Chinese Journal of Polymer Science最新文献

D-π hybridization is a key structural feature that may significantly affect the intrinsic electronic properties of metallopolymers. Herein, we present the electrosynthesis and memristive properties of metallopolymers using the distinct d-π hybridization monomers R₁ and R₂. R₁ (Ru^II-(tpz)Cl₂) features tetradentate ligands (tpz, 6,6′-di(1H-pyrazol-1-yl)-2,2′-bipyridine) enforcing quasi-octahedral geometry; R₂ (Ru^II-(bpp)₂) incorporates tridentate ligands (bpp, 2,6-di(1H-pyrazol-1-yl)pyridine) inducing pronounced geometric distortion. The planar ligand (tpz) in R₁ facilitates ordered molecular assembly through high conformational rigidity and extensive π-π stacking, resulting in increased molecular densities and enhanced morphological uniformity compared to R₂ metallopolymers. Due to pyrazole’s weaker π-acceptance and stronger σ-donation compared to pyridine, R₁ exhibits a 119 nm red-shift in metal-to-ligand charge transfer (MLCT) band and a 30 mV anodic shift in Ru^+2/+3 redox potential relative to R₂. Coupled with a reduced HOMO–LUMO gap, the uniform and ordered structure leads to a lower conductance decay constant in R₁. Additionally, R₂ metallopolymers exhibit superior memristive performance (characterized by lower switching voltage and higher switching ratio) via redox-induced aromatic transitions in axial ligands enhancing electronic delocalization. This work compares two metallopolymers with different ligand geometries, revealing how this difference leads to distinct charge transport and memristive behaviors.

Magnetic resonance imaging (MRI) is one of the most widely used diagnostic techniques. Iron oxide nanoparticles, as a promising kind of contrast agents, have attracted intense research interest due to their low toxicity and superparamagnetism. However, it is still a great challenge to prepare ideal iron oxide based contrast agents with high uniformity, excellent water solubility and biocompatibility. In this paper, a novel water-soluble polymer ligand pentaerythritol tetrakis 3-mercaptopropionate-poly(N-vinyl-2-pyrrolidone) (PTMP-PVP) was used as a capping reagent to prepare iron oxide nanoparticles MIONs@PTMP-PVP through one-step co-precipitation of iron precursors in aqueous solution at 100 °C. The obtained nanoparticles MIONs@PTMP-PVP had a small size and narrow size distribution, and they were found to be biocompatible as determined through CCK-8 assay and histology analysis. In vivo MRI study demonstrated that the obtained MIONs@PTMP-PVP can be potentially used as an effective T₂-weighted MRI contrast agent.

The preparation and functionalization of polymeric capsules attract intense attention due to their application in various areas. Herein we presented an amphiphilic alternating copolymer (ACP)-based microcapsule which is both robust and readily-functionalized through interfacial click polymerization. A water-in-oil emulsion was constructed to act as the reaction medium, the hydrophilic 1,3-butadiene diepoxide (BDE) in water phase reacted with the oleophilic 1,4-dibutanedithiol (BDT) in oil phase at the water-oil interface to form the amphiphilic ACP named poly(2,3-dihydroxy butylene-alt-butylene dithioether) (abbreviated as P(DHB-a-BDT) below), which would deposite in situ to form the micro-sized capsules. Significantly, the dried capsules are robust enough to be rehydrated once the water was added and almost restored their original morphologies. Further elucidation showed that the Young’s modulus of these capsules exceeded 1 GPa. As long as we know, it is the first time for the mechanical properties of the ACP-based microstructures being investigated. Besides, functionalization could be achieved simultaneously with the formation process. As a proof of concept, positive-charged capsules were successfully obtained through click copolymerization. Stemming from the unique characteristics of amphiphilic ACPs which combined both merits of click chemistry and interfacial reactions, all these features of the current method as well as the resultant capsules may promote the application of the polymeric capsules.

