Abstract
When characterizing the viscoelastic properties of polymers, shear rheological measurements are commonly the method of choice. These properties are known to affect extrusion and nozzle-based processes such as fiber melt spinning, cast film extrusion and 3D-printing. However, an adequate characterization of shear thinning polymers can be challenging and still insufficient to not only describe but predict process relevant influences. Furthermore, the evaluation of rheological model systems in literature is mostly based on stress–relaxation experiments, which are rarely available for various polymeric materials. Therefore, a simple approach is presented, that can be used to evaluate and benchmark a wide range of rheological model systems based on commonly accessible frequency sweep data. The approach is validated by analyzing alginate PH176 solutions of various concentrations, a thermoplastic poly-urethane (TPU) Elastollan 1180A melt, the liquid silicon rubber Elastosil 7670 and a polycaprolactone (PCL) fiber-alginate composite system. The used rheological model systems, consisting of simple springs and dashpots, are suitable for the description of complex, viscoelastic material properties that can be observed for polymer solutions and gel-like systems. After revealing a suitable model system for describing those material properties, the determination and evaluation of relevant model parameters can take place. We present a detailed guideline for the systematic parameter revelation using alginate solutions of different concentrations as example. Furthermore, a starting point for future correlations of strut spreading in 3D-bioprinting and model parameters is revealed. This work establishes the basis for a better understanding and potential predictability of key parameters for various fabrication techniques.
Highlights
The prediction of material behavior can lead to immense savings, monetary and time wise, in various industrial processes
The evaluation of rheological model systems in literature is mostly based on stress–relaxation experiments, which are rarely available for various polymeric materials
The approach is validated by analyzing alginate PH176 solutions of various concentrations, a thermoplastic poly-urethane (TPU) Elastollan 1180A melt, the liquid silicon rubber
Summary
The prediction of material behavior can lead to immense savings, monetary and time wise, in various industrial processes. A commonly chosen method for such predictions is the analysis of rheological material properties. The subsequent modelling of generated data can potentially further expand its predictability exceeding the underlying experimental range. Due to the advances in computational engineering and technology, many researches focus on constitutive modeling, based on linear and nonlinear continuum mechanics [1,2] and computational modeling using a variety of finite element approaches [3,4]. Computational simulations are often highly specific due to the chosen boundary conditions, while continuum mechanical approaches require a deep knowledge of the underlying physical and mathematical tools. A more accessible approach for rheological modelling
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