent in refining applications through optimized heat transfer, as shown by the comparison.