Conventional investigations on fluid flows are undertaken with an assumption of constant fluid properties. But in reality, the properties such as viscosity and thermal conductivity vary with temperature. In such cases, considering these variabilities aids in modelling the flows with accuracy. Particularly, studying the flow of graphene based nanofluids with variable properties makes the best of both the advantageous thermophysical properties of graphene nanoparticles in heat transfer and the variable fluid properties in accuartely modelling the flow. In this article, the flow of graphene oxide nanofluid along a linearly stretching cylinder under no-slip and convective boundary conditions is investigated, by taking the base fluid viscosity to be a temperature dependant function. Buongiorno model is adapted to develop the flow of graphene nanofluids including the influence of variable heat source, cross-diffusion effects and the effects of nanoparticle characteristics such as thermophoresis and Brownian motion. The modelled equations are transformed and are numerically solved using linearization method. The impacts of embedded parameters including the Dufour and Soret numbers on temperature, concentration and velocity profiles of the chosen nanofluid and their consequent impacts on the predominant cause for the generated entropy are studied. The obtained results are depicted and interpreted in detail. From the tabulated values of skin friction and the values of Sherwood and Nusselt numbers, it is inferred that the conductive heat and mass transfer can be enhanced by variable viscosity parameter and skin friction can be reduced by Soret number. Furthermore, entropy generation is analysed and Bejan number is calculated to be lesser than 0.5, thus demonstrating the dominance of irreversibilty to fluid friction and mass transfer.

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