Chinese Journal of Polymer Science最新文献

In this study, a novel cost-effective methodology was developed to enhance the gas barrier properties and permselectivity of unfilled natural rubber (NR)/polybutadiene rubber (BR) composites through the construction of a heterogeneous structure using pre-vulcanized powder rubber to replace traditional fillers. The matrix material is composed of a blend of NR and BR, which is widely used in tire manufacturing. By incorporating pre-vulcanized trans-1,4-poly(isoprene-co-butadiene) (TBIR) rubber powder (pVTPR) with different cross-linking densities and contents, significant improvements in the gas barrier properties and CO₂ permselectivity of the NR/BR/pVTPR composites were observed. The results indicated that compared to NR/BR/TBIR composites prepared through direct blending of NR, BR, and TBIR, the NR/BR/pVTPR composites exhibited markedly superior gas barrier properties. Increasing the cross-linking density of pVTPR resulted in progressive enhancement of the gas barrier properties of the NR/BR/pVTPR composite. For example, the addition of 20 phr pVTPR with a cross-linking density of 346 mol/m³ resulted in a 79% improvement in the oxygen barrier property of NR/BR/pVTPR compared to NR/BR, achieving a value of 5.47×10⁻¹⁴ cm³·cm·cm⁻²·s⁻¹·Pa⁻¹. Similarly, the nitrogen barrier property improved by 76% compared to NR/BR, reaching 2.4×10⁻¹⁴ cm³·cm·cm⁻²·s⁻¹·Pa⁻¹, which is 28 % higher than the conventional inner liner material brominated butyl rubber (BIIR, P_N2=3.32×10⁻¹⁴ cm³·cm·cm⁻²·s⁻¹·Pa⁻¹). Owing to its low cost, exceptional gas barrier properties, superior adhesion to various tire components, and co-vulcanization capabilities, the NR/BR/pVTPR composite has emerged as a promising alternative to butyl rubber in the inner liner of tires. Furthermore, by fine-tuning the cross-linking density of pVTPR, the high-gas-barrier NR/BR/pVTPR composites also demonstrated remarkable CO₂ permselectivity, with a CO₂/N₂ selectivity of 61.4 and a CO₂/O₂ selectivity of 26.12. This innovation provides a novel strategy for CO₂ capture and separation, with potential applications in future environmental and industrial processes. The multifunctional NR/BR/pVTPR composite, with its superior gas barrier properties and CO₂ permselectivity, is expected to contribute to the development of safer, greener, and more cost-effective transportation solutions.

Melt pre-shear induced crystallization of polymer blends holds great significance in industrial processing and product application. In this work, two typical PB/PP blends (50/50, 90/10), possessing commercial value and academic hotspot, were employed to investigate the effect of melt pre-shear on the crystallization of isotactic poly(1-butene) (PB) and polypropylene (PP) by applying shearing slightly above the melting temperature of PP with subsequent non-isothermal crystallization to simulate actual processing conditions. It was discovered that in PB/PP (90/10) blend, in situ melt pre-shear generated oriented PP precursors induced the formation of PP-FIC (Flow-induced crystallization) which acted as row crystal nucleus significantly promoting PB crystallization into spherulite with higher melting temperatures (T_m), crystallinity (X_c), and thicker lamellar thickness (d_c). While in PB/PP (50/50) blend, the melt pre-shear generated PP-shish precursors induced the formation of PP shish-kebab that exerted a confining effect on the crystal growth of PB, resulting in truncated spherulite formation with higher T_m and thicker d_c but lower X_c. This research provides insight into the mechanism underlying oriented crystal structure formation, crystal properties, and phase morphology of PB/PP blends under melt pre-shear fields, which have significant theoretical and practical implications for their industrial processing and preparation of high-performance products.

