journal article·2023-10

Controllable preparation and thermal properties of SiC spherical high temperature shape-stable composite phase change materials based on gel-casting

Yicheng Hou, Jun Qiu, Wei Wang, Xibo He, Zhen Wang, Yong Shuai

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Abstract

The development of high-temperature composite phase change materials (CPCMs) suitable for mass-production and high-performance is still a very urgent problem in the efficient utilization of renewable energy. In this study, a SiC spherical high-temperature CPCMs based on aqueous gel-casting suitable for batch molding using commercially available silicone molds is proposed. The porosity of the porous SiC framework can be adjusted by changing the content of starch granules in the slurry. The sample containing 20 wt% starch has relatively high open porosity and thermal conductivity, which is considered to be close to the optimal formulation of CPCMs. This formula possesses a high thermal conductivity of 10.2 W·m −1·k −1 benefiting from the continuous thermal transport channels consisting of the uniformly distributed large spherical pores and interconnected small pores. Meanwhile, the thermal storage density of the CPCMs reaches 395.21 J·g −1 in the temperature range of 550 ℃ and 750 ℃ since up to 89.06% of the pores are filled with molten salts. At the same time, the CPCMs exhibit excellent cycle stability in 100 thermal cycles. In particular, these CPCMs can be easily integrated into thermal energy storage (TES) system. Based on the rapid heat storage simulation of the C-D model, the packed-bed latent thermal energy storage system containing spherical CPCMs will have a more uniform temperature distribution and a 26.7% reduction in charging time compared with the traditional packed-bed system. This work provides a new reference for the design of spherical CPCMs in TES systems.
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Research context

OpenAlex topics: Phase Change Materials Research · Adsorption and Cooling Systems · Thermal properties of materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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