Abstract
This paper investigates the bio-convective behavior of a third-grade non-Newtonian nanofluid over a stretching sheet. While the influence of Newtonian fluid flow based on classical Fourier and Fick’s laws has been widely discussed in previous studies, this work focuses on a novel third-grade nanofluid model incorporating various physical effects. Notably, the classical Fourier law is replaced by the Cattaneo–Christov (CC) theory for both heat and mass fluxes, capturing relaxation phenomena in the presence of bioconvective effects. Heat and mass transport are modeled using the CC framework, and nanoscale mechanisms are described via the Buongiorno nanofluid model. The influences of thermophoresis and Brownian motion are analyzed alongside dissipative and radiative effects. The Optimal Homotopy Asymptotic Method (OHAM) is employed to solve the resulting nonlinear equations. Graphical representations of key parameters are presented. Results reveal that the velocity profile increases with higher values of material parameters but decreases with an increase in the Reynolds number. The temperature decreases with higher Prandtl number but increases with greater radiation parameter. The concentration profile is found to decline with increasing Schmidt number.
Keywords
modified fourier and fick's law
third-grade nano-fluid
MHD
viscous dissipation
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by Jiangsu Excellent Postdoctoral Program under Grant 2023ZB890.
Conflicts of Interest
The author declares no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
Cite This Article
APA Style
Shah, F. (2025). Numerical Study of Nonlinear Third-Grade Nanofluid with Generalized Heat and Mass Flux in Mixed Convective Flow. ICCK Journal of Applied Mathematics, 1(2), 52-61. https://doi.org/10.62762/JAM.2025.671250
Publisher's Note
ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and Permissions

Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.