Machine learning-assisted prediction of polymer properties prior to synthesis has the potential to significantly accelerate the discovery and development of new polymer materials. To date, several approaches have been implemented to represent the chemical structure in machine learning models, among which Mol2Vec embeddings have attracted considerable attention in the cheminformatics community since their introduction in 2018. However, for small datasets, the use of chemical structure representations typically increases the dimensionality of the input dataset, resulting in a decrease in model performance. Furthermore, the limited diversity of polymer chemical structures hinders the training of reliable embeddings, necessitating complex task-specific architecture implementations. To address these challenges, we examined the efficacy of Mol2Vec pre-trained embeddings in deriving vectorized representations of polymers. This study assesses the impact of incorporating Mol2Vec compound vectors into the input features on the efficacy of a model reliant on the physical properties of 214 polymers. The results will hopefully highlight the potential for improving prediction accuracy in polymer studies by incorporating pre-trained embeddings or promote their utilization when dealing with modestly sized polymer databases.

A series of transparent crosslinked colorless polyimide (CPI) films are prepared from 3,3′,4,4′-biphenyltetracarboxylic dianhydride (BPDA), 2,2′-bis(trifluoro-methyl)benzidine (TFMB), and 4,4′-oxydianiline (ODA) by thermal imidization, incorporating varying contents of 2,2′-(1,3-phenylene)bis(2-oxazoline) (1,3-PBO) as the crosslinking agent. Following the incorporation of the crosslinking structure, the CPI films show good optical transparency (approximately 85% winthin visible light range), enhanced glass transition temperature (from 325 °C to 341 °C), and improved thermal stability, and tensile strength. Notably, compared with the pristine uncrosslinked CPI, these crosslinked CPI films significantly increase in elongation at break (from 5.4% to 44.2%). Furthermore, the new approach ensures that crosslinked CPIs improve heat resistance and mechanical properties, while avoiding the embrittlement of materials. This study also offeres straightforward preparation methods for optically transparent crosslinked polyimides without additional processing steps. All these results make this approach can effectively improve the competitive performance of the CPI films for potential applications in microelectronic and optoelectronic fields.

Nanopore sequencing harnesses changes in ionic current as nucleotides traverse a nanopore, enabling real-time decoding of DNA/RNA sequences. The instruments for the dynamic behavior of substances in the nanopore on the molecular scale are still very limited experimentally. This study employs all-atom molecular dynamics (MD) simulations to explore the impact of charge densities on graphene nanopore in the translocation of single-stranded DNA (ssDNA). We find that the magnitude of graphene’s charge, rather than the charge disparity between ssDNA and graphene, significantly influences ssDNA adsorption and translocation speed. Specifically, high negative charge densities on graphene nanopores are shown to substantially slow down ssDNA translocation, highlighting the importance of hydrodynamic effects and electrostatic repulsions. This indicates translocation is crucial for achieving distinct ionic current blockades, which plays a central role for DNA sequencing accuracy. Our findings suggest that negatively charged graphene nanopores hold considerable potential for optimizing DNA sequencing, marking a critical advancement in this field.

Mechanical properties of polymers can be regulated by changing the numbers of hydrogen bonds and entanglement points. However, the interplay between hydrogen bond network and entangled network during stretching has not been fully studied. We performed molecular dynamics simulations to investigate the changes of hydrogen bonds and entanglements during stretching. The stretching causes the orientation of local segments, leading to the entanglement sliding and disentanglements at different strain regions. Then, the number of entanglement points keeps constant at first and then decreases with increasing strain. Differently, the orientation of local segments can cause the change of chain conformation, which leads to the breakage of hydrogen bonds. Thus, the number of hydrogen bonds decreases with the increase of strain. Simulation results also demonstrated that the number of hydrogen bonds decreases faster during stretching in systems containing more entanglements. In systems with different hydrogen bond site contents, the initial number of entanglement nodes and its decline range during stretching increase firstly and then decrease with the increase of hydrogen bond site content.

