Supercooling of salt hydrates is a challenge in engineering these materials for thermal energy storage. Understanding supercooling in a salt hydrate such as sodium sulfate decahydrate (SSD) is further complicated by scatter in basic data reported for phase transitions. To understand the role of extensive effects in measurement uncertainties, we model the probability of nucleation as a function of sample size to quantify its relationship with the statistical uncertainty in supercooling. We further conduct well-controlled measurements using differential scanning calorimetry (DSC) and the temperature-history method (T-history) that span sample volume by three orders of magnitude. Finally, we simulate these experiments using basic heat transfer modeling to explore the source of discrepancies between DSC and T-history data. This work shows that extensive effects are dominant, explains why there is scatter in the literature data and then provides insights into how to correctly set conditions and interpret data. This is a crucial step toward realizing large-scale practical thermal energy storage. Additionally, this work suggests that while DSC should use the slower ramp rate of 1 °C min −1 to avoid issues related to heat compensation, it is advantageous to use a faster ramp rate of 4 °C min −1 in the T-history method for reduced errors and measurement times. • Nucleation probability model explains the mass-dependent effect on supercooling. • Experimental comparison between DSC and the T-history method follows the model. • Small salt hydrate mass reduces nucleation probability, causing larger supercooling. • Lower measured energy storage density is observed as a result of phase segregation. • The extensive effect on supercooling is more pronounced in cycling.
Lee et al. (Fri,) studied this question.