Cold energy storage devices are widely used for coping with the mismatch between thermal energy production and demand. These devices can store cold thermal energy and return it when required. Besides the countless advantages of these devices, their freezing rate is sluggish, therefore researchers are continuously searching for techniques to improve their operating speed. This paper tries to address this problem by simultaneously combining a network of plate fins and various types of carbon-based nanomaterials (NMs) in a series of complex computational fluid dynamics (CFD) simulations that are validated by published experimental results. Horizontal, vertical, and the combination of these two plate-fin arrangements are tested and compared to the base model. Subsequently, several carbon-based NMs, including SWCNT, MWCNT, and graphene-oxide NMs are utilized to further improve the process. The influence of these fin networks, nanoparticle types, and their volume- and mass-based concentrations within the PCM container are studied and discussed. According to the results, carbon-based NMs exhibit superior performance compared to metal-oxide NMs, so that at identical NM volume and mass fractions, MWCNT particles present a 2.77% and 17.72% faster freezing rate than the CuO particles. The combination of plate-fin network and MWCNT particles is a promising technique that can expedite the ice formation rate by up to 70.14%.
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