Nonlinear nanofluid fluid flow under the consequences of Lorentz forces and Arrhenius kinetics through a permeable surface: A robust spectral approach

Background: Emerging applications in nanomaterials processing are increasingly featuring\ud multiple physical phenomena including magnetic body forces, chemical reactions and high\ud temperature behavior. Stimulated by developing a deeper insight of nanoscale fluid dynamics in\ud such manufacturing systems, in the current article, we study the magnetic nanofluid dynamics\ud along a nonlinear porous stretching sheet with Arrhenius chemical kinetics and wall transpiration.\ud Appropriate similarity transformations are employed to simplify the governing flow problem.\ud Methods: The emerging momentum, thermal energy and nanoparticle concentration ordinary\ud differential conservation equations are solved numerically with a hybrid technique combining\ud Successive Linearization and Chebyshev Spectral Collocation. A parametric study of the impacts\ud of magnetic parameter, porous media parameter, Brownian motion parameter, parameters for\ud thermophoresis, radiation, Arrhenius function, suction/injection (transpiration) and nonlinear\ud stretching in addition to Schmidt number on velocity, temperature and nanoparticle (concentration)\ud distribution is conducted. A detail numerical comparison is presented with different numerical and \ud 2\ud analytical techniques as a specific case of the current investigation.\ud Findings: Increasing chemical reaction constant parameter significantly decreases nanoparticle\ud concentration magnitudes and results in a thickening of the nanoparticle concentration boundary\ud layer. Enhancing the values of activation energy parameter significantly increases the nanoparticle\ud concentration magnitudes. Increasing thermophoresis parameter elevates both temperature and\ud nanoparticle concentration. Increasing radiation parameter increases temperature and thermal\ud boundary layer thickness. Enlarging Brownian motion parameter (smaller nanoparticles) and\ud Schmidt number both depress the nanoparticle concentration.