Dynamic mechanical properties are critical in the evaluation of materials with viscoelastic behavior. Various techniques, including dynamic mechanical analysis (DMA), rheology, nanoindentation, and others have been developed for this purpose and typically report complex modulus. Each of these techniques has strengths and weaknesses depending on sample geometry and length scale, mechanical properties, and skill of the user. In many industry applications, techniques may also be blindly applied according to a standard procedure without optimization for a specific sample. This can pose challenges for correct characterization of novel materials, and some techniques are more robust to agnostic application than others. A relative assessment of dynamic mechanical techniques is important when considering the appropriate technique to use to characterize a material. It also has bearing on organizations with limited resources that must strategically select one or two capabilities to meet as broad a set of materials as possible. The purpose of this study was to evaluate the measurement characteristics (e.g., precision and bias) of a selection of six dynamic mechanical test methods on a range of polymeric materials. Such a comprehensive comparison of dynamic mechanical testing methods was not identified in the literature. We also considered other technical characteristics of the techniques that influence their usability and strategic value to a laboratory and introduce a novel use of the House of Quality method to systematically compare measurement techniques.
The selected methods spanned a range of length scales, frequency ranges, and prevalence of use. DMA, rheology, and oscillatory loading using a servohydraulic tensile tester were evaluated as traditional bulk techniques. Determination of complex modulus by beam vibration was also considered as a bulk technique. At a small length scale, both an oscillatory nanoindentation method and AFM were evaluated. Each method was employed to evaluate samples of polycarbonate, polypropylene, amorphous PET, and semi-crystalline PET. A measurement systems analysis (MSA) based on the ANOVA methods outlined in ASTM E2782 was conducted using storage modulus data obtained at 1 Hz. Additional correlations over a range of frequencies were tested between rheology/DMA and the remaining methods. Note that no attempts were made to optimize data collection for the test specimens. Rather, typical test methods were applied in order to simulate the type of results that would be expected in typical industrial characterization of materials.
Data indicated low levels of repeatability error (<5%) for DMA, rheology, and nanoindentation. Biases were material dependent, indicating nonlinearity in the measurement systems. Nanoindentation and AFM results differed from the other techniques for PET samples, where anisotropy is believed to have affected in-plane versus out-of-plane measurements. Tensile-tester based results were generally poor and were determined to be related to the controllability of the actuator relative to the size of test specimens. The vibrations-based test method showed good agreement with time-temperature superposition determined properties from DMA. This result is particularly interesting since the vibrations technique directly accesses higher frequency responses and does not rely on time-temperature superposition, which is not suitable for all materials.
MSA results were subsequently evaluated along with other technical attributes of the instruments using the House of Quality method. Technical attributes were weighted against a set of “user demands” that reflect the qualitative expectations often placed on measurement systems. Based on this analysis, we determined that DMA and rheology provide the broadest capability while remaining robust and easy to use. Other techniques, such as nanoindentation and vibrations, have unique qualities that fulfill niche applications where DMA and rheology are not suitable. This analysis provides an industry-relevant evaluation of measurement techniques and demonstrates a framework for evaluating the capabilities of analytical equipment relative to organizational needs.
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