Influence of Preparation Conditions on Network Parameters of Sulfur-Cured Natural Rubber

• Published in: Macromolecules Vol. 34; no. 23; pp. 8107 - 8116
• Main Authors: Klüppel, M, Menge, H, Schmidt, H, Schneider, H, Schuster, R. H
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 06.11.2001
• Subjects: Applied sciences; Exact sciences and technology; Natural polymers; Natural rubber; Physicochemistry of polymers; Structure processing relationship; Vulcanization; Molecular structure; Vulcanizate; Crosslink density; Mechanical properties; Natural rubber; Experimental study; Property processing relationship; Sulfur
• ISSN: 0024-9297; 1520-5835
• DOI: 10.1021/ma010490v

The effect of initial chain length before cross-linking and sulfur/accelerator amount during curing of natural rubber samples on network parameters (effective chain density, gel fraction, amount of chain ends, entanglement density, trapping factor, and relaxation and correlation times) is investigated by means of proton NMR relaxation, equilibrium swelling, and stress−strain analysis. Remarkable differences are observed in the two sample series depending on the variable initial molar mass. The stress−strain data are evaluated with respect to a non-Gaussian tube model of rubber elasticity that considers the finite extensibility of network chains by referring to the path integral approach of Edwards and Vilgis (Rep. Prog. Phys. 1988, 51, 243; Polymer 1986, 27, 483). According to several experimental indications, we assume a nonaffine tube deformation law as first derived by Heinrich et al. (Adv. Polym. Sci. 1988, 85, 33). The NMR relaxation data are analyzed by considering three types of chains (gel, sol and chain ends). The best fit is obtained by assuming an anisotropic motion of the inter-cross-link chains and chain ends. The swelling data are analyzed by assuming phantom like chains. Within the framework of experimental errors, the network parameters evaluated from the three experimental techniques show fair agreement for both sample series.