We studied the static and dynamic mechanical properties of crosslinked polymer matrices using multiscale simulations and experiments. We continued to develop the multiscale methodology for generating atomistic polymer networks, and applied it to the case of phthalonitrile resin. The mechanical properties of the resulting networks were analyzed using atomistic molecular dynamics (MD) and dissipative particle dynamics (DPD). The Young’s and storage moduli increased with conversion, due both to the appearance of a network of covalent bonds, and to freezing of degrees of freedom and lowering of the glass transition temperature during crosslinking. The simulations’ data showed good quantitative agreement with experimental dynamic mechanical analysis measurements at temperatures below the glass transition. The data obtained in MD and DPD simulations at elevated temperatures were conformable. This makes it possible to use the suggested approach for the prediction of mechanical properties of a broad range of polymer matrices, including ones with high structural heterogeneity.

The formation of a thermoset polymer network is a complex process with great variability. In this study, we used dissipative particle dynamics and graph theory tools to investigate the curing process and network topology of a phthalonitrile thermoset to reveal the influence of initiator and plasticizer concentration on its properties. We also propose a novel way to characterize the network topology on the basis of two independent characteristics: simple cycle length (which is mainly affected by the initiator amount) and the number of simple cycles passing through a single covalent bond (which is determined primarily by plasticizer concentration). These values can be treated in the more familiar terms of network “mesh size” and “sponginess”, correspondingly. The combination of these two topological parameters allows one to characterize any given network in an implicit but precise way and predict the resulting network properties, including the mechanical modulus. We believe that the same approach could be useful for other polymer networks as well, including rubbers and gels.

The paper aims to study the mechanical properties of epoxy resin filled with clay nanoparticles (NPs), depending on their shapes and content on the surface of a modifying agent capable of forming covalent bonds with a polymer. The cylindrical clay nanoparticles with equal volume and different aspects ratios (disks, barrel, and stick) are addressed. The NPs’ bonding ratio with the polymer (RGC) is determined by the fraction of reactive groups and conversion time and varies from RGC = 0 (non-bonded nanoparticles) to RGC = 0.65 (more than half of the surface groups are linked with the polymer matrix). The performed simulations show the so-called load-bearing chains (LBCs) of chemically cross-linked monomers and modified nanoparticles to determine the mechanical properties of the simulated composites. The introduction of nanoparticles leads to the breaking of such chains, and the chemical cross-linking of NPs with the polymer matrix restores the LBCs and strengthens the composite. At small values of RGC, the largest value of the elastic modulus is found for systems filled with nanoparticles having the smallest surface area, and at high values of RGC, on the contrary, the systems containing disk-shaped particles with the largest surface area have a larger elastic modulus than the others. All calculations are performed within the framework of a mesoscopic model based on accurate mapping of the atomistic structures of the polymer matrix and nanoparticles into coarse-grained representations, which, if necessary, allow reverse data mapping and quantitative assessment of the state of the filled epoxy resin. On the other hand, the obtained data can be used to design the functional materials with specified mechanical properties based on other practically significant polymer matrices and nanofillers.

Polyacrylonitrile (PAN) is widely used as a raw material for the production of high-modulus carbon fibers, the internal structure of which is directly affected by the spinning of the precursor. Although PAN fibers have been studied for a long time, the formation of their internal structure has not been sufficiently investigated theoretically. This is due to the large number of stages in the process and the parameters controlling them. In this study, we present a mesoscale model describing the evolution of nascent PAN fibers during the coagulation. It is constructed within the framework of a mesoscale dynamic density functional theory. We use the model to study the influence of a combined solvent of dimethyl sulfoxide (DMSO, a good solvent) and water (a non-solvent) on the microstructure of the fibers. A porous structure of PAN is formed as a result of the microphase separation of the polymer and the residual combined solvent at a high water content in the system. The model shows that one of the possible ways to obtain the homogeneous fiber structure is to slow down the coagulation by increasing the amount of good solvent in the system. This result is in agreement with the existing experimental data and confirms the efficiency of the presented model.

We present a mesoscale model and the simulation results of a system composed of polyacrylonitrile (PAN), carbon nanotubes (CNTs), and a mixed solvent of dimethylsulfoxide (DMSO) and water. The model describes a fragment of a nascent PAN/CNT composite fiber during coagulation. This process represents one of the stages in the production of PAN composite fibers, which are considered as precursors for carbon fibers with improved properties. All calculations are based on dynamic density functional theory. The results obtained show that the greatest structural heterogeneity of the system is observed when water dominates in the composition of the mixed solvent, which is identified with the conditions of a non-solvent coagulation bath. The model also predicts that the introduction of CNTs can lead to an increase in structural heterogeneity in the polymer matrix with increasing water content in the system. In addition, it is shown that the presence of a surface modifier on the CNT surface, which increases the affinity of the filler to the polymer, can sufficiently reduce the inhomogeneity of the nascent fiber structure.

A mesoscopic model of a nanocomposite based on crosslinked polymer networks with embedded clay nanoparticles was developed. The model makes it possible to predict the main trends in changes in the mechanical properties of systems, taking into account the degree of crosslinking of nanoparticles with a polymer matrix. The performed simulations showed that modified nanoparticles can significantly improve the Young’s modulus of the nanocomposite compared to the unfilled polymer. It was also shown that the average value of the number of load-bearing chains determines the mechanical response of the coarse-grained model of the polymer system.