Fractional Calculus-Based Analysis of Magneto-Thermal Nanofluid Flow Over Stretching and Shrinking Surfaces

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 02 | Page :
    By

    Bibhu Prasad Ganthia,

  • Subash Ranjan Kabat,

  1. Assistant Professor, Department of Electrical Engineering, Indira Gandhi Institute of Technology, Sarang, Dhenkanal, Odisha, India
  2. Professor and Principal, Department of Electrical Engineering, Radhakrishna Institute of Technology and Engineering, Bhubaneswar, Odisha, India

Abstract

This study presents a comprehensive investigation of magneto-thermal hybrid nanofluid flow over stretching and shrinking surfaces using a fractional calculus framework to capture the memory and hereditary characteristics of complex fluid transport phenomena. The proposed model incorporates the effects of magnetic field intensity, thermal radiation, viscous dissipation, Brownian motion, and thermophoretic diffusion on the velocity and temperature distributions within the boundary layer region. A fractional-order derivative formulation is employed to provide a more realistic representation of anomalous heat and momentum transport compared with conventional integer-order models. The controlling nonlinear partial differential equations are transformed into coupled ordinary differential equations via similarity transformations, and an effective computational approach is used to solve these equations numerically. The influence of fractional order parameters, Hartmann number, nanoparticle volume fraction, and stretching/shrinking rates on skin friction coefficient and Nusselt number is analysed in detail. Results reveal that increasing magnetic field strength suppresses fluid velocity while enhancing thermal boundary layer thickness, whereas fractional parameters significantly modify the transport characteristics due to memory effects. The findings demonstrate the potential applicability of fractional nanofluid models in advanced cooling systems, microfluidic devices, solar thermal collectors, and energy transport technologies, thereby improving predictive accuracy for practical engineering applications significantly overall.

Keywords: Fractional Calculus, Magneto-Thermal Flow, Hybrid Nanofluids, Stretching Surface, Shrinking Surface, Thermal Radiation, Magnetohydrodynamics (MHD), Heat Transfer.

How to cite this article:
Bibhu Prasad Ganthia, Subash Ranjan Kabat. Fractional Calculus-Based Analysis of Magneto-Thermal Nanofluid Flow Over Stretching and Shrinking Surfaces. Recent Trends in Fluid Mechanics. 2026; 13(02):-.
How to cite this URL:
Bibhu Prasad Ganthia, Subash Ranjan Kabat. Fractional Calculus-Based Analysis of Magneto-Thermal Nanofluid Flow Over Stretching and Shrinking Surfaces. Recent Trends in Fluid Mechanics. 2026; 13(02):-. Available from: https://journals.stmjournals.com/rtfm/article=2026/view=250276


