Akademik Veri Yönetim Sistemi
International Journal of Thermophysics, cilt.47, sa.1, 2026 (SCI-Expanded, Scopus)
The adoption of phase change materials (PCMs) is hindered by the complex characterization of their thermophysical properties, as most studies still address only a narrow range of properties. In this work, temperature-dependent measurements deliver accurate data and enable functional modeling essential for advancing practical applications. Thermophysical characterization of three organic PCMs was conducted, including two commercial paraffins (RT28HC and RT26) and industrially processed pork fat. The comprehensive experimental analysis (temperature-dependent characterization) was provided using differential scanning calorimetry (DSC), the transient hot wire (THW) method, density measurements, and rheological analysis. It was determined that paraffins RT26 and RT28HC have high values of latent heat, amounting to 198.1 kJ kg−1 and 215.8 kJ kg−1 for the endothermic process, respectively. Paraffin RT26 was observed to have two melting peaks, at 19.6 °C and 28.8 °C, while RT28HC showed one at 29.6 °C. The results also revealed that both paraffins in liquid state have almost identical values of thermal conductivity and diffusivity, while in solid state these values differ. Results obtained with DSC and THW deviate significantly from the manufacturer’s datasheet with discrepancies ranging from 10% to 44%. Pork fat showed lower values of latent heat, but slightly higher thermal conductivity and diffusivity. The melting peak of pork fat was measured at 34.8 °C. All three materials were found to behave like Newtonian fluids, with pork fat having the highest viscosity of 73.2 mPas at 20 °C. Specific heat capacity was also calculated for all samples, with the highest value of 2.559 kJ kg−1 K−1 determined for RT28HC at 60 °C. It was also discovered that the THW apparatus is able to detect the onset of liquid-to-solid transition in paraffins and pork fat. The key research outcomes of this work are useful for numerical modeling since reliable dataset of thermophysical properties is provided herein, and which is ultimately needed for accurate numerical modeling of PCM-based thermal energy storage (TES) systems.