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Open AccessArticle

Morphological Monte Carlo Simulation for Crystallization of Isotactic Polypropylene in a Temperature Gradient

School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China
Crystals 2019, 9(4), 213; https://doi.org/10.3390/cryst9040213
Received: 4 March 2019 / Revised: 15 April 2019 / Accepted: 18 April 2019 / Published: 20 April 2019
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Abstract

Polymers are poor heat conductors, so the cooling of thick-walled shapes results in temperature gradients. Here, isotactic polypropylene (iPP) is chosen as a model polymer for the study of polymer crystallization in a temperature gradient field. The morphological Monte Carlo algorithm is applied, combined with the radius growth model, to predict the growth of spherulites. Through comparison of the two numerical solutions, analytical solution and experimental data, the validity of the morphological Monte Carlo algorithm is demonstrated. In addition, the roles of central temperature, temperature gradient for the evolution of spherulites, and the conversion degree of the melt into spherulites are considered. The results of the study show that increases in central temperature and temperature gradient can increase the anisotropy of spherulites. Isothermal crystallization and crystallization in a temperature gradient field are compared, and the differences are considered. Results show that when the central temperature is below 125 °C, and when the temperature gradients are less than 15 K/mm and 27 K/mm, the differences in the conversion degree of the melt into spherulites are less than 2% and 5%, respectively. Therefore, crystallization under such temperature gradient conditions can be simplified as isothermal crystallization. View Full-Text
Keywords: Monte Carlo simulation; temperature gradient; crystallization; anisotropic Monte Carlo simulation; temperature gradient; crystallization; anisotropic
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Ruan, C. Morphological Monte Carlo Simulation for Crystallization of Isotactic Polypropylene in a Temperature Gradient. Crystals 2019, 9, 213.

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