References

  1. Muzara H, Shateyi S. Magnetohydrodynamics Williamson nanofluid flow over an exponentially stretching surface with a chemical reaction and thermal radiation. Mathematics. 2023 Jun 16;11(12):2740.
  2. Fetecau C, Vieru D, Azhar WA. Natural convection flow of fractional nanofluids over an isothermal vertical plate with thermal radiation. Applied Sciences. 2017 Mar 3;7(3):247.
  3. Li H, Nikonov DE, Lin CC, Camsari K, Liao YC, Hsu CS, Naeemi A, Young IA. Physics-based models for magneto-electric spin-orbit logic circuits. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 2022 Jan 14;8(1):10-8.
  4. Onizawa N, Hanyu T. CMOS invertible logic: Bidirectional operation based on the probabilistic device model and stochastic computing. IEEE Nanotechnology Magazine. 2021 Dec 1;16(1):33-46.
  5. Kumar R, Divyanshu D, Khan D, Amara S, Massoud Y. Polymorphic hybrid CMOS-MTJ logic gates for hardware security applications. Electronics. 2023 Feb 10;12(4):902.
  6. Rangaprasad S, Joshi VK. A fully non-volatile reconfigurable magnetic arithmetic logic unit based on majority logic. IEEE Access. 2023 Oct 23;11:118944-61.
  7. Incorvia JA, Xiao TP, Zogbi N, Naeemi A, Adelmann C, Catthoor F, Tahoori M, Casanova F, Becherer M, Prenat G, Couet S. Spintronics for achieving system-level energy-efficient logic. Nature Reviews Electrical Engineering. 2024 Nov;1(11):700-13.
  8. Liu Z, Lu J, Liu J, Li W, Gui X, Lu S, Zhang H, Cao K, Xue W, Xu X, Zhao W. A Programmable In- Situ Logic-in-Memory with Full Boolean and Arithmetic Functions through Voltage-Gated Spin-Orbit Torque. IEEE Electron Device Letters. 2025 Dec 3.
  9. Jurj SL. A Physics-Regularized Neural Surrogate Framework for Printed Memristors. IEEE Access. 2026 Jan 26.
  10. Barla P, Joshi VK, Bhat S. Spintronic devices: a promising alternative to CMOS devices. Journal of Computational Electronics. 2021 Apr;20(2):805-37.
  11. Manipatruni S, Nikonov DE, Ramesh R, Li H, Young IA. Spin-orbit logic with magnetoelectric nodes: A scalable charge mediated nonvolatile spintronic logic. arXiv preprint arXiv:1512.05428. 2015 Dec 17.
  12. Xie H, Wang Y, Gao Z, Ganthia BP, Truong CV. Research on frequency parameter detection of frequency shifted track circuit based on nonlinear algorithm. Nonlinear Engineering. 2021 Jan 1;10(1):592-9.
  13. Gu J, Wang W, Yin R, Truong CV, Ganthia BP. Complex circuit simulation and nonlinear characteristics analysis of GaN power switching device. Nonlinear Engineering. 2021 Jan 1;10(1):555- 62.
  14. Rubavathy SJ, Venkatasubramanian R, Kumar MM, Ganthia BP, Kumar JS, Hemachandu P, Ramkumar MS. Smart grid based multiagent system in transmission sector. In2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) 2021 Sep 2 (pp. 1-5). IEEE.
  15. Priyadarshini L, Kundu S, Maharana MK, Ganthia BP. Controller design for the pitch control of an autonomous underwater vehicle. Engineering, Technology & Applied Science Research. 2022 Aug 7;12(4):8967-71.
  16. Zheng W, Mehbodniya A, Neware R, Wawale SG, Ganthia BP, Shabaz M. Modular unmanned aerial vehicle platform design: Multi-objective evolutionary system method. Computers and Electrical Engineering. 2022 Apr 1;99:107838.
  17. Ranjan S, Jaiswal S, Latif A, Das DC, Sinha N, Hussain SS, Ustun TS. Isolated and interconnected multi-area hybrid power systems: A review on control strategies. Energies. 2021 Dec 8;14(24):8276.
  18. Pellis S. Golden Fractals in Fluid Dynamics and Turbulence. Available at SSRN 5543579. 2025 Sep 28.
  19. Sharma BP, Peelam MS, Gupta A, Shekhar C, Chamola V. A comprehensive survey on data converters for iot applications: Scope, issues and future directions. IEEE Internet of Things Journal. 2025 Mar 20.
  20. Baraa SM, Desa H, Mohammed KS, Al-Malaisi TA, Hussain AS, Majdi HS. Selective harmonic elimination in reduced-switch multilevel inverters for PV systems using the sparrow search algorithm. Journal of Robotics and Control (JRC). 2025 Feb 15;6(1):385-95.
  21. Arshad M, Karamti H, Awrejcewicz J, Grzelczyk D, Galal AM. Thermal transmission comparison of nanofluids over stretching surface under the influence of magnetic field. Micromachines. 2022 Aug 11;13(8):1296.

Ahead of Print Subscription Review Article
Volume 13
02
Received 15/07/2026
Accepted 16/07/2026
Published 20/07/2026
Publication Time 5 Days


Login


My IP

PlumX Metrics