Journal of Polymer Science最新文献

Passive radiative cooling, as a zero-energy, environmentally friendly refrigeration technology, holds significant application potential in mitigating global warming and related fields. However, a critical bottleneck persists: the inherent trade-off between its optical cooling performance and mechanical robustness, which severely limits its practical deployment. This paper proposes a one-pot ball milling process that simultaneously refines, mixes, and chemically fuses microcrystalline cellulose (MCC) and silica (SiO₂) to fabricate hierarchical MCC/SiO₂ hybrid particles. The engineered fillers are then seamlessly integrated into a polydimethylsiloxane (PDMS) matrix, ultimately yielding flexible, mechanically robust, and highly efficient radiative cooling composite MCC/SiO₂/PDMS film for synergistic enhancement of optical and mechanical properties. The optimized film exhibits a record-high solar reflectance of 94.58% and a long-wave infrared emissivity of 95.22%. Notably, it breaks the traditional performance trade-off: the incorporation of MCC/SiO₂ enhances the mechanical strength and toughness of PDMS by 1.6 MPa and 1.02 MJ cm⁻³. Outdoor tests demonstrate an average sub-ambient cooling effect of 8°C under direct sunlight. This work provides a novel paradigm for designing sustainable high-performance materials through microstructural engineering of hybrid fillers.

This study develops a predictive model for the Flory–Huggins interaction parameter (χ) using quantum chemical descriptors and accounting for temperature effects. A dataset of 2474 χ values across 19 polymers and 88 solvents was utilized. An optimized convolutional neural network (CNN) model, incorporating 30 selected features, demonstrated superior performance, achieving a mean absolute error (MAE) of 0.140, a root mean squared error (RMSE) of 0.177, and a coefficient of determination (R ²) of 0.973 on the test set. These results represent a significant improvement over existing quantitative structure–property relationship (QSPR) models (particularly for those with test set sizes exceeding 150 samples, which typically report RMSE > 0.25 and R ² < 0.94). Mechanism analysis revealed that χ is primarily governed by charge-related properties (e.g., the most positive hydrogen charge in the polymer, H_p, and the most negative atomic charge in the solvent, N_s), polarity properties (polymer and solvent dipole moments, μ_p and μ_s), and solvent thermal energy (E_s). These factors collectively regulate the balance between specific molecular interactions and disorder effects. This study delivers not only a state-of-the-art predictive tool but also physical insight, establishing a new paradigm for the rational design of advanced polymer materials.

Polypropylene alloys exhibit a complex multiscale structure, posing challenges for traditional analytical methods in uncovering the relationships between structural and mechanical properties. To address this, a novel machine learning framework that integrates graphical modeling with regression techniques is proposed to enhance interpretability and predictive accuracy. Specifically, a Bayesian network is constructed to elucidate the dependencies among structural variables, guiding feature selection in the regression stage, and a hierarchical XGBoost regression model based on this network (BNXGB) is developed to predict impact strength (IS) and flexural modulus (FM). Compared to a conventional XGBoost model (XGB), BNXGB demonstrates superior performance, achieving higher R ² score for both IS and FM. More importantly, BNXGB handles missing input features by leveraging the network to impute them from parent nodes, thereby maintaining robust performance under incomplete data. Even under the extreme condition when all features except the four root nodes are missing, BNXGB still preserves reasonable R ² scores for both IS and FM, whereas XGB's performance drops sharply. These results demonstrate the robustness and practical applicability of the BNXGB framework for polymer property prediction under missing data, potentially reducing the need for exhaustive material characterization.

