Effects of nanoparticle aggregation on the thermal conductivity of nanofluids: A comprehensive review based on multiscale methods

Abstract

Nanofluids, enhanced by the addition of nanoparticles, have attracted significant interest for their superior thermal conductivity, making them ideal for applications in thermal management and energy storage. However, nanoparticle aggregation within the base fluid remains a critical challenge, as it disrupts uniform dispersion and alters heat conduction pathways, thereby changing overall thermodynamic characteristics. This comprehensive review examines the impact of nanoparticle aggregation on the thermal conductivity of nanofluids through theoretical models, experimental studies, and multi-scale simulations. It explores the primary models used to predict thermal conductivity, compares their accuracy and applicability, and discusses advanced experimental techniques for controlling particle aggregation, such as surface modification, particle concentration adjustment, and dispersion optimization. Additionally, the review highlights simulation approaches at microscopic, mesoscopic, and macroscopic scales that elucidate the mechanisms by which aggregation affects thermal properties. Through these analyses, the applicability of different models under various working conditions and application requirements was clarified, the intrinsic relationship between aggregation levels and thermal conductivity changes was revealed, and critical references and guidance were provided for future research and applications involving nanofluids. Despite significant advancements, challenges such as accurately predicting aggregation behavior in various fluid environments and enhancing dispersion stability persist. Future research directions include advancing experimental techniques for extreme conditions and cross-scale simulation to better understand and optimize the thermal performance of nanofluids, thereby facilitating their broader application in high-efficiency thermal systems.