Chinese Journal of Polymer Science最新文献

Thermophilic proteins maintain their structure and function at high temperatures, making them widely useful in industrial applications. Due to the complexity of experimental measurements, predicting the melting temperature (T_m) of proteins has become a research hotspot. Previous methods rely on amino acid composition, physicochemical properties of proteins, and the optimal growth temperature (OGT) of hosts for T_m prediction. However, their performance in predicting T_m values for thermophilic proteins (T_m>60 °C) are generally unsatisfactory due to data scarcity. Herein, we introduce TmPred, a T_m prediction model for thermophilic proteins, that combines protein language model, graph convolutional network and Graphormer module. For performance evaluation, TmPred achieves a root mean square error (RMSE) of 5.48 °C, a pearson correlation coefficient (P) of 0.784, and a coefficient of determination (R²) of 0.613, representing improvements of 19%, 15%, and 32%, respectively, compared to the state-of-the-art predictive models like DeepTM. Furthermore, TmPred demonstrated strong generalization capability on independent blind test datasets. Overall, TmPred provides an effective tool for the mining and modification of thermophilic proteins by leveraging deep learning.

Adjusting the structure of the hard segment (HS) represents a key method for manipulating the mechanical properties of thermoplastic polyurethane (TPU). This study developed a novel molecular design strategy to tailor TPU’s mechanical performance through altering the terminal diisocyanate structure of HS. The typical HDI-BDO based TPU was chosen as a model. Replacing HS’s terminal HDI residues with aromatic PPDI, TODI, and MDI (the corresponding TPUs are named as 2P, 2TO, and 2M, respectively) enabled broad tuning of TPU’s Young’s modulus while maintaining high tensile strength and elongation. Compared with linear PPDI and TODI, the bent and unsymmetrical MDI exhibits greater deviation from the central axis of the middle HDI-BDO segment, which reduces HS’s capability of three-dimensionally ordered packing. Therefore, 2P and 2TO show higher hydrogen bond content and crystallinity, stronger physical crosslinking network, and thus much higher Young’s modulus than 2M (75.6 MPa). Besides geometric structure, π–π stacking between HS’s terminal aromatic diisocyanates critically governs TPU’s physical crosslinking network. In 2P, π–π stacking induces torsion of the middle HDI-BDO segment and disrupts the neighboring hydrogen bonds, leading to a dense network with fine hard blocks. In contrast, the lateral methyl groups in TODI hinder π–π stacking, resulting in a sparse network with large hard blocks. Accordingly, 2TO exhibits a higher Young’s modulus (146.2 MPa) than 2P (124.0 MPa), but greater strain-rate sensitivity.

This study reports the fabrication of polypropylene (PP)-based microfiber webs (<1 µm) using a hybrid melt electrospinning/blown process with the aim of establishing a scalable and solvent-free platform for advanced lithium-ion battery separators. The primary objective was to address the inherent limitations of conventional melt electrospinning particularly the difficulty of achieving fiber thinning due to the high viscosity of polymer melts by incorporating auxiliary hot air flow and reducing the nozzle diameter from 1.0 mm to 0.3 mm. This modified configuration enables enhanced jet elongation and fiber diameter control under processing conditions relevant to industrial applications. The effects of nozzle temperature, hot air temperature, and applied voltage on fiber formation and jet behavior were systematically examined using highspeed charge-coupled device (CCD) imaging techniques. The results demonstrated that increasing both the hot air temperature and applied voltage significantly improved fiber thinning and uniformity, yielding an average fiber diameter of approximately 0.86 µm without evidence of thermal degradation. In contrast, elevated nozzle temperatures, while enhancing melt flowability, resulted in increased discharge rates and hindered fiber refinement when applied alone. These findings identify hot-air temperature as the most robust and controllable parameter for producing submicron fibers while maintaining the polymer integrity. Although the present study primarily focuses on morphological optimization and jet dynamics, future research will investigate the functional performance of fabricated microfiber webs as battery separators. Overall, the proposed hybrid process offers a technically feasible and environmentally sustainable route for the continuous production of fine PP-based fibers tailored for high-performance energy-storage applications.

