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The objective of this article is to explore the computational aspects of temperature dependent dynamic viscosity of Maxwell nanofluid flow over a variable thicked surface. The dynamic viscosity of the fluid is assumed to depend on temperature and due to thermal and solutal stratifications, viscosity of the liquid also depends on thermal and concentration diffusions. Temperature dependent dynamic viscosity model causes change in thermal and solutal stratifications. The basic mathematical model (system of PDEs) is reduced into nonlinear ODEs by applying similarity variables. Computational solutions of the differential system are obtained by efficient numerical approach (fifth order Rung-Kutta Fehlberg method) along the Cash and Karp. The consequential solutions are sketched for different values of physical constraints. Parameters like the temperature dependent viscosity, the fluid relaxation parameter, the wall thickness parameter and the Hartmann number are found to control the flow field. In addition, the Prandtl number, the Brownian motion parameter, the activation energy parameter, the chemical reaction rate parameter, the thermophoresis parameter, the thermal stratification parameter, the Lewis number, and the solutal stratification parameter are found to control the concentration and temperature distributions inside the stretching surface. It can be seen that for large values of the fluid relaxation parameter, the temperature dependent viscosity and the wall thickness parameter the velocity profile declines whereas reverse behavior is noticed for Hartmann number. Moreover, for large values the Lewis number, solutal stratification parameter and activation energy parameter the concentration profile shows decrease behavior.

This article addresses the effects of homogenous-heterogeneous reactions on electrically conducting boundary layer fluid flow and heat transfer characteristics over a stretching sheet with Newtonian heating are examined. Using similarity transformations, the governing equations are transformed into nonlinear ordinary differential equations. The constricted ordinary differential equations are solved computationally by shooting technique. The impact of pertinent physical parameters on the velocity, concentration and temperature profiles is discussed and explored via figures and tables. It is clear from figures that the velocity profile reduces for large values of fluid parameter B and Hartmann number H. Skin friction coefficient decreases for large values of Hartmann number H and fluid parameter B. Also, heat transfer rate monotonically enhances with conjugate parameter of Newtonian heating γ and Prandtl number Pr.