Influence of graphene nanoplate size and heat flux on nanofluid heat exchanger performance: A molecular dynamics approach

Journal article


Yang, Z., Basem, A., Jasim, D.J., Singh, N.S.S., Saeidlou, S., Al-Bahrani, M., Sajadi, S.M., Salahshour, S. and Hasanabad, A.M. 2025. Influence of graphene nanoplate size and heat flux on nanofluid heat exchanger performance: A molecular dynamics approach. International Communications in Heat and Mass Transfer. 167 (109386). https://doi.org/10.1016/j.icheatmasstransfer.2025.109386
AuthorsYang, Z., Basem, A., Jasim, D.J., Singh, N.S.S., Saeidlou, S., Al-Bahrani, M., Sajadi, S.M., Salahshour, S. and Hasanabad, A.M.
Abstract

This study aimed to enhance the thermal efficiency of nanofluid-based heat exchangers by exploring the simultaneous effects of external heat flux and graphene nanoplate sizes on thermal and structural characteristics. Effective heat transfer is a critical requirement for managing heat in microscale systems, where optimizing the thermal performance of nanofluids can improve device performance. Molecular dynamics simulations were carried out of a sinusoidal inner surface copper heat exchanger coated with silicon nanoparticles to demonstrate atomic-level interaction within the nanofluid. The significant findings showed that while an external rising heat flux decreased heat flux from 41.7 to 37.26 W/m² and thermal conductivity of nanofluid from 14.53 to 13.80 W/m·K, only an increase in viscosity from 0.32 to 0.49 mPa·s, the agglomeration time of nanoparticles decreased from 3.71 to 3.33 ns and friction coefficient from 0.022 to 0.015, could indicate a difference in particle behavior responding to the thermal stress. However, the size of the graphene nanoplate from 5 to 15 Å increased the heat flux from 40.05 to 46.77 W/m² and thermal conductivity of the nanofluid from 14.15 to 14.99 W/m·K, since the larger graphene nanoplate films can produce a more substantial covalent bonding and link interlayer coupling. In contrast, the larger nanoplate also enhanced viscosity from 0.30 to 0.39 mPa·s, aggregation time from 3.64 to 4.01 ns, and friction coefficient from 0.020 to 0.026, which indicated lower particle mobility. This study was the first of its kind to contribute to the existing knowledge gap by investigating the simultaneous effect of both the nanoplate size and external heat flux in an oscillating microchannel heat exchanger. The knowledge provided offers an experimental pathway in optimizing the nanofluid properties and the heat exchanger geometry for improved thermal management for compact and microscale applications.

KeywordsHeat exchanger; Graphene nanoplates; Thermal properties; Molecular dynamics simulation
Year2025
JournalInternational Communications in Heat and Mass Transfer
Journal citation167 (109386)
PublisherElsevier
ISSN0735-1933
Digital Object Identifier (DOI)https://doi.org/10.1016/j.icheatmasstransfer.2025.109386
Official URLhttps://www.sciencedirect.com/science/article/pii/S0735193325008127
Publication dates
Online21 Jul 2025
Publication process dates
Accepted13 Jul 2025
Deposited23 Jul 2025
Accepted author manuscript
License
File Access Level
Open
Output statusPublished
References

[1] M. H. Aghahadi, M. Niknejadi, and D. Toghraie, “An experimental study on the rheological behavior of hybrid Tungsten oxide (WO3)-MWCNTs/engine oil Newtonian nanofluids,” Journal of Molecular Structure, vol. 1197, pp. 497-507, 2019.

[2] Ayoob, H. W., Omar, I., Ghanim, W. K., Fares, M. N., Fazilati, M. A., Salahshour, S., & Esmaeili, S. (2025). The thermal-flow performance of water-Al2O3 nanofluid flow in an elliptical duct heat exchanger equipped with two rotating twisted tapes. Case Studies in Chemical and Environmental Engineering, 11(101094), 101094. doi:10.1016/j.cscee.2025.101094.

[3] A. Ruhani, A. Abidi, A. K. Hussein, O. Younis, M. Degani, and M. Sharifpur, “Numerical simulation of the effect of battery distance and inlet and outlet length on the cooling of cylindrical lithium-ion batteries and overall performance of thermal management system,” Journal of Energy Storage, vol. 45, pp. 103714, 2022.

[4] I. Razzaq, W. Xinhua, G. Rasool, T. Sun, A. S. Shflot, M. Y. Malik, K. Abbas, S. Ali, and A. Ali, “Nanofluids for advanced applications: a comprehensive review on preparation methods, properties, and environmental impact,” ACS omega, vol. 10, no. 6, pp. 5251-5282, 2025.

[5] H. Younes, M. Mao, S. S. Murshed, D. Lou, H. Hong, and G. Peterson, “Nanofluids: Key parameters to enhance thermal conductivity and its applications,” Applied Thermal Engineering, vol. 207, pp. 118202, 2022.