Strong polyelectrolyte brushes (SPBs) play an important role in enabling material surface functionalization due to their unique stimuli-responsive properties. Although the unexpected pH responsiveness of SPBs has been revealed in the past ten years, it is still unclear if the pH-responsive properties of SPBs are affected by the brush thickness. In this study, we employed the positively charged poly[2-(methacryloyloxy)ethyl] trimethylammonium chloride (PMETAC) and negatively charged sodium poly(styrenesulfonate) (NaPSS) brushes as model systems to explore the effect of thickness on the pH-responsive properties of SPBs. The results demonstrate that the pH-responsive properties of SPBs manifest different dependences on the brush thickness. Specifically, for both PMETAC and NaPSS brushes, the pH-responsive hydration and stiffness are influenced by the thickness, and the pH-responsive wettability and adhesion are almost unaffected by the thickness. This work not only provides a clear understanding of the relationship between the brush thickness and the pH responsiveness of SPBs, but also offers a new method to control the pH-responsive properties of SPBs.

Polymers often exhibit multi-state conformational transitions with multiple pathways as temperature varies. However, characterizing the inherent features of these pathways is hindered by the lack of physical characterizations that can distinguish various transition pathways between complex and disordered states. In this work, we introduced a machine-learning framework based on spatiotemporal point-cloud neural networks to identify and analyze conformational transition pathways in polymer chains. As a case study, we applied this framework to the temperature-induced unfolding of a single semi-flexible polymer chain, simulated via coarse-grained molecular dynamics. We first combined spatiotemporal point cloud neural networks and contrastive learning to extract features of conformational evolution, and then we employed unsupervised learning methods to cluster distinct transition pathways and unfolding trajectories. Our results reveal that, with increasing temperature, semi-flexible polymer chains exhibit five distinct unfolding pathways: rigid rod → random coil; small toroid → large toroid → hairpin → random coil; rod bundle → hairpin → random coil; hairpin → random coil; and tailed structure → random coil. We further calculated the structural order parameters of those typical conformations with distinct transition pathways, we distincted five transition mechanisms, including the straightening of rigid rods, tightening of small rings, expansion of hairpin ends, symmetrization of rod bundles, and retraction of tailed structures. These findings demonstrate that our framework presents a promising data-driven approach for analyzing complex conformational transitions in disordered polymers, which might be potentially extendable to other heterogeneous systems like intrinsically disordered proteins.

Anion exchange membrane water electrolysis (AEMWE) synergize the kinetic merits of alkaline systems, zero-gap configurations and compatibility with non-noble metal catalysts, offering a promising pathway toward green hydrogen production. Nevertheless, practical exploitation was hindered by critical challenges: inferior alkaline stability, insufficient mechanical integrity, and detrimental hydrogen crossover of anion exchange membranes (AEMs), which compromise both device durability and operational safety. Here, we engineered a porous expanded polytetrafluoroethylene (e-PTFE)-reinforced poly(arylene quinuclidinium) membrane that enhances AEM mechanical robustness, prevents stress-induced rupture, and suppresses hydrogen crossover during electrolyzer operation. Specifically, the reinforced poly(arylene quinuclidinium) membrane (R-PTPQui) exhibited a tensile strength of 56 MPa and an elongation at break of 55%. Moreover, it effectively reduced hydrogen permeation in the electrolyzer, achieving an extremely low H₂-to-O₂ (HTO) value of 0.44 vol% at 0.1 A·cm⁻². The R-PTPQui-based electrolyzer achieved a high current density of 4.9 A·cm⁻² at 2.0 V and a Faradaic efficiency of 98.6% using a non-precious anode catalyst. These advances significantly strength the compatibility of poly(arylene quinuclidinium)-based AEMs for industrial-scale green hydrogen generation.

Due to environmental concerns and the oil crisis, biodegradable polymer foams have garnered increasing attention. Among all biodegradable materials, Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (P(HB-co-HV)) distinguishes itself with the advantage of being biodegradable in all natural environments. However, preparing P(HB-co-HV) foam with a fine cellular structure remains challenging. Herein, P(HB-co-HV) foams with a double melting peak structure were developed. P(HB-co-HV) samples were first heated briefly near the melting temperature to melt most of the crystals, followed by saturation and foaming at a lower temperature (foaming temperature). P(HB-co-HV) foams with cell sizes of 7.1–30.0 µm and relative densities ranging from 0.3 to 0.9 were prepared, and the foaming temperature window was as wide as 16 °C. The effect of heat treatment temperature and foaming temperature on the crystallization and cell structure was investigated through DSC and SEM. It was found that the high-melting temperature crystals generated during the saturation step significantly improved the cell structure of P(HB-co-HV), since these crystals can enhance the heterogeneous cell nucleation and hinder the cell growth during foaming. The low-melting temperature crystals were formed during foaming. In situ WAXD analysis during heating showed that the high- and low-melting peaks corresponded to HV-unit-excluded and HV-unit-included PHB crystals, respectively.

