Journal
THERMOCHIMICA ACTA
Volume 722, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.tca.2023.179456
Keywords
Heat capacity; Polyvinylpyrrolidone; Glass transition; Skeletal vibration; Group vibration; Deep neural network
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In this study, the heat capacity of dried PVP was measured to determine the recommended values for further analysis of the water state in biocompatible PVP. The heat capacity of the solid state was analyzed using group vibrational spectrum and skeletal vibrations. The heat capacity of the liquid was fitted to a linear function, and the change in heat capacity of amorphous PVP at the glass transition temperature was determined.
As a first step in the analysis of the water state in biocompatible poly(N-vinylpyrrolidone) (PVP), the heat ca-pacity of dried PVP was measured over a temperature range 15-520 K by adiabatic calorimetry and differential scanning calorimetry (DSC) to determine the recommended values. Based on these values, the heat capacity of the sold state was analyzed using an approximate group vibrational spectrum and skeletal vibrations. The 2-pyr-rolidone-ring group vibrations of 34 modes were determined from the ab initio calculations based on density functional theory regarding the hydrogen-terminated dimer of PVP. The six skeletal vibrational modes are well represented by a Tarasov function with theta temperature of Theta 1 = 646.0 K and Theta 3 = 81.9 K, which were obtained from a three-step mesh optimization. The heat capacity of the liquid was fitted to a linear function: CPliquid = 0.2909 T + 101.9 (in J K-1 mol-1). The change in heat capacity, Delta CP0, of amorphous PVP at the glass transition temperature (440 K) is 29.3 J K-1 mol-1. The values of Delta CP0, Theta 1 and Theta 3 agreed with the deep-learning pre-dictions based on the ATHAS data bank with a relative error within 20%. Using the obtained characteristic parameters and group vibrations, the calculated heat capacities as a function of temperature (which correspond to the DSC baseline) were determined.
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