Review of supercooling suppression of phase change materials based on nanoparticles

Abstract

The phenomenon of supercooling in phase change materials has been a major obstacle to the effective use of these materials in thermal energy storage systems. Numerous studies have shown that nanoparticles display significant advantages over other methods of supercooling inhibition in terms of increased nucleation rate, enhanced thermal conductivity, reduced supercooling, and improved cycling stability. Yet, the mechanism of supercooling inhibition by nanoparticles has not been comprehensively discussed or reviewed in published articles. The objective of this review is to provide a comprehensive analysis of the mechanisms by which nanoparticles promote nucleation and reduce supercooling in phase change materials, as well as to discuss the most influential factors such as the type, concentration, and size of the nanoparticles, as well as ultrasonic and synergistic effects. Additionally, the paper focuses on an overview of recent advances in the application of machine learning to control the supercooling of nanofluid phase change materials. The potential for practical applications of machine learning techniques to enhance the thermophysical properties of phase change materials and suppress phase change material supercooling is one of our major findings.