Glucose, ascorbic acid (AA), uric acid (UA), and dopamine (DA) are vital biomarkers whose dynamic concentrations correlate with critical diseases; however, multiplexed detection remains challenging for conventional electrochemical sensors because of their limited sensitivity and selectivity. Here, we present a millimeter-scale all-poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) organic electrochemical transistor (OECT) platform that integrates dual-mode sensing with enzyme/metal-free operation for ultrasensitive biomarker monitoring. By engineering polycrystalline PEDOT:PSS channels via H₂SO₄ post-treatment, the device achieves record-high conductivity (about (2312.0±29.9) S·cm⁻¹), maximum transconductance (about (2.82±0.12) mS), and on/off ratio (about 210.0±7.8), enabling signal amplification at low gate voltages. The dual-mode strategy combines the selectivity of electrochemistry with the sensitivity of OECTs, realizing simultaneous detection of glucose, AA, UA, and DA with clinical-level sensitivity: detection limits down to 8 nmol·L⁻¹ (glucose), 0.5 nmol·L⁻¹ (AA), 5 nmol·L⁻¹ (DA), and 0.5 nmol·L⁻¹ (UA). Validation using human urine samples yielded recovery rates of 94%–114%. This flexible sensing platform provides a new pathway for the development of wearable biosensors for precision diagnostics.

Biopolymeric nanocomposites have attracted considerable attention because of their biocompatibility, biodegradability, and unique physicochemical properties. It is essential to manufacture three-dimensional (3D) biocompatible micro/nanostructures using biopolymeric nanocomposites. Herein, we demonstrate the high-fidelity fabrication of biocompatible 3D features with sub-50 nm resolution using femtosecond laser direct writing (FsLDW) of a biopolymeric nanocomposite composed of egg white and sulfonated graphene (S-graphene). The biopolymer nanocomposite acts as a negative photoresist suitable for water-based lithography. The introduction of S-graphene not only dramatically lowered the laser power threshold but also significantly modulated the morphology of the 3D features constructed by FsLDW. Microstructures with porous, rough, or smooth morphologies were obtained by optimizing the S-graphene concentration and laser scanning speed. The fabricated egg-white/S-graphene microstructures exhibited biocompatibility and environmental degradability. Egg white/S-graphene was also employed to fabricate diffractive gratings with superior optical quality. This study provides a promising method to manufacture biocompatible 3D features with controllable morphology, which has potential applications in biological and photonic fields.

Azobenzene-based polymer actuators show great promise for photoactuation owing to their unique photoisomerization behavior and tailorable molecular programmability. However, conventional systems are limited by inadequate mechanical robustness, self-healing, and recyclability, hindering their practical implementation. Herein, we present a high-performance azobenzene-functionalized polyurethane (AzoPU) elastomer actuator designed via molecular engineering of photoactive azobenzene moieties and dynamic disulfide bonds. AzoPU exhibits exceptional mechanical properties with retained performance after multiple reshaping cycles, enabled by well-engineered hard-soft segments and synergistic stress dissipation from weak covalent bonds/hierarchical hydrogen bonds. It achieves over 93% self-healing efficiency at room temperature owing to the synergistic interplay of disulfide bonds in the polymer backbone and intermolecular hydrogen bonds. Furthermore, it demonstrates remarkable light-triggered actuation behavior, achieving a phototropic bending angle exceeding 180° toward the light source within 45 s. To showcase its practical potential, proof-of-concept photoactuated devices with flower-, hook-, and gripper-like and local-orientation processed strip-shaped structures were fabricated, which exhibited rapid and reversible light-triggered deformation. This study proposes a novel strategy for the development of intelligent polymeric materials that integrate light responsiveness, self-healing, and recyclability, thus holding great promise for applications in flexible electronics, smart actuators, and sustainable functional materials.