An efficient strategy has been developed to reconstruct chain folding and traversing of poly(L-lactide) (PLLA) during melt crystallization based on the selective hydrolysis of its amorphous regions. The molecular weights of the pristine PLLA (crystalline part), single stem, and single cluster were determined by gel permeation chromatography (GPC) according to their evolution during alkali hydrolysis. The maximum-folding-number (in a single cluster) and minimum-cluster-number (in one polymer chain) were obtained using these molecular weights. With the help of two numbers, the chain folding and traversing during the melt crystallization process (at 120 °C) of PLLA can be described as follows. Statistically, in a single polymer chain, there are at least 2 clusters consisting of up to 6.5 stems in each of them, while the rest of the polymer chain contributes to amorphous regions. Our results provide a new strategy for the investigation and fundamental understanding of the melt crystallization of PLLA.

A series of imido-vanadium(V) complexes bearing bidentate phenoxy-phosphine ligands were synthesized and characterized by NMR, elemental analysis, and single-crystal X-ray diffraction. These complexes demonstrated excellent catalytic performance in ethylene/1-hexene copolymerization, achieving high activities of 12.0×10⁶–49.0×10⁶ g_polymer ·(mol_V)⁻¹·h⁻¹ and affording random copolymers with tunable 1-hexene incorporations. These catalysts also exhibited ultrahigh activity, up to 112.2×10⁶ g_polymer ·(mol_V)⁻¹·h⁻¹, in ethylene/norbornene (NB) copolymerization, yielding cyclic olefin copolymers with adjustable NB incorporations. Remarkably, these catalysts demonstrated exceptional tolerance toward polar functional groups, enabling efficient copolymerization of ethylene with both 10-undecen-1-ol (U-OH) and 5-norbornene-2-methanol (NB-OH), incorporating about 2 mol% polar comonomers with high efficiency. Different with the catalytic behaviors in copolymerization of ethylene with nonpolar comonomers, the catalytic activities in E/U-OH copolymerization (25.7×10⁶ g_polymer ·(mol_V)⁻¹·h⁻¹) were much higher than those in E/NB-OH copolymerization (8.6×10⁶ g_polymer ·(mol_V)⁻¹·h⁻¹). DFT calculations revealed that the catalytic performance is governed by synergistic electronic and steric effects. For E/NB copolymerization, strong preference for cyclic olefins was attributed to favorable transition state stabilization. In polar comonomer systems, steric effects were predominant, with NB-OH exhibiting a larger buried volume around vanadium center upon coordination compared to U-OH. Overall, this work provides fundamental insights into vanadium-catalyzed (co)polymerization and offers new strategies for tailored polyolefin design.

Polycaprolactam (PA6) is an important engineering plastic known for its excellent strength and processability, making it widely applicable in the automotive and transportation industries. Previous studies have demonstrated that incorporating a small amount of organic-modified montmorillonite (OMMT) can significantly enhance the gas barrier properties of PA6. Based on PA6/OMMT, this study further introduced maleic anhydride-grafted ethylene-octyl copolymer (mPOE) and polytetrafluoroethylene (PTFE). Morphological characterization revealed the successful manipulation of the microstructure within this toughening system, revealing a distinctive tassel bundle morphology in the ternary blend of PA6/mPOE/PTFE. in the quaternary PA6/OMMT/mPOE/PTFE system, scanning electron microscopy (SEM) analysis demonstrated that the special “tassel bundle (TB)” morphology could induce an ordered arrangement of OMMT nanosheets, leading to synergistic improvements in both toughness and gas barrier performance. These findings offer promising potential for applications requiring simultaneously high gas barrier properties and enhanced toughness, particularly in hydrogen storage tanks and related industrial fields.