**8. Conclusions**

These reconsideration efforts are worthy enough to categorize the enhancement in heat transfer and thermal conductivity of non-Newtonian fluid with nanoparticle conductive properties. The velocity profile shows an increase with increasing value of the unsteadiness parameter *St*, while the increasing values of the magnetic parameter causes the decline of the velocity profile of the nanofluid film. It is shown that the coefficient of skin friction rises with the larger rates of the magnetic parameter *M* and the unsteadiness parameter *St*; on the other hand, the coefficient of skin friction decreases with higher values of the stretching and thickness parameters. The temperature profile shows a direct variation with Brownian motion parameter. The thermal boundary-layer thickness decreases with increasing values of the of *Sc*. Nusselt number with increasing values of the radiation parameter increases. The surface temperature of the fluid increases with increasing values of Prandtl number, while an opposite tendency is observed with larger values of the unsteady parameter on the temperature profile. Similar results are investigated for the temperature profile with the variation of the thermophoresis parameter. The mass flux shows a decline with higher numbers of the Brownian motion parameter, while an opposite trend is experienced for the thermophoretic parameter. The implemented technique convergence is shown numerically for the validation of our technique.

**Author Contributions:** A.U., Z.S. and S.I. modeled the problem and wrote the manuscript. P.K. and M.A. thoroughly checked the mathematical modeling and English corrections. M.J. and A.U. solved the problem using Mathematica software, and P.K., Z.S., M.J., and M.A. contributed to the results and discussions. All authors finalized the manuscript after its internal evaluation.

**Funding:** This research was funded by the Center of Excellence in Theoretical and Computational Science (TaCS-CoE), KMUTT.

**Acknowledgments:** This project was supported by the Theoretical and Computational Science (TaCS) Center under Computational and Applied Science for Smart Innovation Research Cluster (CLASSIC), Faculty of Science, KMUTT.

**Conflicts of Interest:** The authors declare no conflict of interest.
