investigated the effects of the particle size on dynamic mechanical and physical
properties. They have proved that nanofiller-MgO (size: 20–50 nm) in rubbery
composites causes a significant increase in G
0 and G
00 modulus, and also, at higher
values of tangent δ a clear Payne effect was observed [61].
Very interesting studies of natural rubber reinforcement with ZnO nanoparticles
were performed by scientists from India, under the direction of Sabu Thomas
[62]. The goal of these studies was to characterize the viscoelastic behavior and
reinforcement mechanism of ZnO nanoparticles introduced into the rubber matrix.
They have presented a constrained polymer model based on a rubbery region and a
ZnO nanoparticle. Very interestingly, the authors presented a core-shell morphology model and constrained polymer model to explain the constrained polymer
chains in NR/ZnO nanocomposites [62]. Thanks to this research and the proposed
models, it is possible to understand the behavior of nanofillers in the polymer matrix
and maybe in the future to develop an ideal nanofiller for use in the rubber matrix.
4 Summary, Conclusions and Future Outlook
In this chapter, the rheology and the dynamic-mechanical behavior of
iso-dimensional rubber nanocomposites in the non-linear zone have been reviewed.
Briefly described were the effect of nanofiller on the nonlinear viscoelastic properties of rubbers and the mechanism of nonlinearity in these polymeric systems.
The addition of iso-dimensional nanofillers into elastomers causes many
changes in mechanical and physical properties, but especially, the effect of
nanoparticles on the nonlinear viscoelasticity properties of rubbers has been investigated. In rubber matrices containing nanofillers, exhibition of the Payne effect is
strongly connected with the dispersion of the nanofiller and the tendency to create
aggregates among the nanoparticles. Filler dispersion plays an important role in
determining the nonlinear viscoelastic behavior of these systems—in particular,
both the properties of the filler particles and filler-polymer compatibility.
One of the most studied iso-dimensional nanofillers, described in this chapter, is
silica, which is a commonly available nanofiller that is susceptible to various
chemical modifications. Therefore, the simultaneous formation of the particles
and the rubber matrix, usually using the sol–gel process, seems to be interesting
and have much potential. Also, creation of new, complex iso-dimensional
nanofillers provides the ability to create systems having better physico-mechanical
properties and better nanofiller compatibility in the rubber matrix.
The rheological properties, especially the dynamic-mechanical properties, can
be very useful in predicting the dispersion of the nanofiller. In rubber
nanocomposites, the observed Payne effect can be correlated with microscopic
investigation, and often both these characteristics are consistent.
Rubber nanocomposites represent a very attractive field of materials science,
bringing new challenges for scientists working in experimental as well as simulation areas. At present the most popular models for predicting the Payne effect are:
80
M. Strankowski
properties. They have proved that nanofiller-MgO (size: 20–50 nm) in rubbery
composites causes a significant increase in G
0 and G
00 modulus, and also, at higher
values of tangent δ a clear Payne effect was observed [61].
Very interesting studies of natural rubber reinforcement with ZnO nanoparticles
were performed by scientists from India, under the direction of Sabu Thomas
[62]. The goal of these studies was to characterize the viscoelastic behavior and
reinforcement mechanism of ZnO nanoparticles introduced into the rubber matrix.
They have presented a constrained polymer model based on a rubbery region and a
ZnO nanoparticle. Very interestingly, the authors presented a core-shell morphology model and constrained polymer model to explain the constrained polymer
chains in NR/ZnO nanocomposites [62]. Thanks to this research and the proposed
models, it is possible to understand the behavior of nanofillers in the polymer matrix
and maybe in the future to develop an ideal nanofiller for use in the rubber matrix.
4 Summary, Conclusions and Future Outlook
In this chapter, the rheology and the dynamic-mechanical behavior of
iso-dimensional rubber nanocomposites in the non-linear zone have been reviewed.
Briefly described were the effect of nanofiller on the nonlinear viscoelastic properties of rubbers and the mechanism of nonlinearity in these polymeric systems.
The addition of iso-dimensional nanofillers into elastomers causes many
changes in mechanical and physical properties, but especially, the effect of
nanoparticles on the nonlinear viscoelasticity properties of rubbers has been investigated. In rubber matrices containing nanofillers, exhibition of the Payne effect is
strongly connected with the dispersion of the nanofiller and the tendency to create
aggregates among the nanoparticles. Filler dispersion plays an important role in
determining the nonlinear viscoelastic behavior of these systems—in particular,
both the properties of the filler particles and filler-polymer compatibility.
One of the most studied iso-dimensional nanofillers, described in this chapter, is
silica, which is a commonly available nanofiller that is susceptible to various
chemical modifications. Therefore, the simultaneous formation of the particles
and the rubber matrix, usually using the sol–gel process, seems to be interesting
and have much potential. Also, creation of new, complex iso-dimensional
nanofillers provides the ability to create systems having better physico-mechanical
properties and better nanofiller compatibility in the rubber matrix.
The rheological properties, especially the dynamic-mechanical properties, can
be very useful in predicting the dispersion of the nanofiller. In rubber
nanocomposites, the observed Payne effect can be correlated with microscopic
investigation, and often both these characteristics are consistent.
Rubber nanocomposites represent a very attractive field of materials science,
bringing new challenges for scientists working in experimental as well as simulation areas. At present the most popular models for predicting the Payne effect are:
80
M. Strankowski