Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials.

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer-particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer-particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

Investigating structure and dynamics of unentangled poly(dimethyl-co-diphenyl)siloxane via molecular dynamics simulation.

Polysiloxane is one of the most important polymeric materials in technological use. Polydimethylsiloxane displays glass-like mechanical properties at low temperatures. Incorporation of phenyl siloxane, via copolymerization for example, improves not only the low-temperature elasticity but also enhances its performance over a wide range of temperatures. Copolymerization with the phenyl component can significantly change the microscopic properties of polysiloxanes, such as chain dynamics and relaxation. However, despite much work in the literature, the influence of such changes is still not clearly understood. In this work, we systematically study the structure and dynamics of random poly(dimethyl-co-diphenyl)siloxane via atomistic molecular dynamics simulations. As the molar ratio ϕ of the diphenyl component increases, we find that the size of the linear copolymer chain expands. At the same time, the chain-diffusivity slows down by over an order of magnitudes. The reduced diffusivity appears to be a result of a complex interplay between the structural and dynamic changes induced by phenyl substitution.

Bead-Spring Simulation of Ionomer Melts-Studying the Effects of Chain-Length and Associating Group Fraction on Equilibrium Structure and Extensional Flow Behavior.

Ionomers are associative polymers with diverse applications ranging from selective membranes and high-performance adhesives to abrasion- and chemical-resistant coatings, insulation layers, vacuum packaging, and foamed sheets. Within equilibrium melt, the ionic or associating groups are known to form thermally reversible, associative clusters whose presence can significantly affect the system's mechanical, viscoelastic, and transport properties. It is, thus, of great interest to understand how to control such clusters' size distribution, shape, and stability through the designed choice of polymer architecture and the ionic groups' fraction, arrangement, and interaction strength. In this work, we represent linear associating polymers using a Kremer-Grest type bead-spring model and perform large-scale MD simulations to explore the effect of polymer chain-length (l) and fraction (fs) of randomly placed associating groups on the size distribution and stability of formed clusters. We consider different chain-lengths (below and above entanglement), varying fractions of associating groups (represented by 'sticky' beads) between 5 and 20%, and a fixed sticky-sticky nonbond interaction strength of four times that between regular non-associating beads. For all melts containing associating groups the equilibrium structure factor S(q) displays a signature ionomer peak at low wave vector q whose intensity increases with increasing fs and l. The average cluster size Nc increases with fs. However, the effect of chain-length on Nc appears to be pronounced only at higher values of fs. Under extensional flows, the computed stress (and viscosity) is higher at higher fs and l regardless of strain rate. Beyond a critical strain rate, we observe fragmentation of the associative clusters, which has interesting effects on the stress/viscous response.

Multiscale Strategy for Predicting Radiation Chemistry in Polymers.

A primary mode for radiation damage in polymers arises from ballistic electrons that induce electronic excitations, yet subsequent chemical mechanisms are poorly understood. We develop a multiscale strategy to predict this chemistry starting from subatomic scattering calculations. Nonadiabatic molecular dynamics simulations sample initial bond-breaking events following the most likely excitations, which feed into semiempirical simulations that approach chemical equilibrium. Application to polyethylene reveals a mechanism explaining the low propensity to cross-link in crystalline samples.

Computational exploration of polymer nanocomposite mechanical property modification via cross-linking topology.

Molecular dynamics simulations have been performed in order to study the effects of nanoscale filler cross-linking topologies and loading levels on the mechanical properties of a model elastomeric nanocomposite. The model system considered here is constructed from octafunctional polyhedral oligomeric silsesquioxane (POSS) dispersed in a poly(dimethylsiloxane) (PDMS) matrix. Shear moduli, G, have been computed for pure and for filled and unfilled PDMS as a function of cross-linking density, POSS fill loading level, and polymer network topology. The results reported here show that G increases as the cross-linking (covalent bonds formed between the POSS and the PDMS network) density increases. Further, G is found to have a strong dependence on cross-linking topology. The increase in shear modulus, G, for POSS filled PDMS is significantly higher than that for unfilled PDMS cross-linked with standard molecular species, suggesting an enhanced reinforcement mechanism for POSS. In contrast, in blended systems (POSS/PDMS mixture with no cross-linking) G was not observed to significantly increase with POSS loading. Finally, we find intriguing differences in the structural arrangement of bond strains between the cross-linked and the blended systems. In the unfilled PDMS the distribution of highly strained bonds appears to be random, while in the POSS filled system, the strained bonds form a netlike distribution that spans the network. Such a distribution may form a structural network "holding" the composite together and resulting in increases in G compared to an unfilled, cross-linked system. These results are of importance for engineering of new POSS-based multifunctional materials with tailor-made mechanical properties.

Mixed aromatic-alkyne system on a Pd surface: a first-principles study.

The chemistry of mixed aromatic-alkyne systems on a metal surface is of general interest in many industrial processes. We use density functional theory (DFT) to investigate the chemistry of one such system (i.e., 1,4-diphenyl-butadiyne (DPB) in contact with Pd(110) and Pd(111) surfaces). Reaction pathways and the energetics of important processes are explored, including H2 adsorption, dissociation and migration on the metal surface, the DPB-metal interaction, the energetics of H uptake, and the effects of impurities such as CO and CO2 on H chemistry. We find that (i) strong aromatic-metal interaction leads to significant binding strength of the DPB molecule to both Pd surfaces, especially the (110); (ii) H2 molecules readily dissociate on the Pd surface into H-radicals, which get taken up by alkyne triple bonds; (iii) CO has strong binding to the metal surface, but interacts weakly with H radicals; and (iv) CO2 binds weakly to the metal surface, but could potentially lead to interesting chemical reactions with H.

Molecular dynamics simulations of ordering of poly(dimethylsiloxane) under uniaxial stress.

Molecular dynamics simulations of bulk melts of poly(dimethylsiloxane) (PDMS) are utilized to study chain conformation and ordering under constant stress uniaxial extension at room temperature. We find that large extensions induce chain ordering in the direction of applied stress. During the extension, we also find that voids are created via a cavitation mechanism. At the end of our simulations, by visual inspection, we distinguish cavity, fibril, and amorphous regions that coexist together. The surrounding material about the formed cavities is fibril-like, while the remaining material remains amorphous. We also estimate the surface energy of the cavity. The cavity size continually increases in the dimension of applied stress but saturates in the lateral dimensions, most likely due to the finite size of the system. Despite chain orientation and ordering in the direction of applied stress, crystallization is absent in the time and stress range of our simulation. This study represents a baseline for the future study of mechanical properties of PDMS melts enriched with fillers under stress.