University of Tehran Press Journal of Computational Applied Mechanics 2423-6713 57 2 2026 04 01 Unsteady Fractional MHD Flow of Blood-Based Au-Cu Hybrid Nanofluids: Coupled Heat-Mass Transfer with Dufour-Soret Effects and Biomedical Implications 195 211 104821 10.22059/jcamech.2025.406512.1698 EN Ji-Huan He School of Information Engineering, Yango University, Fuzhou, China M. Y Adamu Department of Mathematics Abubakar Tafawa Balewa University Bauchi, Nigeria Isah Abdullahi Department of Mathematics Abubakar Tafawa Balewa University Bauchi, Nigeria Nuo Xu School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China Chun-Hui He School of Civil Engineering & Transportation, Foshan University, Foshan 528000, China Journal Article 2025 11 18 This study investigates the unsteady magnetohydrodynamic (MHD) flow of blood-based Au-Cu hybrid nanofluids in cylindrical arteries, integrating thermal radiation, Joule heating, chemical reactions, and Dufour-Soret cross-diffusion effects. These effects are critical for biomedical applications like hyperthermia and targeted drug delivery. A Caputo time-fractional derivative is adopted to capture memory-dependent behaviors of biological fluids, which are typically overlooked by classical models. The governing equations for velocity, temperature, and nanoparticle concentration are transformed via Laplace transforms and solved semi-analytically using the Concentrated Matrix Exponential method. This ensures accuracy and computational efficiency. The results indicate that increasing the fractional-order parameter delays momentum, thermal, and concentration diffusion, thereby reflecting stronger memory effects. Magnetic fields have been shown to reduce velocity but enhance temperature via Joule heating. Furthermore, higher Dufour numbers have been demonstrated to strengthen temperature gradients, while elevated Soret numbers have been shown to intensify concentration gradients. This article’s novelty lies in its integration of fractional calculus with hybrid nanofluid MHD modeling, accounting for complex coupled effects. The proposed model provides more realistic predictions of unsteady biological flows, offering valuable insights for optimizing biomedical therapies and cardiovascular device design. https://jcamech.ut.ac.ir/article_104821_282828882594ac23ab1a4e2c5ed6e424.pdf