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Modifying the tait equation with cooling‐rate effects to predict the pressure–volume–temperature behaviors of amorphous polymers: Modeling and experiments
Author(s) -
Chang R. Y.,
Chen C. H.,
Su K. S.
Publication year - 1996
Publication title -
polymer engineering and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.503
H-Index - 111
eISSN - 1548-2634
pISSN - 0032-3888
DOI - 10.1002/pen.10574
Subject(s) - thermodynamics , work (physics) , materials science , polystyrene , volume (thermodynamics) , polymer , amorphous solid , glass transition , composite material , physics , chemistry , organic chemistry
Cooling‐rate effects play an important role in polymer processing because the materials experience rapid cooling when transferring from melt states to solid states. The traditional Tait equation has been used widely in representing the volumetric behaviors of polymers as a function of temperature and pressure, but not of cooling rate. Based on the dependence of glass‐transition temperature on cooling rate (i.e., θ = dT g /d log ∣ q ∣), the volumetric dependence on cooling rate is employed in this work to modify the traditional Tait P–V–T equation to become a time‐dependent P–V–T model. The physical meanings of the traditional Tait equation parameters are interpreted and, thereby, parameters in the new model are derived according to the material constant θ. The controlled cooling‐rate measurements of polymeric volumetric data have been performed in this work to verify the validity of the proposed model. Additionally, the material parameter θ, calculated from the measured data of polystyrene (PS) (Chi‐Mei PG‐33) in this work, equals 2.85 K, which is close to 2.86 K calculated from the Greiner‐Schwarzl work. Furthermore, a comparison of the predicted results with the experimental data both in this work and from literature is discussed under different pressures and various cooling rates. The results have indicated that the proposed non‐equilibrium P–V–T model closely correlates with experimental data.