Crystallization of cross-linked polyethylene by molecular dynamics simulation

Paajanen, Antti; Vaari, Jukka; Verho, Tuukka

doi:10.1016/j.polymer.2019.03.040

Cited by 60 publications

(40 citation statements)

References 32 publications

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“…The crystal cluster shown in Figure 1 corresponds to 600 carbon atoms, the approximate critical nucleus size for the conditions and molecular model used in this study (see [38]). The varying stem lengths in Figure 1 along with similar simulation snapshots from previous studies [17,19,20,[27][28][29][30][31][32][33][34] highlight that structural non-uniformity (heterogeneity) is present at the early stages of crystallization in a monodisperse polymer melt. This study contributes a detailed quantitative characterization and discussion of this structural heterogeneity.…”

Section: Resultssupporting

confidence: 71%

“…Based on the visual inspection of snapshots from nucleation simulations, Meyer and Müller-Plathe [26] noted in passing that nuclei could be composed of stems of varying length and contain a variable number of stems. Similarly, images of polymer crystal nuclei from previous work [15,17,19,20,23,[27][28][29][30][31][32][33][34][35][36] exhibit stem length variability, and sometimes quite pronounced variability, though these studies did not directly explore nor quantify the stem length distributions of nuclei. More recently, Hagita et al [37] demonstrated that stem length probability distributions broaden as linear and ring polyethylene melts crystallize, though multiple nuclei of differing size formed in their systems, obfuscating the structural details of individual nuclei.…”

Section: Introductionmentioning

confidence: 96%

“…With molecular simulations, one can directly study the molecular-level nanoscopic details of polymer crystal nuclei and stems during polymer crystallization. Previous in silico studies have probed stem-related properties and phenomena during crystallization, including the lamellar thickness of nuclei [14,15], intra-lamellar stem reordering mechanisms [16], stem growth rates as a function of stem length [16,17], the structural details of crystal growth fronts [16,18,19], and connections between average stem lengths and crystallization conditions (e.g., temperature and system composition) [20][21][22][23]. In particular, Doye and Frenkel [24] studied the distribution of stem lengths during the formation of crystalline layers from solution on polymer crystal growth faces of varying thickness, and thereby revealed that stem lengths can vary substantially.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Monodisperse Polymer Melts Crystallize via Structurally Polydisperse Nanoscale Clusters: Insights from Polyethylene

et al. 2020

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This study demonstrates that monodisperse entangled polymer melts crystallize via the formation of nanoscale nascent polymer crystals (i.e., nuclei) that exhibit substantial variability in terms of their constituent crystalline polymer chain segments (stems). More specifically, large-scale coarse-grain molecular simulations are used to quantify the evolution of stem length distributions and their properties during the formation of polymer nuclei in supercooled prototypical polyethylene melts. Stems can adopt a range of lengths within an individual nucleus (e.g., ∼1–10 nm) while two nuclei of comparable size can have markedly different stem distributions. As such, the attainment of chemically monodisperse polymer specimens is not sufficient to achieve physical uniformity and consistency. Furthermore, stem length distributions and their evolution indicate that polymer crystal nucleation (i.e., the initial emergence of a nascent crystal) is phenomenologically distinct from crystal growth. These results highlight that the tailoring of polymeric materials requires strategies for controlling polymer crystal nucleation and growth at the nanoscale.

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Section: Resultssupporting

confidence: 71%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Monodisperse Polymer Melts Crystallize via Structurally Polydisperse Nanoscale Clusters: Insights from Polyethylene

et al. 2020

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“…In addition, in the cases of PU 1–PU 4 and PU 2 –PU 5 pairs, the E-modulus decrease with crosslinking, which might be attributed to the fact that crosslinking may suppress the crystallization of the PPDL segments to some extent yielding moduli of lower values. A similar finding has been obtained for the linear/crosslinked polyethylene [ 32 , 33 ]. On the contrary, the crosslinked versions have higher ε R values than those of the linear ones.…”

Section: Resultssupporting

confidence: 87%

Block Copolymers of Poly(ω-Pentadecalactone) in Segmented Polyurethanes: Novel Biodegradable Shape Memory Polyurethanes

et al. 2020

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In this report, the synthesis of poly(ω-pentadecalactone) (PPDL) (co)polymers and their incorporation into polyurethanes (PUs) are reported. Optimal conditions for the ring-opening polymerization (ROP) of ω-pentadecalactone (PDL) using dibutyltin dilaurate catalyst were established. For the synthesis of linear and crosslinked PUs, 50 kDa poly(ε-caprolactone) (PCL) and 1,6-hexamethylenediisocyanate (HDI) were used. The obtained polyurethanes were characterized by Attenuated Total Reflectance Fourier-Transform Infrared spectroscopy (AT-FTIR), differential scanning calorimetry (DSC), and dynamical mechanical analysis (DMA). The DMA of the selected sample showed a rubbery plateau on the storage modulus versus temperature curve predicting shape memory behavior. Indeed, good shape memory performances were obtained with shape fixity (Rf) and shape recovery (Rr) ratios.

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“…The molecular dynamics simulation method is a good tool to illustrate the microscopic phenomenon of the molecule mass transfer in the packaging materials [21]. More detailed information and basic principles of the interaction between molecules and polymers can be obtained [22,23,24,25]. Börjesson et al performed Monte Carlo (MC) and MD simulation to calculate solubility coefficients and diffusion coefficients of oxygen and water in PE to obtain a microscopic diffusion mechanism [26].…”

Section: Introductionmentioning

confidence: 99%

Molecular Dynamics Simulation on the Diffusion of Flavor, O2 and H2O Molecules in LDPE Film

Sun

Zhu

2019

Materials

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The diffusion of five flavor organic molecules, including D-limonene, myrcene, ethyl hexanoate, 2-nonanone, and linalool in low density polyethylene (LDPE) film were investigated by combined experimental and molecular dynamics (MD) simulation studies. The diffusion coefficients derived from the prediction model, experimental determination, and MD simulation were compared, and the related microscopic diffusion mechanism was investigated. The effects of the presence of the flavor organic molecules on the diffusion of O2 and H2O in polyethylene (PE) were also studied by MD simulation. Results show that: The diffusion of five flavor molecules in LDPE is well followed to Fick’s second law by the immersion experiment; MD simulation indicates the dual mode diffusion mechanism of the flavor molecules is in LDPE; the diffusion coefficients from MD simulation are close to those from the experimental determination, but are slightly larger than those values; the presence of the flavor organic molecules hinders the diffusion of O2 and H2O, which can be well explained from the fraction of free volume (FFV) and interaction energy calculation results derived from MD simulation.

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Crystallization of cross-linked polyethylene by molecular dynamics simulation

Cited by 60 publications

References 32 publications

Monodisperse Polymer Melts Crystallize via Structurally Polydisperse Nanoscale Clusters: Insights from Polyethylene

Monodisperse Polymer Melts Crystallize via Structurally Polydisperse Nanoscale Clusters: Insights from Polyethylene

Block Copolymers of Poly(ω-Pentadecalactone) in Segmented Polyurethanes: Novel Biodegradable Shape Memory Polyurethanes

Molecular Dynamics Simulation on the Diffusion of Flavor, O2 and H2O Molecules in LDPE Film

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