Experimental analysis of carbon-based Phase Change Materials composites for a fast numerical design of cold energy storage systems

The adoption of highly conductive nanofillers within a phase change material (PCM) matrix is considered a promising solution to enhance the effective thermal conductivity of the resulting nanocomposite, thus possibly increasing specific power and energy density in latent thermal energy storage plants. However, the expected significant property enhancement of such composite materials is often unmet, with one of the key reason being the critical and poorly studied role played by too high thermal resistances at the nanofiller-matrix interfaces limiting the heat flux within the material. One of the contributions of this work is providing an estimate of the value for such resistances in relevant cases for cold energy storage found to be in the range of: 3 center dot 10(-7) 3 center dot 10(-6) [m(2)K/W]. Those estimates have been obtained by exploiting a synergistic study combining a numerical analysis, based on mean-field theory calculations and finite element simulations, with experimental assessment of the resulting properties of nanocomposite samples. In addition, we show how the numerically predicted values of the effective thermal conductivity can be used as input data in an approximated numerical analysis of a lab-scale shell & tube storage tank connected to a daily domestic user, adopted for the storage of sub ambient temperature thermal energy. This leads to a novel multi-scale analysis coupling the material effective properties and the expected behavior at the plant level, thus allowing a preliminary computationally efficient optimization of the storage system under analysis. Compared to computational fluid dynamics simulations, the approximated design approach proved to predict the propagation front up to 30% accuracy.

Automated summary

The adoption of highly conductive nanofillers within a phase change material matrix is seen as a potential solution to improve the thermal conductivity and energy storage capacity. However, the performance enhancement is often limited due to high thermal resistances at the nanofiller-matrix interfaces. This study provides estimates of these resistances and demonstrates how numerical analysis can be used for the optimization of a storage system.