Viscoelastic properties of thermoplastic polyurethane (TPU) is of fundamental importance for its processing. In this work, we prepared different TPUs from polycaprolactone (PCL) diol, diphenylmethane-4,4′-diisocyanate (MDI), and 1,4-butanediol (BDO), and investigated the viscoelastic behavior of three TPUs with different hard segment content during thermal annealing process. The storage modulus (G′) of TPU increases over time in a medium annealing temperature (T_a) region, but remains unchanged at both high and low temperature regions. The growth of loss modulus (G″) over time is slower than that of G′. At medium T_a, both G′ and G″ increase during the repeating frequency (ω) sweep, due to the gradual crystallization of hard segments. This indicates that the crystallites primarily restrain the relaxation of unit with large size. The increments of G′ and G″ are weakened when the content of hard segment in TPU is decreased. For TPU with high content of hard segments, a complete high elastic platform with a width of 3 orders of magnitude was observed only through one frequency scan test at medium T_a. In addition, the crystallites of hard segments grow up continuously during frequency scan test (isothermal annealing treatment) and cause the extreme increase in G′ and G″ with ω in low ω region.

Membrane fusion is essential for many cellular physiological functions, which is modulated by highly precise molecular mechanism involving multiple energy barriers. Nanoparticles (NPs), which exhibit immense potential in the field of biomedical applications, can act as fusogen proteins to initiate and regulate membrane fusion. However, the underlying mechanisms of NP-induced membrane fusion and the molecular details involved remain largely elusive. Here, using coarse-grained molecular dynamics simulations, we systematically investigate the NP-induced membrane fusion behaviors and the influences of NP properties (size, hydrophobicity and hydrophilicity). Our results show that the vesicle-bilayer fusion induced by a hydrophobic NP is an intricately state-wise process, involving the approach and local deformation of the vesicle and bilayer bridging by the NP, the flip-flop of lipids from proximal leaflets and the formation of a fusion stalk, as well as further lipid interactions between distal leaflets and complete fusion. Moreover, we find that NP properties have distinct effects on membrane fusion and thus the optimal NP conditions for facilitating membrane fusion are obtained. Our work provides a mechanistic understanding of NP-induced membrane fusion and offers useful insights for efficient and controlled regulation of membrane fusion.

Star-shaped poly(lactic acid)s (PLAs) with two to five arms were synthesized by ring opening polymerization using tin(II) 2-ethylhexanoate as catalyst and polyols as initiators. The effects of molecular weight together with multi-arm architecture on crystallization behavior, spherulite morphology and alkaline degradation behavior of star-shaped PLAs have been investigated. The results indicate that the multi-arm architecture interfered with spherulite growth, but promoted nucleation and alkaline degradation of star-shaped PLAs. Interestingly, with the increase of molecular weight (M_n), the crystallization rate first increased and then decreased, while the alkaline degradation rate was the opposite. The characteristic crystallization and alkaline degradation behavior of star-shaped PLAs were discussed based on the competition between segmental mobility and central core confinement.

Anion-exchange membranes (AEMs) with high conductivity and stability are essential components of hydrogen related water electrolysis and fuel cell applications. During the past decades, polynorbornene (PNB)-based AEMs have shown excellent performance due to their saturated all-carbon-based backbones and diverse strategies to prepare cross-linked membranes. However, nearly all previously reported PNB-based AEMs rely on the alkyl-substituted norbornene monomers, whose low-yielding synthesis leads to high-cost of the AEMs. In addition, the cross-linked PNB-based AEMs usually suffered from mechanical brittleness. Herein, we propose a novel semi-interpenetrating polymer network (s-IPN) strategy to simultaneously enhance mechanical modulus and ionic conductivity, while using commercial 5-vinyl-2-norbornene (VNB) as the single norbornene derivatives to prepare high-performance AEMs. A diallylphenol quaternary ammonium salt was used for photo-induced cross-linking with poly-VNB and various dithiols to produce AEMs with s-IPN structures. The resultant membranes have excellent hydroxide conductivities and alkaline stability in 1 mol/L KOH at 80 °C, and are successfully applied in alkaline anion-exchange membrane water electrolyzers to stably operate for over 150 h.