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用于描述聚合物压力-比容-温度行为的连续双域状态方程

Continuous Two-Domain Equations of State for the Description of the Pressure-Specific Volume-Temperature Behavior of Polymers.

作者信息

Wang Jian, Hopmann Christian, Röbig Malte, Hohlweck Tobias, Kahve Cemi, Alms Jonathan

机构信息

College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China.

Institute for Plastics Processing (IKV), RWTH Aachen University, 52074 Aachen, Germany.

出版信息

Polymers (Basel). 2020 Feb 11;12(2):409. doi: 10.3390/polym12020409.

Abstract

The two-domain Schmidt equation of state (EoS), which describes the pressure-specific volume-temperature (pvT) behavior of polymers in both the equilibrium molten/liquid state and non-equilibrium solid/glassy state, is often used in the simulation of polymer processing. However, this empirical model has a discontinuity problem and low fitting accuracy. This work derived a continuous two-domain pvT model with higher fitting accuracy compared with the Schmidt model. The cooling rate as an obvious influencing factor on the pvT behavior of polymers was also considered in the model. The interaction parameters of the equations were fitted with the experimental pvT data of an amorphous polymer, acrylonitrile-butadiene-styrene (ABS), and a semi-crystalline polymer, polypropylene (PP). The fitted results by the continuous two-domain EoS were in good agreement with the experimental data. The average absolute percentage deviations were 0.1% and 0.16% for the amorphous and semi-crystalline polymers, respectively. As a result, the present work provided a simple and useful model for the prediction of the specific volume of polymers as a function of temperature, pressure, and cooling rate.

摘要

双域施密特状态方程(EoS)用于描述聚合物在平衡熔融/液态和非平衡固态/玻璃态下的压力-比容-温度(pvT)行为,常用于聚合物加工模拟。然而,这个经验模型存在不连续问题且拟合精度较低。本工作推导了一个连续的双域pvT模型,与施密特模型相比具有更高的拟合精度。模型中还考虑了冷却速率这一对聚合物pvT行为有显著影响的因素。用无定形聚合物丙烯腈-丁二烯-苯乙烯(ABS)和半结晶聚合物聚丙烯(PP)的实验pvT数据对该方程的相互作用参数进行了拟合。连续双域EoS的拟合结果与实验数据吻合良好。无定形和半结晶聚合物的平均绝对百分比偏差分别为0.1%和0.16%。因此,本工作为预测聚合物比容随温度、压力和冷却速率的变化提供了一个简单且有用的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab84/7077649/19b4fe972359/polymers-12-00409-g001.jpg

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