Polymer micelles are established nanocarriers for hydrophobic molecules, but their use as hosts for sensors of physiological parameters remains underexplored. This work investigates the incorporation of phosphorescent transition metal complexes into block copolymer micelles and examines how composition and structure affect micellar stability and photophysical properties. The study also evaluates their potential as a novel class of oxygen nanosensors with lifetime-based response. Micelles are prepared from block copolymers of poly(ethylene glycol) (PEG) with diverse hydrophobic blocks: polystyrene (PS₃₅-b-PEG₁₁₅), poly(methyl methacrylate) (PMMA₅₅-b-PEG₉₅), polybutadiene (PBd₉₀-b-PEG₁₁₅), polydimethylsiloxane (PDMS₁₅-b-PEG₁₁₅), and polycaprolactone (PCL₄₅-b-PEG₁₁₅). Six phosphorescent complexes, including three Pt(II) and three Ir(III) species, serve as payloads. Screening of “complex@block copolymer” pairs based on sedimentation stability, phosphorescence decay, and oxygen sensitivity identifies Ir3@PCL₄₅-b-PEG₁₁₅ loaded with 2 wt.% of Ir3 as the optimal biosensing system. For this system, loading efficiency, size distribution, cross-sensitivity to environmental parameters, Stern–Volmer plots, and MTT cytotoxicity are assessed. Confocal microscopy and phosphorescence lifetime imaging microscopy (PLIM) demonstrate efficient internalization into CHO-K1 and HeLa cells. The sensor shows distinct lifetime responses under hypoxic, normoxic, and intermediate oxygenation, enabling quantitative intracellular oxygen sensing with pO₂ resolution of 35–40 mm Hg in both cell monolayers and suspensions.

Foam materials are widely used for acoustic absorption due to their light weight, high porosity, and energy absorption. Conventional foams exhibit limited mid-high frequency sound absorption, linked to their cellular structure, and matrix toughness. This paper introduces mesoporous ceramic (M-C) and chlorinated poly(propylene carbonate) (CPPC) into polyurethane (PU) foam to fabricate M-C/CPPC/PU foam composites with a nano-micro hierarchical cellular structure through physically confined foaming. M-C acted as a heterogeneous nucleating agent, refining the cellular structure of PU foam with cell sizes below 250 μm, which enhanced multiple reflections and scattering of sound waves within the cellular structure. CPPC enhanced interfacial bonding, facilitating the transfer of sound waves incident on cell walls to M-C particles with nanoscale open-cell structures, and further extending sound propagation loss paths within the PU matrix. The M-C/CPPC/PU foam composites with small cells (cell size of 200–250 μm, extending propagation paths) and elastic-rigid balance (compressive modulus of 110–120 kPa, promoting penetration) achieved superior acoustic absorption, with an average sound absorption coefficient (ASAC) of 0.851 and 0.965 at 1600 Hz, while maintaining notable thermal insulation properties. This paper significantly improves the broadband acoustic absorption (1000–5000 Hz) of foam materials, providing a technical foundation for effective environmental noise control.

This study examines the synthetic and curing processes for bi- and trifunctional end-capped phthalonitrile (PN) Schiff base resins derived from phenolic aldehydes. Characterization of the resins was conducted via proton (¹H) and carbon (¹³C) nuclear magnetic resonance (NMR) spectroscopy, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), mechanical analysis (torsion), rheometry, in-source fast pyrolysis mass spectrometry (FP-MS), and solid-state NMR. The processing window for each resin was determined using DSC, with both bifunctional resins exhibiting relatively low melting points (57°C and 62°C) and large processing windows greater than 200°C. Each resin was self-curing due to the imine and PN curing groups present and displayed a range of viscosities from 546 to 10,800 cP at 175°C. The resins were degassed and cured into their respective polymers by post-curing up to 380°C. The resulting polymers all exhibited excellent thermal stability with a T _d5% above 500°C in both an inert (N₂) and air atmosphere as well as a 73%–75% char yield under N₂. Excellent toughness was observed for three of the resins with an initial storage modulus (G' at 50°C) above 1530 MPa and moderate modulus retention. This combination of properties suggests the multi-functional resins are excellent materials for high-temperature and mechanical applications.

In ferroelectric thin film fabrication on silicon and glass substrates, Pt bottom electrodes are commonly used. However, transparent fluorine-doped tin oxide (FTO) electrodes improve film crystallinity. We investigated the effect of bottom electrodes on the ferroelectric, piezoelectric, and switching properties of PVDF-TrFE thin films deposited on FTO and Pt electrodes. PVDF films on FTO exhibited superior crystallinity, larger remanent and saturated polarizations, higher piezoelectric coefficients, and faster switching compared to films on Pt. Local domain switching experiments showed lower activation energy for domain wall movement in FTO-based films, explaining their faster switching. These results highlight the potential of PVDF-TrFE thin films for nonvolatile memory applications depending on electrode type.