Kinetics and Morphology of Flow Induced Polymer Crystallization in 3D Shear Flow Investigated by Monte Carlo Simulation

This special issue discusses recent advances in computer simulation studies of crystal growth. Crystal growth is a key to innovation in science and technology. Owing to recent progress in computer performance, computer simulation studies of crystal growth have become increasingly important. This special issue covers a variety of simulation methods, including the Monte Carlo, molecular dynamics, first-principles, multiscale, and continuum simulation methods, which are used for studies on the fundamentals and applications of crystal growth and related phenomena for different materials, such as hard-sphere systems, ice, organic crystals, semiconductors, and graphene.

Section: Organic Moleculesmentioning

confidence: 58%

“…Related to continuum simulations, Ruan used a morphology evolution model and the MC method for simulations of polymer crystallization in a shear flow [15]. Z. Liu et al used a particle level set method [16] for simulations of polymer crystallization under isothermal and temperature gradient conditions [17].…”

Section: Continuum Simulationsmentioning

confidence: 99%

Computer Simulations: Essential Tools for Crystal Growth Studies

Nada

2018

“…The morphological Monte Carlo method [9,11] was used to capture the growth fronts of spherulites. The algorithm is given as follows: STEP 1: Initialization.…”

Section: Methodsmentioning

confidence: 99%

“…In the computer simulation of polymer crystalline morphology, most work is based on isotropic crystal morphology. Methods include the cellular automata method [4,5], the pixel coloring method [6][7][8], the Monte Carlo method [9][10][11], the Level Set method [12,13], and the phase field method [14], etc. Some researchers [15][16][17] considered the anisotropic growth of spherulites and established that both normal and radial growth models apply.…”

Section: Introductionmentioning

confidence: 99%

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

Ruan

2019

Self Cite

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.

“…The method of mesh generation and implementation of Monte Carlo method are not described here. We refer our previous work [8,19,20] for more details. The validity of our Monte Carlo method is proven in our previous work by the comparison of the experimental result taken by Pawlak and Piorkowska and the numerical work taken by Ouyang et al [3,7,8].…”

Section: Monte Carlo Methodsmentioning

confidence: 99%

A Note for Probabilistic Model of Polymer Crystallization in Temperature Gradients

Ruan

2019

Self Cite

A polymer crystallization kinetics model is the most important way to characterize the crystallization rate of polymers. Because polymers are poor heat conductors, the cooling of thick-walled shapes results in temperature gradients. Piorkowska (Piorkowska, E. J. Appl. Polym. Sci., 2002, 86: 1351–1362.) derived the probabilistic analytical model of polymer crystallization in temperature gradients based on the Avrami equation. However, there are some misunderstandings when using this model. Here, isotactic polypropylene (iPP) is chosen as a model polymer and its crystallization is studied in a temperature gradient field. Based on the results of the Monte Carlo method, the probabilistic model methodology is discussed. The results show that when the product has a large temperature gradient and a large temperature difference, the probabilistic model cannot be used directly; instead, it is necessary to use the average probabilistic model. This means that the sample should be divided into several smaller parts and the probabilistic model used separately for each small part. The values are then averaged to obtain the mean conversion degree of the melt into spherulites for the whole product. The effects of the division number are also discussed. The goal of the present paper is to better understand the polymer crystallization kinetics model in terms of temperature gradients.