Exploring the impact of particle stability, size, and morphology on nanofluid thermal conductivity: A comprehensive review for energy applications

Abstract

Recent advancements enhance the efficiency of energy conversion processes and leverage nanofluids—novel thermal fluids with nanoparticles (under 100 nm) suspended in conventional fluids. These nanofluids significantly alter thermophysical properties, notably thermal conductivity, which is crucial for evaluating their thermal performance. Despite three decades of intensive research, disagreements persist due to a lack of comprehensive data on how particle size, shape, stability, and others influence thermal conductivity. This review tries to fill this literature gap by critically reviewing how the characteristics that distinguish nanofluids from their micrometer-sized counterparts affect the stability and convective heat transfer. The study compares experimental results in a systemic way that addresses the reported inconsistencies and provides a general summary of the thermal behavior of nanofluids in energy systems. It has also pointed out the lack of reliable hybrid models considering all parameters affecting thermal conductivity. The current study assembles data from different analyses showing that a particle size within the 10-50 nm range may enhance thermal conductivity, depending on the base-fluid used. Likewise, the morphological options available, namely, spherical, ellipsoid, platelet, and blade-like, all have given promise for enhancing thermal conductivity, hence considering morphological issues. Finally, stability, defined by the zeta potential analyses, forms a vital criterion for the long-term sustainability of these enhancements. By consolidating experimental results across different research groups, this review highlights the variability and sometimes contradictory findings in thermal conductivity enhancements, ranging from negligible increases to over 50% improvement in specific nanofluids systems. The absence of reliable hybrid models encapsulating all influencing parameters for predicting thermal conductivity is critically addressed. It is concluded by identifying the main challenges in the field and offering recommendations for standardizing measurement techniques, which include the need for a unified model capable of predicting thermal conductivity enhancements with an accuracy of $\pm$5%.