Ionic Mixture of Binary Sugar Alcohols and a Polymer: Composition Optimization for Long-Term Thermal Energy Storage

Abstract

A new cold crystallizing material (NaPP) is analyzed for long-term thermal energy storage (TES). NaPP comprises a mixture of erythritol and mannitol as the binary phase change material (PCM) in the scaffold of polyvinyl alcohol (PVA) cross-linked with sodium citrate (SC). The material demonstrates a unique behavior of stable supercooling and vitrification during cooling and cold crystallization during subsequent heating, which enables a reliable long-term storage of the melting enthalpy and a controllable heat release. The use of several components in the material composition, however, impedes optimization of the thermal properties for the storage. As such, differential scanning calorimetry (DSC) was applied to expose the effect of the material components on the thermal properties, and the mixture experimental methodology (MEM) was used to model and optimize these properties. Successful modeling yielded a linear response for the thermal performance, which was significantly affected by the content of SC. Increasing the amount of SC (from 0 to 18 wt %) elevated the ionic strength of the system, which caused reduction in the amount of active PCM (confirmed by X-ray diffraction and DSC) and coarsening of the surface morphology (revealed by optical and scanning electron microscopies). This was also manifested as gradual disappearance of cold crystallization which limits the use of the material to compositions with the glass-transition temperature below −15 °C. MEM identified the optimal composition as 88.9 wt % PCM and 11.1 wt % SC, which showed a melting enthalpy of 194 J/g at 105 °C. Yet, the composition comprising 80 wt % PCM, 10 wt % PVA, and 10 wt % SC showed both high melting enthalpy (176 J/g) and shape stability facilitating larger scale applications. These compositions demonstrated a temperature increase of 10–20 °C during cold crystallization of a 10 g sample, confirming the suitability of the optimization model and the operation of the new material for long-term TES.