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Polymer nanocomposites (PNCs), which exhibit excellent mechanical properties through the incorporation of fillers into polymers, have been extensively studied to achieve enhanced self-healing capability for their next-generation development. However, there is still a lack of investigation into the influence of the topological structures of nanoparticles (NPs) on the self-healing capability of PNCs. In this study, we utilized coarse-grained molecular dynamics simulations (CGMDs) to construct a series of PNC systems composed of NPs with different topological structures, including Linear, Ring, and Cross topologies. We employed non-bonding interaction potentials to examine the interactions between the polymer and NPs, and varied the parameters to simulate different functional groups. Our results indicate that the stress-strain curves and the rate of performance loss validate that the Linear structure is the optimal topology for mechanical reinforcement and self-healing properties. By analyzing the stress heat map during stretching, we observed that the Linear structure NPs experience significant stress, allowing the matrix chains to dominate in small recoverable deformations during stretching. It can be speculated that NPs oriented in the direction of extrusion are more effective than others in enhancing performance. Overall, this work provides valuable theoretical guidance and a novel strategy for designing and manipulating high-performance, self-healing PNCs.
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Bio-based polyester elastomers have been widely studied by researchers in recent years because of their comprehensive sources of monomers and environmentally friendly characteristics. However, compared with traditional petroleum-based elastomers, the thermal decomposition temperature of bio-based polyester elastomers is generally low, limiting the application of bio-based elastomers. An effective strategy to increase the intrinsic thermal decomposition temperature (Td) of bio-based elastomers is to increase the length of the monomer carbon chain in the bio-based elastomers. In this work, the content of dodecanedioic acid (DDA) in a bio-based polyester elastomer composed of butanediol (BDO) and succinic acid (SUA) was increased to improve the Td of the bio-based polyester elastomer through the reaction force-field molecular dynamics (ReaxFF-MD) simulations. And the thermal decomposition mechanism of the bio-based polyester was analyzed in detail. By calculating the change rate of the molecular chain mean square displacement (MSD), it was determined that when the content of DDA was 50%, the Td of the bio-based elastomer was up to 718 K. By calculating the activation energy of thermal decomposition and further analyzing the thermal decomposition process, it is found that the thermal decomposition of the bio-based polyester elastomer is mainly through breaking the C-O bond in the backbone. This work is expected to provide theoretical guidance for designing and fabricating highly heat-resistant bio-based elastomers by systematically exploring the thermal decomposition mechanism of bio-based polyester elastomers.
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Introducing polymeric nanoparticles into polymer matrices is an interesting topic, and the robustness of the polymeric nanoparticles is crucial for the properties of the polymer nanocomposites (PNCs). In this study, by incorporating star-shaped polymeric nanoparticles (SSPNs) into the polymer, the effect of the sphericity (η) and arm length (L) of the SSPNs on the mechanical properties of PNCs is systematically investigated, using a coarse-grained molecular dynamics simulation. In addition, the linear and spherical nanoparticles (NPs) are compared with SSPNs by fixing the approximate diameter and mass fraction of the NPs. The radial distribution function, the second virial coefficient, mean-squared displacement, bond autocorrelation function, and primitive path analysis are employed to systematically characterize the structure and dynamics of these new PNCs. It is found that the dispersion of the NPs is enhanced with the increase of η, and the entanglement density reaches maximum, which both contribute to the greatest mechanical reinforcing effect. More significantly, it is found that the classical Payne effect, namely the storage as a function of the strain amplitude, decreases remarkably, and with a much smaller loss factor for these SSPN filled polymer nanocomposites, compared to conventional PNCs filled with rigid NPs. Furthermore, the change of the arm length of the SSPNs is found to exhibit the same effect on the mechanical and viscoelastic properties, as the variation of the number of the arms. In general, this work shows that these new SSPN filled polymer nanocomposites can exceed conventional PNCs, by manipulating the robustness of the SSPNs using, for example, the number and length of the arms. This research may provide guidelines for the investigation of the structure-property relationships of the topological structure of polymeric nanoparticles.