[6] F. Shuang, and K. E. Aifantis, “Relating the strength of graphene/metal composites to the graphene orientation and position,” Scripta Materialia, vol. 181, pp. 70-75, 2020.

[7] J. Charleston, A. Agrawal, and R. Mirzaeifar, “Effect of interface configuration on the mechanical properties and dislocation mechanisms in metal graphene composites,”

Computational Materials Science, vol. 178, pp. 109621, 2020.
[8] D. J. Kim, Q.-T. Truong, J. I. Kim, Y. Suh, J. Moon, S.-E. Lee, B. H. Hong, and Y. S. Woo, “Ultrahigh-strength multi-layer graphene-coated Ni film with interface-induced hardening,” Carbon, vol. 178, pp. 497-505, 2021.

[9] J. Guo, C. Xiao, J. Gao, G. Li, H. Wu, L. Chen, and L. Qian, “Interplay between counter-surface chemistry and mechanical activation in mechanochemical removal of N-faced GaN surface in humid ambient,” Tribology international, vol. 159, pp. 107004, 2021.

[10] M. Goodarzi, A. Amiri, M. S. Goodarzi, M. R. Safaei, A. Karimipour, E. M. Languri, and M. Dahari, “Investigation of heat transfer and pressure drop of a counter flow corrugated plate heat exchanger using MWCNT based nanofluids,” International communications in heat and mass transfer, vol. 66, pp. 172-179, 2015.

[11] M. H. Bahmani, G. Sheikhzadeh, M. Zarringhalam, O. A. Akbari, A. A. Alrashed, G. A. S. Shabani, and M. Goodarzi, “Investigation of turbulent heat transfer and nanofluid flow in a double pipe heat exchanger,” Advanced Powder Technology, vol. 29, no. 2, pp. 273-282, 2018.

[12] N. A. Qasem, and S. M. Zubair, “Compact and microchannel heat exchangers: A comprehensive review of air-side friction factor and heat transfer correlations,” Energy conversion and management, vol. 173, pp. 555-601, 2018.

[13] W. Ajeeb, and S. S. Murshed, “Nanofluids in compact heat exchangers for thermal applications: A State-of-the-art review,” Thermal Science and Engineering Progress, vol. 30, pp. 101276, 2022.

[14] X. Pan, H. Jin, X. Ku, Y. Guo, and J. Fan, “Coupling at the molecular scale between the graphene nanosheet and water and its effect on the thermal conductivity of the nanofluid,” Physical Chemistry Chemical Physics, vol. 26, no. 3, pp. 2402-2413, 2024.

[15] Y. Li, T. Zhang, Y. Zhang, C. Zhao, N. Zheng, and W. Yu, “A comprehensive experimental study regarding size dependence on thermal conductivity of graphene oxide nanosheet,” International Communications in Heat and Mass Transfer, vol. 130, pp. 105764, 2022.

[16] L. Xiang, Y. Mei, X. Yang, Z. Cao, S. Qin, and L. Chen, “Effect of Graphene Diameter on Heat Transfer Pathways in Graphene/PVDF Nanocomposite Membranes,” ACS Applied Nano Materials, vol. 7, no. 7, pp. 7694-7702, 2024.

[17] H. H. Almutter, W. H. Hassan, S. A. Hussein, D. J. Jasim, S. Salahshour, and N. Emami, “A numerical study of the effect of graphene nanoparticle size on brownian displacement, thermophoresis, and thermal performance of graphene/water nanofluid by molecular dynamics simulation,” International Journal of Thermofluids, vol. 24, pp. 100927, 2024.

[18] X. Guo, D. J. Jasim, A. a. Alizadeh, B. Keivani, N. Nasajpour-Esfahani, S. Salahshour, M. Shamsborhan, and R. Sabetvand, “Investigating the effect of the number of layers of the atomic channel wall on Brownian displacement, thermophoresis, and thermal behavior of graphene/water nanofluid by molecular dynamics simulation,” Case Studies in Thermal Engineering, vol. 53, pp. 103859, 2024.

[19] M. Zolfalizadeh, S. Zeinali Heris, H. Pourpasha, M. Mohammadpourfard, and J. P. Meyer, “Experimental investigation of the effect of graphene/water nanofluid on the heat transfer of a shell‐and‐tube heat exchanger,” International Journal of Energy Research, vol. 2023, no. 1, pp. 3477673, 2023.

[20] C. C. Lima, A. A. Ochoa, J. A. da Costa, F. D. de Menezes, J. V. Alves, J. M. Ferreira, C. C. Azevedo, P. S. Michima, and G. N. Leite, “Experimental and computational fluid dynamic—CFD analysis simulation of heat transfer using graphene nanoplatelets GNP/water in the double tube heat exchanger,” Processes, vol. 11, no. 9, pp. 2735, 2023.

