Theoretical Aspects of Polymer Crystallization in Multiphase Systems

Liang, Guodong; Bao, Suping; Zhu, Fangming

doi:10.1016/b978-0-12-809453-2.00002-5

Cited by 4 publications

(2 citation statements)

References 89 publications

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“…Nucleation or the formation of active nuclei in the liquid phase acting as starting points for the appearance of crystals [1]. Two types of nucleation can be distinguished [4,5]:…”

Section: Crystallization From the Meltmentioning

confidence: 99%

Efficient identification of a flow-induced crystallization model for injection molding simulation

Saad,

Cruz,

Régnier

et al. 2024

Preprint

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Most commercial software used to simulate the injection molding process of semi-crystalline thermoplastic polymers do not explicitly take into account the polymer crystallization, which could lead to errors in the estimations of filling as well as warpage and shrinkage. This is mainly due to the common complexity of the models used to describe crystallization and the challenging respective model parameter identification under injection molding conditions. To close this gap, in this work we use a simple thermo-mechanical crystallization model to describe the flow-induced and quiescent crystallization of an unreinforced semi-crystalline thermoplastic material during injection molding. The crystallization model is implemented in the commercial software Autodesk Moldflow Insight 2021 using the Solver API feature alongside crystallization-dependent viscosity, PVT and solidification models. The model parameters were identified using a calibration workflow that employs surrogate models representing the simulated pressure results to perform a multi-objective optimization. The filling predictions as well as the calculated pressure fields are presented using the calibrated model parameters in comparison to those measured during the actual injection molding of a polyoxymethylene (POM) part using different process conditions. The results show major improvements in the estimations of the time-depending pressure field as well as the level of filling of the produced parts.

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“…Nucleation or the formation of active nuclei in the liquid phase acting as starting points for the appearance of crystals [1]. Two types of nucleation can be distinguished [4,5]:…”

Section: Crystallization From the Meltmentioning

confidence: 99%

Efficient identification of a flow-induced crystallization model for injection molding simulation

Saad,

Cruz,

Régnier

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…More details of the crystallization regimes are given in Sections 3.3.1 and 3.3.3. 𝑏 0 is the width of the chain (i.e., layer thickness perpendicular to the growth plane. For instance, in ideal PE crystals 𝑏 0 is the layer thickness perpendicular to (110) plane reflection, as reflected in a value of 0.411 nm [60] ), 𝜎 is the lateral surface free energy, 𝜎 𝑒 is the fold surface free energy, and as the 𝐾 𝑔 𝐴 value it depends on the input data (e.g., growth vs. overall crystallization), 𝑘 is the Boltzmann constant (1.38x10 -23 J/K), and ∆ℎ 𝑓 is the heat of fusion of a perfect crystal. The Thomas-Stavely [61] equation allows evaluating 𝜎 (Equation 9), and hence, 𝜎 𝑒 and 𝑞 (Equation 11).…”

Section: 3lauritzen and Hoffman Theorymentioning

confidence: 99%

Experimental and Data Fitting Guidelines for the Determination of Polymer Crystallization Kinetics

et al. 2022

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The crystallization kinetics of semicrystalline polymers is often studied with isothermal experiments and analyzed by fitting the data with analytical expressions of the Avrami and Lauritzen and Hoffman (LH) theories. To correctly carry out the analysis, precautions both in experiments and data fitting should be taken. Here, we systematically discussed the factors that influence the validity of the crystallization kinetics study. The basic concepts and fundamentals of the Avrami and LH theories were introduced at first. Then, experimental protocols were discussed in detail. To clarify the impact of various experimental parameters selected common polymers, i.e., polypropylene and polylactide, were studied using various experimental techniques (i.e., differential scanning calorimetry and polarized light optical microscopy). Common mistakes were simulated under conditions when non-ideal experimental parameters were applied. Furthermore, from a practical point of view, we show how to fit the experimental data to the Avrami and the LH theories, using an Origin ® App developed by us.

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Efficient identification of a flow-induced crystallization model for injection molding simulation

Saad,

Cruz,

Régnier

et al. 2024

Int J Adv Manuf Technol

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Theoretical Aspects of Polymer Crystallization in Multiphase Systems

Cited by 4 publications

References 89 publications

Efficient identification of a flow-induced crystallization model for injection molding simulation

Efficient identification of a flow-induced crystallization model for injection molding simulation

Experimental and Data Fitting Guidelines for the Determination of Polymer Crystallization Kinetics

Efficient identification of a flow-induced crystallization model for injection molding simulation

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