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Understanding polymer-substrate interfacial dynamics at the molecular level is crucial for tailoring the properties of polymer ultrathin films (PUFs). Herein, through coarse-grained molecular dynamics simulation, the effect of length (Nloop) and rigidity (Kloop) of loop chains on the dynamics of linear chains is systematically explored, in which the loop chains are adsorbed on a solid substrate and the linear chains are covered on the loop chains. It is found that there is an optimal Kloop, which strongly confines the motion of the linear chains. Meanwhile, compared to increasing the rigidity of the loop chains, increasing the length of the loop chains can more effectively confine the motion of the linear chains. More interestingly, we observe that the mismatch of the length (ΔN) and rigidity (ΔK) between the loop and linear chains leads to dynamic asymmetry (ΔDc). The relationship between the ΔN, ΔK, and ΔDc are found to follow the mathematical expression of ΔDc â¼ (ΔN)α(ΔK)ß, in which the values of α and ß are around 4.58 and 0.83, separately. Remarkably, using the Gaussian process regression model, we construct a master curve of diffusion coefficient on the segmental and chain length scales of the linear chains as a function of Nloop and Kloop, which is further validated by our simulated prediction. In general, this work provides a fundamental understanding of polymer interfacial dynamics at the molecular level, enlightening some rational principles for manipulating the physical properties of PUFs.
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The improvement of mechanical properties of polymer nanocomposites (PNCs) has been studied for many years, with the main focus on the structure of the nanofillers. Much less effort has been devoted to unraveling the factors controlling the structure of the grafted chains. Herein, through coarse-grained molecular-dynamics simulations, we have successfully fabricated an ideal, mechanically-interlocked composite structure composed of end-functionalized chains grafted to the nanoparticle surface forming rings and making the matrix chains thread through these rings. Depending on the details of the grafting, the reinforcement effect can be remarkable, improving the tensile stress of the system significantly up to 700%. Meanwhile, anisotropy of the system's mechanical response is also observed. Furthermore, the influence of the grafted chain distribution on the mechanical properties of the system has been investigated as well. We observe that the mechanical properties of the system are closely related to the total number of the beads in the grafted chains or the synergistic effect between the length and density of the grafted chains leads to no significant difference in the performance of systems. At constant grafting density, the mechanical properties of the systems correlate negatively to the grafted chain length. In general, our study should help to design and fabricate high-performance PNCs with excellent mechanical properties.
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Detailed coarse-grained molecular dynamics simulations are performed to investigate the structural and mechanical properties of nanoparticles (NPs) grafted with an amphiphilic AB diblock copolymer, with the A-block being compatible with NPs and the B-block being miscible with a homopolymer matrix. We systematically investigate the effects of the grafting density (Ng), the component ratio (α) and the flexibility of the grafted diblock copolymer on the structural and mechanical properties of polymer nanocomposites (PNCs). Interestingly, we observe that the grafted NPs can form a core-shell like structure attributed to the adsorption of the A-blocks onto the NPs, validated by the radial distribution function of the A and B blocks away from the surface of the NPs. The integrity of the core-shell structure is influenced by the grafting density and the component ratio of the grafted chains. The core-shell structure of the NPs becomes more perfect with greater Ng. The morphology of the NPs is shifted from a network structure to an isolated or well dispersed state upon increasing the grafting density. Meanwhile, we analyze the evolution of the morphology of the NPs during the uniaxial tensile process by calculating the number of neighboring NPs as a function of strain, thus finding that the NP network is broken-up at low grafting density, while only a little change is observed at high grafting density. Upon increasing the component ratio of the B-block to the A-block, the dispersion of the NPs becomes better, characterized by the radial distribution function of NPs-NPs, NPs-A-blocks, NPs-B-blocks, NPs-matrix, the number of neighboring NPs and the snapshots. Lastly, by changing the B-block from being flexible to stiff, the core-shell structure of the NPs disappears after the formation of a typical capsule morphology. This capsule-ordered structure becomes more prominent with the increase in Ng. Remarkably, compared to the effect of the core-shell morphology on the mechanical properties, the capsule morphology reinforces the mechanical properties more obviously. In general, this simulation work provides a deep insight into the structural and mechanical properties of NPs grafted with diblock copolymer chains, in the hope of providing some guidance on the design and preparation of high-performance PNCs.