[21] X. Guo, X. Chen, J. Zhao, W. Zhou, and J. Wei, “Effect of the Addition of Graphene Nanoplatelets on the Thermal Conductivity of Rocket Kerosene: A Molecular Dynamics Study,” Materials, vol. 15, no. 16, pp. 5511, 2022.

[22] I. Moulefera, J. D. Marín, A. Cascales, M. Montalbán, M. Alarcón, and G. Víllora, “Innovative application of graphene nanoplatelet-based ionanofluids as heat transfer fluid in hybrid photovoltaic-thermal solar collectors,” Scientific Reports, vol. 15, no. 1, pp. 6489, 2025.

[23] D. Frenkel, and B. Smit, Understanding molecular simulation: from algorithms to applications: Elsevier, 2023.

[24] G. Vakili-Nezhaad, M. Al-Wadhahi, A. M. Gujrathi, R. Al-Maamari, and M. Mohammadi, “Effect of temperature and diameter of narrow single-walled carbon nanotubes on the viscosity of nanofluid: A molecular dynamics study,” Fluid Phase Equilibria, vol. 434, pp. 193-199, 2017.

[25] S. Lee, R. Saidur, M. Sabri, and T. Min, “Effects of the particle size and temperature on the efficiency of nanofluids using molecular dynamic simulation,” Numerical Heat Transfer, Part A: Applications, vol. 69, no. 9, pp. 996-1013, 2016.

[26] S. Ju, X. Liang, and X. Xu, “Out-of-plane thermal conductivity of polycrystalline silicon nanofilm by molecular dynamics simulation,” Journal of Applied Physics, vol. 110, no. 5, 2011.

[27] K. Vollmayr-Lee, “Introduction to molecular dynamics simulations,” American Journal of Physics, vol. 88, no. 5, pp. 401-422, 2020.

[28] M. S. Badar, S. Shamsi, J. Ahmed, and M. A. Alam, "Molecular dynamics simulations: concept, methods, and applications," Transdisciplinarity, pp. 131-151: Springer, 2022.

[29] J. Jung, C. Kobayashi, and Y. Sugita, “Kinetic energy definition in velocity Verlet integration for accurate pressure evaluation,” The Journal of chemical physics, vol. 148, no. 16, 2018.

[30] N. K. Dehkordi, S. Shojaei, A. Asefnejad, K. Hassani, and S. Z. Benisi, “Investigation of mechanical properties and the effect of volume fraction of polyacrylamide hydrogel with molecular dynamics simulation,” Results in Physics, vol. 57, pp. 107440, 2024.

[31] D. d. C. Branco, and G. J. Cheng, “Employing hybrid Lennard-Jones and Axilrod-Teller potentials to parametrize force fields for the simulation of materials’ properties,” Materials, vol. 14, no. 21, pp. 6352, 2021.
[32] M. P. Bernhardt, Y. Nagata, and N. F. va
n der Vegt, “Where Lennard-Jones potentials fail: Iterative optimization of ion–water pair potentials based on ab initio molecular dynamics data,” The Journal of Physical Chemistry Letters, vol. 13, no. 16, pp. 3712-3717, 2022.

[33] D. Pan, J. Li, L. C. Voon, and P. Wei, “Determination of Lennard-Jones potential parameters for interfacial interaction in elemental layered crystals,” Journal of Applied Physics, vol. 135, no. 20, 2024.

[34] Q. Deng, and Q. Liu, “Field‐programmable gate array acceleration of the Tersoff potential in LAMMPS,” Engineering Reports, vol. 7, no. 1, pp. e12694, 2025.

[35] X. Wang, J. Yan, H. Zhang, Z. Xu, and J. Z. Zhang, “An electrostatic energy-based charge model for molecular dynamics simulation,” The Journal of Chemical Physics, vol. 154, no. 13, 2021.

[36] Liu, Y., Basem, A., Al-zahy, Y. M. A., Singh, N. S. S., Al-Bahrani, M., Abduvalieva, D., … Esmaeili, S. (2025). Molecular dynamics simulation of thermal behavior of paraffin/Cu nanoparticle PCM in a non-connected rotating ribbed tube. International Communications in Heat and Mass Transfer, 165(109058), 109058. doi:10.1016/j.icheatmasstransfer.2025.109058

[37] Zhang, E., Yao, X., Ali, A. B. M., Singh, N. S. S., Baghaei, S., & Marzouki, R. (2025). Using staircase walls to improve heat and mass transfer inside a micro flat plate heat pipe cell: A molecular dynamics simulation study. International Communications in Heat and Mass Transfer, 164(108880), 108880.
doi:10.1016/j.icheatmasstransfer.2025.108880

[38] Ru, Y., Ali, A. B. M., Qader, K. H., Hussein, R. A., Jhala, R., Soliyeva, M., … Hekmatifar, M. (2025). Effect of nanoparticle size on the thermal performance of paraffin-O2 hybrid heat sink using molecular dynamics approach. International Communications in Heat and Mass Transfer, 163(108713), 108713. doi:10.1016/j.icheatmasstransfer.2025.108713

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