화학공학소재연구정보센터
Macromolecules, Vol.44, No.20, 8106-8115, 2011
Linking Network Microstructure to Macroscopic Properties of Siloxane Elastomers Using Combined Nuclear Magnetic Resonance and Mesoscale Computational Modeling
It is well established that many fundamental properties of polymer materials are directly governed by chain dynamics, and both experimental and computational efforts to probe this motional spectrum have been manifold. Recently, multiple quantum (MQ) nuclear magnetic resonance (NMR) has afforded the capability to extract meaningful quantities from such measurements, namely, an effective molecular weight distribution between various topological constraints (cross-links, entanglements, etc.). We describe herein the results of recent work on model end-linked poly(dimethylsiloxane) networks where mesoscale computational studies were used to calculate elastic moduli using the NMR-derived molecular weight distributions as their sole input. These results are then compared to dynamic mechanical analysis measurements to assess the degree to which this new methodology can predict the mechanical properties of these simple elastomers. The results of this initial study suggest a high confidence in prediction and portend a nondestructive methodology capable of monitoring subtle changes in network structural motifs associated with material performance and age.