Effect of Flow-Induced Nematic Order on Polyethylene Crystal Nucleation

Predicting Natural Rubber Crystallinity by a Novel Machine Learning Algorithm Based on Molecular Dynamics Simulation Data

Natural rubber (NR) with excellent mechanical properties, mainly attributed to its strain-induced crystallization (SIC), has garnered significant scientific and technological interest. With the aid of molecular dynamics (MD) simulations, we can investigate the impacts of crucial structural elements on SIC on the molecular scale. Nonetheless, the computational complexity and time-consuming nature of this high-precision method constrain its widespread application. The integration of machine learning with MD represents a promising avenue for enhancing the speed of simulations while maintaining accuracy. Herein, we developed a crystallinity algorithm tailored to the SIC properties of natural rubber materials. With the data enhancement algorithm, the high evaluation value of the prediction model ensures the accuracy of the computational simulation results. In contrast to the direct utilization of small sample prediction algorithms, we propose a novel concept grounded in feature engineering. The proposed machine learning (ML) methodology consists of (1) An eXtreme Gradient Boosting (XGB) model to predict the crystallinity of NR; (2) a generative adversarial network (GAN) data augmentation algorithm to optimize the utilization of the limited training data, which is utilized to construct the XGB prediction model; (3) an elaboration of the effects induced by phospholipid and protein percentage (ω), hydrogen bond strength (εH), and non-hydrogen bond strength (εNH) of natural rubber materials with crystallinity prediction under dynamic conditions are analyzed by employing weight integration with feature importance analysis. Eventually, we succeeded in concluding that εH has the most significant effect on the strain-induced crystallinity, followed by ω and finally εNH.

Initial Crystallization Effects in Coarse-Grained Polyethylene Systems After Uni- and Biaxial Stretching in Blow-Molding Cooling Scenarios

This study investigates the initial stage of the thermo-mechanical crystallization behavior for uni- and biaxially stretched polyethylene. The models are based on a mesoscale molecular dynamics approach. We take constraints that occur in real-life polymer processing into account, especially with respect to the blowing stage of the extrusion blow-molding process. For this purpose, we deform our systems using a wide range of stretching levels before they are quenched. We discuss the effects of the stretching procedures on the micro-mechanical state of the systems, characterized by entanglement behavior and nematic ordering of chain segments. For the cooling stage, we use two different approaches which allow for free or hindered shrinkage, respectively. During cooling, crystallization kinetics are monitored: We precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influence crystallization behavior. Our models reveal that the main stretching direction dominates microscopic states of the different systems. We are able to show that crystallization mainly depends on the (dis-)entanglement behavior. Nematic ordering plays a secondary role.

Material Property Recovery by Controlling the Melt Memory Effects on Recrystallization and on Crystal Deformation: An Approach by the Molecular Dynamics Simulation for Polyethylene

Degradation in the mechanical properties of recycled polymer materials has been recently appearing as a big issue in polymer science. The molecular mechanism of the degradation is considered in part due to residual memories of flow experienced during molding processes, and therefore the mechanical recycling through remolding involving melting and recrystallization has been attempted in recent years. In the present paper, the molecular processes of melting and recrystallization are investigated by the molecular dynamics simulation for polyethylene with special interest in the melt memory effects. We also studied the mechanical properties of the recrystalized materials that have undergone different recrystallization processes aiming to discover better recycling strategies. A successive step-by-step approach is adopted to study the loss of the crystal memory during retention in the melt, the effects of the melt memory on the mode of recrystallization, the relation between the recrystallization mode and the resulting higher-order structure, and the mechanical properties controlled by the higher-order structures. It is shown that the melt memory clearly remains in various order parameters that persist over time scales corresponding to the Rouse time, the remaining melt memory markedly affects the crystallization mode leading to distinct crystalline morphologies, and the distinct morphologies obtained give different mechanical responses during large deformations.

Polymer crystallization under external flow

The general aspects of polymer crystallization under external flow, i.e., flow-induced crystallization (FIC) from fundamental theoretical background to multi-scale characterization and modeling results are presented. FIC is crucial for modern polymer processing, such as blowing, casting, and injection modeling, as two-third of daily-used polymers is crystalline, and nearly all of them need to be processed before final applications. For academics, the FIC is intrinsically far from equilibrium, where the polymer crystallization behavior is different from that in quiescent conditions. The continuous investigation of crystallization contributes to a better understanding on the general non-equilibrium ordering in condensed physics. In the current review, the general theories related to polymer nucleation under flow (FIN) were summarized first as a preliminary knowledge. Various theories and models, i.e., coil-stretch transition and entropy reduction model, are briefly presented together with the modified versions. Subsequently, the multi-step ordering process of FIC is discussed in detail, including chain extension, conformational ordering, density fluctuation, and final perfection of the polymer crystalline. These achievements for a thorough understanding of the fundamental basis of FIC benefit from the development of various hyphenated rheometer, i.e., rheo-optical spectroscopy, rheo-IR, and rheo-x-ray scattering. The selected experimental results are introduced to present efforts on elucidating the multi-step and hierarchical structure transition during FIC. Then, the multi-scale modeling methods are summarized, including micro/meso scale simulation and macroscopic continuum modeling. At last, we briefly describe our personal opinions related to the future directions of this field, aiming to ultimately establish the unified theory of FIC and promote building of the more applicable models in the polymer processing.

Direct observation of long chain enrichment in flow-induced nuclei from molecular dynamics simulations of bimodal blends

Modelling of flow-induced nucleation in polymers suggest that long chains are enriched in nuclei, relative to their melt concentration. This enrichment has important consequences for the nucleation rate and mechanism, but cannot be directly observed with current experimental techniques. Instead, we ran united atom molecular dynamics simulations of bimodal polyethylene blends, comprising linear chains at a 50 : 50 mix of long (1000 carbon) and short (500-125 carbon) chains, under shear flow. We developed a method to extract the nucleus composition during a transient start-up flow. Our simulations show significant and systematic enrichment of long-chains for all nucleus sizes up to and beyond the critical nucleus. This enrichment is quantitatively predicted by the recent polySTRAND model [Read et al. Phys. Rev. Lett. 2020, 124, 147802]. The same model parameters also correctly capture the nucleus induction time in our simulations. All parameters of the model were fitted to a small subset of our data in which long chain enhancement was absent. We conclude that long-chain enrichment is central to the mechanism of flow-induced nucleation and that this enrichment must be captured to correctly predict the nucleation rate.

Molecular Dynamics Simulations of Crystal Nucleation near Interfaces in Incompatible Polymer Blends

We apply molecular dynamics (MD) simulations to investigate crystal nucleation in incompatible polymer blends under deep supercooling conditions. Simulations of isothermal nucleation are performed for phase-separated blends with different degrees of incompatibility. In weakly segregated blends, slow and incompatible chains in crystallizable polymer domains can significantly hinder the crystal nucleation and growth. When a crystallizable polymer is blended with a more mobile species in interfacial regions, enhanced molecular mobility leads to the fast growth of crystalline order. However, the incubation time remains the same as that in pure samples. By inducing anisotropic alignment near the interfaces of strongly segregated blends, phase separation also promotes crystalline order to grow near interfaces between different polymer domains.