Recent advances on nano-enhanced phase change materials (NEPCMs) for photovoltaic thermal management and role of machine learning: A review of fundamentals, preparation, characterization, and thermo-physical properties

Phase change material (PCM) has attracted research attentions as a passive cooling method due to its ability to store and release heat in latent form. However, its capability in storing and releasing heat is effected by its low thermal conductivity. To address this problem nanoparticle are dispersed inside the PCM to produce nano enhanced phase change material (NEPCM) with an improved thermal conductivity. Yet, this approach is not without challenges. The PCM thermo-physical properties changes and the PCM is subjected to many issues such as agglomeration, sedimentation, change in melting and solidification temperatures, and reduction in latent heat capacity which can't be ignored. This study tends to delve into the fundamentals, preparation, characterization, and thermo-physical properties of NEPCM, with a focus on their applications in photovoltaic thermal management and role of machine learning. In this work, a bibliometric analysis is done to show trends and research directions in this field. The fundamentals and the working theory of PV panels with a look at the commercial and latest advances in PVs are addressed. Different categories and types of PCM as well as of nanoparticles are tackled. Moreover, a discussion of various preparation methods, characterization techniques, and different stability enhancers methods are presented. In a comprehensive study, the article reviews, summarizes, and discusses previous work done in altering the PCM thermo-physical properties using metallic, metallic oxide, quantum dots, carbon based, and hybrid nano particles. The paper also summarizes and discuss different work done on enhancing the performance of PV using NEPCM. Moreover, the article highlights the importance of machine learning algorithms in building a clear science for the interaction between PCM and nanoparticles and its effect on PV performance. Finally, a discussion, and key findings are demonstrated with an outlook on NEPCM in PV thermal management. The main results show that using NEPCM can reduce the PV temperature up to 23 K and improve the efficiency up to 18.16 %.