To investigate the effects of fractional order (), nanoparticle volume fraction (), magnetic field strength (), and Brinkman permeability () on both flow and heat transfer characteristics, a detailed parametric and statistical analysis is conducted. The statistical regression analysis shows that the volume fraction of nanoparticles and temperature have a strong positive correlation (coefficient = 0.94, p = 0.021) indicating that Mo2C MXene is an excellent heat absorption. On the other hand, the fractional parameter α has a strong negative effect on temperature field (coefficient = − 0.086, p < 0.001), which emphasizes its importance in describing the effects of thermal memory. The findings also indicate that, although MXene nanoparticles significantly increase thermal transport, an augmentation in magnetic field strength and Brinkman resistance cause a resistive Lorentz force and frictional drag, respectively, to prevent fluid flow. These results are physically informative about non-Fourier heat transfer in MXene-based nanofluids as well as offer invaluable information to developing high-performance thermal management systems and solar-energy applications.

This study investigates the magneto hydrodynamic (MHD) boundary layer flow and double-diffusive heat and mass transfer characteristics of a hybrid nanofluid composed of silver (Ag) and magnesium oxide (MgO) nanoparticles dispersed in water over a vertically oriented cone with convective surface heating. The novelty of the work lies in the simultaneous incorporation of Cattaneo–Christov heat and mass flux theories to model non-Fourier heat conduction and non-Fickian mass diffusion in the presence of hybrid nanofluid effects, space-dependent internal heat generation/absorption, and first-order chemical reaction. A uniform transverse magnetic field is applied to examine electromagnetic control of the transport processes. The governing nonlinear partial differential equations describing continuity, momentum, energy, and concentration are transformed into a coupled system of nonlinear ordinary differential equations using suitable similarity transformations. The resulting system is solved analytically through the Optimal Homotopy Asymptotic Method (OHAM). The results demonstrate that increasing the magnetic parameter significantly suppresses the velocity field due to the enhanced Lorentz force, while simultaneously elevating the temperature distribution because of resistive heating effects. The inclusion of Ag–MgO hybrid nanoparticles substantially enhances thermal performance, yielding nearly 31.2% improvements in heat transfer rate compared with the base fluid. Furthermore, thermal and solutal relaxation parameters delay heat and mass diffusion, thereby reducing thermal and concentration boundary layer thicknesses. Stronger chemical reaction effects markedly decrease concentration profiles through accelerated species consumption. These findings highlight the potential of hybrid nanofluids in advanced cooling technologies, nuclear energy systems, and high-performance thermal management applications.