The equilibrium dynamics and nonlinear rheology of unentangled polymer blends remain inadequately understood, especially regarding the influence of short-chain matrix length N_S on the structure and rheological behavior of dispersed long chains. Using molecular dynamics simulations based on the Kremer-Grest model, we systematically explore the N_S-dependence of static conformations, equilibrium dynamics, and nonlinear shear responses in unentangled long-chain/short-chain polymer blends. Our results demonstrate a decoupling between the static and dynamic sensitivity to N_S: while the static chain size, R_g, follows Flory theory with slight swelling at small N_S due to incomplete excluded volume screening, the diffusion coefficient, D, and the relaxation time, τ₀, exhibit a strong, non-monotonic N_S-dependence, transitioning from monomeric friction dominance at small N_S to collective segmental rearrangement at large N_S. Additionally, we observe partial decoupling between the viscous and normal stress responses: while the zero-shear viscosity, η, is strongly N_S-dependent, the first and second normal stress coefficients, Ψ₁ and Ψ₂, collapse onto universal curves when scaled by the dimensionless shear rate, (dot{gamma}tau_{0}), suggesting a common mechanism of orientation and stretching. Under shear, long chains compress in the vorticity direction λ_z ∼ Wi^−0.2, which reduces collision frequency and contributes to shear thinning, while the scaling of weaker orientation resistance m_G ∼ Wi^0.35 reflects hydrodynamic screening by the short-chain matrix. These findings highlight the limitations of single-chain models and emphasize the necessity of considering N_S-dependent matrix dynamics and flow-induced structural changes in understanding the rheology of unentangled polymer blends.

Early knee osteoarthritis (KOA) is characterized by progressive degeneration of the articular cartilage, synovial inflammation, and excessive accumulation of reactive oxygen species (ROS). At present, intra-articular injection of hyaluronic acid (HA) is widely used to alleviate symptoms; however, its lubrication persistence, antioxidant, and anti-inflammatory abilities are limited, and it is difficult to effectively delay the early process of cartilage degeneration. Based on this, hyaluronic acid-g-lipoic acid (HA-LA) was synthesized by esterification reaction, and HA-LA microspheres were prepared by a reversed-phase emulsion method, which was combined with a macromolecular HA-LA solution to form injectable hydrogels. The objective of this study was to evaluate the efficacy of an injectable hydrogel based on hyaluronic acid-g-lipoic acid microspheres (HA-LA MS) for the treatment of KOA and to verify its injectability, lubricity, reactive oxygen species (ROS) scavenging ability, and anti-inflammatory effects. The results show that the HA-LA MS hydrogel has excellent shear thinning characteristics and continuous injectability, and its microsphere structure significantly reduces the interfacial friction coefficient through the rolling effect. In vitro experiments have shown that the hydrogel can efficiently scavenge ROS, reduce the expression of inflammatory factors, and is non-cytotoxic. The HA-LA MS injectable hydrogel has excellent lubricity, ROS scavenging ability, and anti-inflammatory effects in vivo, which can effectively delay the degeneration of early KOA cartilage, and its efficacy is significantly better than that of traditional hyaluronic acid, making it a promising intra-articular injection preparation.

Accelerated aging tests are widely used to rapidly evaluate the durability of materials, of which thermal-oxidative aging is the most common approach. To quantitatively predict the effects of multiple coupled factors, this study takes polyamide66 reinforced with glass fiber (PA66-GF) as a model system and proposed a high-precision paradigm for coupled thermal-oxidative aging. By integrating Arrhenius-type reaction kinetics with oxygen diffusion, a predictive formula that holistically captures the nonlinear synergistic effects of multiple factors was developed, thereby overcoming the limitations of traditional single-variable models. A systematic evaluation of the stepwise improved formulas through nonlinear fitting showed that the coefficient of determination (R²) increased from 0.223 to 0.803, elucidating the fundamental reason why conventional approaches fail in quantitative prediction. These formulae were further embedded as physical constraints into a physics-informed neural network (PINN), which further enhanced the predictive performance, with the proposed formula achieving a peak R² of 0.946. The results highlight that robust data fitting alone is insufficient; the decisive factor for the success of PINN lies in whether the embedded formula faithfully reflects the underlying physical mechanisms. When applied to polyamide 6 reinforced with glass fiber (PA6-GF), the Formula-constrained PINN maintained a high level of accuracy (R²=0.916), demonstrating its strong cross-system generalizability. In summary, this work establishes a robust hybrid physics-machine learning framework that combines high accuracy with transferability for predicting the thermal-oxidative aging behavior of composite material systems.