Depth-sensing indentation of soft matter

Rettler, Erik Franz-Josef GND

The advantages and current limitations of depth-sensing indentation (DSI) as a characterization tool for polymer materials are discussed throughout this thesis. It could be demonstrated that depth-sensing indentation studies of soft polymers are still a challenging field which is up to now only in its infancy. Within the summarized studies a base for the reliable characterization of polymer libraries was created. This included a careful verification of suitable indentation parameters as well as a cross-evaluation of the obtained results with complementary techniques, which ultimately allowed not only to determine the underlying intermolecular changes of the sample system, but also verified the level of precision which can currently be obtained by DSI. Particular problems arise for soft sample systems due to the material behavior that does not comply with the typical characteristics of hard materials for which DSI was originally designed. In Chapter 2 practical solutions for the investigation of soft polymers are provided. In particular the adjustment of the unloading cycle turned out to be sufficient to improve the data integrity significantly. The determined measurement protocol was applied in Chapter 3 to a polymer library consisting of poly(2-oxazoline)s with different molecular architecture. Different aspects which influence the mechanical properties could be determined: The crystallinity, branching and the influence of adsorbed water molecules. It was demonstrated in Chapter 4 that DSI can also be used to investigate time-dependent processes, like UV-induced crosslinking. A polystyrene / polybutadiene copolymer system with varying amounts of crosslinking agent was used to investigate this process by a stepwise irradiation/measurement cycle. The presented studies clearly show that DSI on soft sample systems inherently suffers from non-ideal sample behavior. A standardized application of DSI will certainly rely on an implementation of refined models to extract the mechanical properties.



Rettler, Erik Franz-Josef: Depth-sensing indentation of soft matter. 2014.


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