Abstract
In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.
Highlights
Polymers are of great importance in industrial and consumer related applications.Their low costs, easy processability, and good performance characteristics give polymers versatile usage options
As we focus on mimicking macroscopic processing conditions we stretch, cool and relax our systems under two different approaches that both typically occur in real-life processing: (1) “free conditions”, where the system is able to shrink immediately after stretching; (2) “fixed conditions”, where the box size is fixed in every direction of space to mimic the effect of a mold constraint
We describe the different effects that occur in priorly stretched polyethylene systems
Summary
Polymers are of great importance in industrial and consumer related applications. Their low costs, easy processability, and good performance characteristics give polymers versatile usage options. Individual component design is a difficult procedure and in many cases is characterized by strong compromises due to their distinctive time, temperature, and load-dependent behavior. For the development of an optimized product at minimum material usage, the use of computer-aided-engineering (CAE) has become increasingly important over the past several years. Simulation results strongly depend on the input data for the analysis procedure [1,2,3,4,5]. The material description, consisting of the choice of the material model and the related material properties, influences the results. Performing the necessary experiments is associated with high costs, especially if different types of experiments are needed to fully characterize the material’s behavior [1,2,3]
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