ABSTRACT
Performing conventional mechanical characterization techniques on soft materials can be challenging due to issues such as limited sample volumes and clamping difficulties. Deep indentation and puncture is a promising alternative as it is an information-rich measurement with the potential to be performed in a high-throughput manner. Despite its promise, the method lacks standardized protocols, and open questions remain about its possible limitations. Addressing these shortcomings is vital to ensure consistent methodology, measurements, and interpretation across samples and labs. To fill this gap, we examine the role of finite sample dimensions (and by extension, volume) on measured forces to determine the sample geometry needed to perform and unambiguously interpret puncture tests. Through measurements of puncture on a well-characterized elastomer using systematically varied sample dimensions, we show that the apparent mechanical response of a material is in fact sensitive to near-wall effects, and that additional properties, such as the sliding friction coefficient, can only be extracted in the larger dimension case where such effects are negligible.
ABSTRACT
Manufacturers use a large number of components in the production of modern rubber products. The selection of the constituents of the rubber recipe is primarily determined by the purpose of use. The different fields of applications of rubbers require the presence of appropriate mechanical properties. In this respect, it can be useful to know which substances forming the rubber recipe have significant influence on the different mechanical properties. In this study, the statistical analysis of the influence of rubber components on the hardness of natural rubber (NR) is proposed based on literature review. Based on the literature data, various statistical analyses, like linear regression, constrained linear regression, Ridge regression, Ridge sparse regression and binary classification decision trees were performed to determine which rubber components have the most significant effect on the hardness. In the statistical analyses, the effect of a total of 42 constituents of rubber compound on hardness was investigated. Most of the applied statistical methods confirmed that the traditional frequently used rubber components, such as carbon black and sulfur, have a primary effect on the hardness. However, the substances forming the rubber compound that are not widely used in practice or newly developed components appear differently in the lists of significant additives obtained by the different statistical methods.
