Effect of Filler Morphology and Distribution State on the Linear and Nonlinear Mechanical Behavior of Nanofilled Elastomers

Abstract

We extend the model proposed by Merabia et al. [2008] regarding reinforcement mechanisms of filled elastomers. This model is based on the presence of glassy layers around filler particles which may bridge neighboring particles. The model was solved by Merabia et al. for spherical particles only and for a single dispersion state. However, experiments show that mechanical properties depend crucially on the complex shape of fillers as well as on their spatial distribution. We consider extensively both aspects in this article. We show that the distribution state of the fillers is key for controlling the reinforcement at high temperature. For a given distribution state, we show a strong effect of filler morphology on reinforcement. Distances between fillers are smaller with fractal aggregates, which leads to stronger reinforcement. Our model opens the path for the development of systems with tailored properties by tuning the filler distribution state and morphology.

Translation of segment scale stiffening into macroscale reinforcement in polymer nanocomposites

“…b) in polymers above T g is suggested to be the main reason for the nonclassical stiffening of PNCs by numerous authors . For instance, Tauban et al simulated the mechanical response of PNCs with retarded polymer segments within the particle structures of various morphologies based on previous experimental and theoretical results . The simulation results for relative storage modulus versus the temperature distance from T g ( T − T g ) exhibit very similar “ bell‐shape ” temperature dependence for highly filled PNCs as we observe in our experiments and which is plotted in Fig.…”

“…Percolation of the polymer with altered dynamics around NPs and their assemblies (as depicted in Fig. b) in polymers above T g is suggested to be the main reason for the nonclassical stiffening of PNCs by numerous authors . For instance, Tauban et al simulated the mechanical response of PNCs with retarded polymer segments within the particle structures of various morphologies based on previous experimental and theoretical results .…”

“…Despite extensive research, understanding the reinforcing mechanisms acting at various length scales of PNCs remains a challenging task. The proposed mechanisms include the modification of polymer properties beyond the properties of neat polymer chains via slowing down the polymer dynamics due to the interactions with nanoparticles and percolation of nanoparticles into load-bearing structures [16][17][18][19][21][22][23][24][25].…”

Analysis on Microstructure–Property Linkages of Filled Rubber Using Machine Learning and Molecular Dynamics Simulations

“…In addition, the difference between the distributions of the filler aggregates in the positive and negative examples extracted by the CNN was investigated because the CNN-extracted aggregate was a subset of the PH-extracted aggregate and could be considered a core structure, as described above, and some studies reported that the filler aggregate distribution was a factor determining the mechanical property [ 2 , 3 , 12 ]. The positions of the filler aggregates extracted by the CNN represented by the coordinates of the pixels with positive values were analyzed by the PH.…”

“…Filled rubber is a composite material fabricated from polymers and fine filler nanoparticles, and its mechanical properties are directly related to tire performance, such as rolling resistance, abrasion resistance, and wet traction [ 1 , 2 , 3 , 4 ]. To establish a relationship between the mechanical properties of the rubber and filler morphology, X-ray scattering, electronic microscopy, and atomic force microscopy studies were conducted [ 3 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ].…”