Recent Advances in Nanofluids for Thermal and Energy Systems

Submission Deadline: 31 August 2027 View: 31 Submit to Special Issue

Guest Editor(s)

Dr. Mohammed Yahya

Email: mohammed.yahya@torontomu.ca

Affiliation: Mechanical Engineering, Toronto Metropolitan University, Toronto, Canada

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Research Interests: nanofluids, heat transfer enhancement, thermal energy systems, advanced heat exchangers, TPMS structures, computational fluid dynamics (CFD), experimental thermal-fluid sciences, and machine learning.

Prof. Junfeng Zhang

Email: jzhang@laurentian.ca

Affiliation: School of Engineering and Computer Science, Laurentian University, Sudbury, Canada

Homepage:

Research Interests: nanofluids, heat and mass transfer, porous flows, numerical methods, lattice Boltzmann method, microscopic blood flows

Summary

1. Introduction and Importance

Nanofluids have gained significant attention due to their potential to enhance heat transfer efficiency in thermal and energy systems. Their applications include heat exchangers, cooling systems, renewable energy technologies, energy storage, electronics cooling, and industrial thermal processes. Understanding nanofluid fluid dynamics, transport behaviors and thermal performance is essential for the effective design and operation of these systems. Recent advances in computational fluid dynamics, experimental techniques, and artificial intelligence provide new opportunities to investigate and optimize nanofluid performance.

2. Aim and Scope

This Special Issue aims to present recent advances in nanofluid science and engineering, focusing on heat transfer, fluid dynamics, thermophysical properties, numerical modelling, optimization, and practical thermal-energy applications. Experimental, numerical, theoretical, and AI-assisted studies involving conventional, hybrid, and advanced nanofluids are encouraged.

3. Suggested Themes

Suggested topics include thermophysical and transport properties, nanofluid fluid dynamics, heat and mass transfer enhancement, laminar and turbulent flows, pressure drop and pumping performance, hybrid nanofluids, numerical modelling, experimental validation, thermal management, renewable energy, energy storage, AI and machine learning applications, and optimization of advanced thermal-fluid systems.

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