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The structure-property relationship of polymer nanocomposites (PNCs) has been extensively investigated, but less effort has been devoted to studying the effect of chain architectures. Herein, through coarse-grained molecular dynamics simulation, we build six different chain architectures namely linear, branch-2 (with two side chains), branch-4 (with four side chains), branch-10 (with ten side chains), star-4 (with four arms) and star-6 (with six arms), by fixing the molecular weight per chain. First, we examine the effect of the interfacial interaction between the polymer and nanoparticles (NPs) εnp on the dispersion of NPs, by calculating the radial distribution function between NPs, the second virial coefficient and the average number of neighbor fillers. We observe a non-monotonic change of the NP dispersion as a function of εnp for all PNCs with different chain architectures, indicating the optimal dispersion of NPs at moderate εnp. Meanwhile, we find that the star-6, branch-4 and linear chains promote the best dispersion of NPs at moderate εnp, compared to the other chain architectures. Then we investigate the strain hardening behavior and chain orientation of these PNCs under uniaxial tension. We find that the star-6 chains demonstrate relatively the most remarkable reinforced mechanical behavior of PNCs. Furthermore, we probe the effect of end-functionalization of polymer chains with different architectures on the dispersion of NPs, by comparing them to the case without any functionalization. We find that the introduction of the end-functionalization benefits mostly the high degree of chain branching for promoting the dispersion of NPs. Meanwhile, we observe that when the tensile strain is small, the branch-4 structure shows relatively improved mechanical properties, however, when the tensile strain is large, the star-6 and branch-10 structures display the best mechanical properties, and the end-functionalization evidently improves the mechanical properties of the PNCs. Our simulation results provide guidelines to tailor the dispersion of NPs and the mechanical properties of PNCs, by taking advantage of the chain architecture and its end-functionalization strategy.
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Using short polymer chains and through molecular dynamics simulation, we designed a well-dispersed nanoparticle (NP) network, which was then incorporated with the polymer matrix. First, we examined the effects of the dual-end grafted chains flexibility and density on the spatial distribution of this particular polymer nanocomposites system. By changing the interaction strength between the matrix polymer chains and the dual-end grafted chains in the semi-interpenetrating network system (NP network), we analyzed the interpenetration state between the linear polymer matrix and the NP network via calculating the total interfacial interaction energy. Moreover, the uniaxial tensile stress-strain and orientation behavior influenced by the interaction strength between the matrix polymer and the grafted chains were investigated for both the semi-interpenetrating network system and the interpenetrating network system (NP network and matrix network). Furthermore, for the interpenetrating network system, we modulated the integrity of the NP network ranging from 0% to 100%, corresponding to the gradual transition of the dispersion morphology of the NPs from the aggregation state to the uniform dispersion state, to examine the effect of the NP network on the tensile mechanical behavior. In particular, by simulating the dynamic shear process in the semi-interpenetrating network system, the composites were found to exhibit a lower non-linear behavior (the famous Payne effect), a higher storage modulus, and a lower tangent loss at large strain amplitude with increasing NP network integrity. In general, our results could provide a new approach for the design of high-performance polymer nanocomposites by taking advantage of the semi-interpenetrating or interpenetrating network reinforcing structure.
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Linear polyisoprene (PI) and SiO2-g-PI particle brushes were synthesized by both conventional and activators regenerated by electron transfer (ARGET) atom transfer radical polymerization (ATRP). The morphology and solution state study on the particle brushes by transmission electron microscopy (TEM) and dynamic light scattering (DLS) confirmed the successful grafting of PI ligands on the silica surface. The presence of nanoparticle clusters suggests low grafting density (associated with the limited initiation efficiency of ARGET for PI). Nevertheless, particle brushes with very high molecular weights, Mn > 300,000, were prepared, which significantly improved the dispersion of silica nanoparticles and also contributed to excellent mechanical performance. The reinforcing effects of SiO2 nanofillers and very high molecular weight PI ligands were investigated by dynamic mechanical analysis (DMA) as well as computational simulation for the cured linear PI homopolymer/SiO2-g-PI particle brush bulk films.
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Since the proposal of self-healing materials, numerous researchers have focused on exploring their potential applications in flexible sensors, bionic robots, satellites, etc. However, there have been few studies on the relationship between the morphology of the dynamic crosslink network and the comprehensive properties of self-healing polymer nanocomposites (PNCs). In this study, we designed a series of modified nanoparticles with different sphericity (η) to establish a supramolecular network, which provide the self-healing ability to PNCs. We analyzed the relationship between the morphology of the supramolecular network and the mechanical performance and self-healing behavior. We observed that as η increased, the distribution of the supramolecular network became more uniform in most cases. Examination of the segment dynamics of polymer chains showed that the completeness of the supramolecular network significantly hindered the mobility of polymer matrix chains. The mechanical performance and self-healing behavior of the PNCs showed that the supramolecular network mainly contributed to the mechanical performance, while the self-healing efficiency was dominated by the variation of η. We observed that appropriate grafting density is the proper way to effectively enhance the mechanical and self-healing performance of PNCs. This study provides a unique guideline for designing and fabricating self-healing PNCs with modified Nanoparticles (NPs).
