Tetraphenylphenyl-modified damping additives for silicone rubber: Experimental and molecular simulation investigation

• Main Authors: Lin Zhu, Xin Chen, Ruirui Shi, Hao Zhang, Rui Han, Xiao Cheng, Chuanjian Zhou
• Format: Article
• Language: English
• Published: Elsevier 2021-04-01
• Series: Materials & Design
• Subjects: Damping property; Silicone composite; Compatibility; Interaction mechanism; Molecular simulation
• Online Access: http://www.sciencedirect.com/science/article/pii/S0264127521001040

The incorporation of additive into rubber matrix is a promising approach toward desirable damping materials. However, the design and selection of additives remain a challenge. Herein, tetraphenylphenyl-modified damping additives were synthesized by Diels-Alder chemistry. The effects of additives on the mechanical and morphological properties of phenyl silicone rubber were investigated experimentally and computationally. Experimental results showed that the addition of additives substantially improved the damping while preserving excellent mechanical properties. The composite with 15 phr tetraphenylphenyl-modified dimethylpolysiloxane (TPP-VMPS-3) exhibited a broad plateau of loss factor (tanδ >0.25) from −50 to 30 °C, effectively expanding the damping temperature range. When the composite incorporated 15 phr tetraphenylphenyl-modified methylphenylpolysiloxane (TPP-VPMPS), the tanδ increased from 0.09 to 0.21 at 150 °C, showing excellent high-temperature damping performance. Furthermore, molecular dynamics (MD) simulation provided mechanistic insights into the phase separation and relaxation behavior of composites by studying the compatibility, interaction mechanism, and diffusion characteristic. The results demonstrated that the enhanced intermolecular interactions and steric hindrance were the crucial reason for the improvement of damping. This work shed light on the relationship among composition, structure and property, which may provide a framework for preparing high-performance silicone composites via the synergistic experimental and computational method.