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Updated: Dec 19, 2025

Studying Large Amplitude Oscillatory Shear Response of Soft Materials
Published on: April 25, 2019
A Novel Simple Approach to Material Parameters from Commonly Accessible Rheometer Data
S Schrüfer1,2, D Sonnleitner3, G Lang3
1Department of Materials Science and Engineering, Institute of Polymer Materials, University Erlangen-Nuremberg, Martensstraße 7, 91058 Erlangen, Germany.
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.
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