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The control of the self-assembly of the nanocrystals into ordered structures has been extensively investigated, but fewer efforts have been devoted to studying one-component polymer-grafted nanoparticles (OPNPs). Herein, through coarse-grained molecular dynamics simulation, we design a novel nanoparticle (NP) grafted with polymer chains, focusing on its self-assembled structures. First, we examine the effects of length and density of grafted polymer chains by calculating the radial distribution function between NPs, as well as through direct visualization. We observe a monotonic change of the arranged morphology of grafted-NPs as a function of the density of grafted polymer chains, which indicates that the increase of the grafting density contributes to the order of the morphology. Meanwhile, we find that much longer grafted polymer chains worsen the regularity of the morphology. Then, we probe the influence of the stiffness of grafted polymer chains (denoted by K ranging from 0 to 500) on the order of grafted-NPs, finding that the order of the structure exhibits a nonmonotonic behavior as a function of K at moderate grafting density. For high grafting density, the order of the morphology is initially enhanced and becomes saturated as a function of K. For the effect of K on the stress-strain behavior, the system with the lowest order demonstrates the most remarkable reinforced mechanical behavior for both low and high grafting density. Last, we establish the phase diagram by varying the stiffness and density of the grafted polymer chains, which contains the amorphous, ordered, and superlattice structures, respectively. In general, our simulated results provide guidelines to tailor the self-assembly of the OPNPs by taking advantage of the length, density, and stiffness of grafted polymer chains.
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Through coarse-grained molecular dynamics simulation, we have successfully designed the chemically cross-linked (fixed junction) and the slide-ring (SR) systems. Firstly, we examine the dynamic properties such as the mean-square displacement, the bond, and the end-to-end autocorrelation functions as a function of the cross-linking density, consistently pointing out that the SR system exhibits much lower mobility compared with the fixed junction one at the same cross-linking density. This is further validated by a relatively higher glass transition temperature for the SR system compared with that of the fixed junction one. Then, we calculated the effect of the cross-linking density on the stretch-recovery behavior for the SR and fixed junction systems. Although the chain orientation of the SR system is higher than that of the fixed-junction system, the tensile stress is smaller than the latter. We infer that much greater chain sliding can occur during the stretch, because the movable ring structure homogeneously sustains the external force of the SR system, which, therefore, leads to much larger permanent set and higher hysteresis during the recovery process compared with the fixed-junction one. Based on the stretch-recovery behavior for various cross-linking densities, we obtain the change of the hysteresis loss, which is larger for the SR system than that of the fixed junction system. Lastly, we note that the relatively bigger compressive stress for the SR system results from the aggregation of the rigid rings compared with the fixed junction system. In general, compared with the traditionally cross-linked system, a deep molecular-level insight into the slide-ring polymer network is offered and thus is believed to provide some guidance to the design and preparation of the slide-ring polymer network with both good mechanical and damping properties.
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Through coarse-grained molecular dynamics simulation, we construct a novel kind of end-linked polymer network by employing dual end-functionalized polymer chains that chemically attach to the surface of nanoparticles (NPs), so that the NPs act as large cross-linkers. We examine the effects of the length and flexibility of polymer chains on the dispersion of NPs, and the effect of the chain length on the stress-strain behavior and the segment orientation during the deformation process. We find that the stress upturn becomes more prominent with the decrease of the chain length, attributed to the limited extensibility of the chain strand connecting two neighboring NPs. In addition, this end-linked polymer nanocomposite (PNC) is shown to have a temperature-dependent stress-strain behavior that is contrary to traditional physically mixed PNCs, whose mechanical properties deteriorate with increasing temperature. This is due to the stability of the dispersion of NPs and higher entropic elasticity at higher temperature for the former, while the latter has poorer interfacial interaction at higher temperature, leading to less reinforcing efficiency. By imposing a dynamic oscillatory shear deformation, we obtain a dynamic hysteresis loop for end-linked and physically mixed dispersions. Interestingly, the end-linked system possesses a much smaller hysteresis loss than does the physically mixed system, with the latter exhibiting a more prominent decrease with increasing temperature, due to less interfacial contact. Our results demonstrate that end-linked PNCs combine attractive static and dynamic mechanical properties and exhibit an unusual response to temperature, which could find potential applications in the future.