Macromolecular Rapid Communications最新文献

Biocompatible elastomers that combine high toughness with excellent elastic restorability hold great promise for biomedical applications; however, achieving the toughness and elasticity simultaneously in a single material remains a significant challenge. In this study, polycaprolactone-based poly(urethane-urea) (PUU) elastomers that exhibit excellent mechanical properties as well as superb biocompatibility are reported. Hydrazide chain extenders are employed to introduce abundant hydrogen bonds to ensure high toughness, while isophorone diisocyanate, having a bulky steric structure, is used to limit the aggregation of hard segment clusters and suppress strain-induced crystallization, thereby enhancing the elastic recovery. The obtained PUU elastomer achieves a toughness of 333.2 MJ m^-3 and a strength of 63.7 MPa, with low residual strains of ∼11% and ∼44% at 100% strain and 400% strain, respectively. In addition, the elastomer demonstrates good healability, recyclability, and biocompatibility. These combined properties position the material as a promising candidate for biomedical applications and provide valuable insights for future material design.

Light-emitting polymers (LEPs) combine the luminescent properties of organic emitters with the structural versatility of polymers, supporting applications in solid-state display, chemical sensing, and bioimaging, owning to the efficient tuning of their performance across multiple scales, from monomer units and chain sequence to solid-state packing and solution processing. Recent strategies have expanded emission color space, improved quantum yields, and simplified design rules, evolving from traditional π-conjugated systems to mechanisms driven by aggregation and charge transfer. Yet this multiscale flexibility also creates a vast and complex design space, where the interplay of monomer choice, polymer architecture, and processing methods makes it impossible to exhaustively map their structure-property relationships by empirical means. In this perspective, we review the development of recent design strategies in LEPs, highlighting the key experimental challenges they reveal, and discuss how data-driven approaches, particularly machine learning, can help navigate this complexity and accelerate the discovery and optimization of next-generation LEPs.

Machine learning applications in polymer science are often inefficient due to molecular representations that neglect the inherent hierarchical and statistical nature of macromolecules. This work introduces a structure-aware graph convolutional network (GCN) framework that addresses this limitation by treating polymer samples as statistical ensembles. The approach utilizes a hierarchical graph representation where nodes correspond to monomer units and explicitly integrates molecular mass distribution (MMD) data to account for sample dispersity. A key innovation is an ensemble-based training strategy using topologically realistic graphs generated on-demand via an optimized kinetic Monte Carlo simulation. The model's efficacy was validated on a broad range of tasks. On synthetic data, it achieved more than 98% accuracy in classifying complex polymer architectures. When applied to a large experimental dataset, the model predicts glass transition temperatures (T_g) with high accuracy (R² = 0.89 ± 0.01). Crucially, a fine-tuning experiment demonstrated that the model could successfully learn the physically / chemically grounded relationship between T_g and molar mass by integrating MMD information. This work establishes a robust and physically realistic paradigm for polymer informatics, enabling more accurate property predictions and paving the way for accelerated in silico material design.

Crystallization of poly(ethylene glycol) (PEG) greatly debase the quality of printing and coating during drying, where it is used as a dispersant. In this work, we have investigated the drying process of aqueous droplet of poly(ethylene glycol) (PEG) as a function of molecular weight (M_w). It shows that PEG would crystallize on a hydrophilic surface but form an amorphous deposit on a hydrophobic surface at a humidity (RH) of 40% when M_w ≤5000 g/mol. However, PEG would crystallize regardless of the surface and RH when M_w is above 10 000 and 20 000 g/mol. By regulating PEG concentration, molecular weight, and RH, the droplet can be dried into an amorphous deposit for over 24 h. Raman spectroscopy and low-field nuclear magnetic resonance (LF-NMR) indicate that the water molecules bound to PEG chains (M_w ≤5000 g/mol) under slow drying inhibit their crystallization.

Fullerenes attract much interest due to the potentials to various applications. However, their insolubility in water and some organic solvents often hinders development. Herein, poly(ethylene glycol) (PEG), polyvinylpyrrolidone (PVP), poly(vinyl alcohol) (PVA), polyacrylic acid (PAA), and Pluronic L64 and 17R4, are attempted for dispersing fullerene in water via ultrasonication, and some of these are found to disperse an exceedingly large amount. The maximum concentration of C₆₀ is achieved with Pluronic L64, being 9.8 g/L (13.6 mm) without re-aggregation for a long time. Electron paramagnetic resonance (EPR) spectroscopy shows a significant amount of radical species existing in the fullerene-polymer complexes, which are stable for several weeks. DLS and TEM exhibit the formation of nanoparticles, and NMR, FT-IR, and MALDI-TOF MS are used to characterize the fullerene nanoparticles-polymer complexes. The aqueous dispersions of the complexes can be dried and redispersed in water and polar organic solvents. Column chromatographic separation is performed to give unreacted fullerene and fullerene-polymer complexes, the latter of which shows a strong EPR signal. Density functional simulations reveal partial electron transfer from the PEG segment to fullerene, which causes charge separation in the complexes, resulting in the excellent dispersibility in water, while the poly(propylene glycol) (PPG) segment likely assists the complexation by hydrophobic interactions with fullerene.

Developing high-efficiency antifouling nanofiltration (NF) membranes is crucial to address the dual challenges of low separation selectivity and severe membrane fouling in lithium extraction from high Mg²⁺/Li⁺ ratio salt-lake brines. This study presents an efficient strategy based on one-step dip-coating surface modification. By grafting 1, 2-epoxy-3,3,3-trifluoropropane (TFO) molecules onto a PEI-TMC polyamide (PA) base membrane, a unique bipolar electrostatic potential reconstruction was triggered, simultaneously and significantly enhancing both the separation selectivity and antifouling performance of the membrane. In simulated high Mg²⁺/Li⁺ ratio brine (2000 ppm, Mg²⁺/Li⁺= 30:1), the PA-TFO_0.75 membrane demonstrated exceptional integrated performance by achieving a high Li⁺/Mg²⁺ selectivity of 20.5 (9.76 times higher than commercial NF membranes) while maintaining a high water permeance of 14.65 L m^-2 h^-2 bar^-1, and exhibiting an outstanding flux recovery ratio (FRR) approaching 100.6% (a 151% improvement over the pristine membrane), thereby meeting industrial fouling resistance standards. Critically, this strategy enabled the continuous fabrication of large-area membranes (60 m × 0.298 m). The assembled spiral-wound module (1812-type) retained a Li⁺/Mg²⁺ selectivity of 19.5 in the same simulated brine, providing an efficient, antifouling, and scalable industrial-scale solution for lithium extraction from high Mg²⁺/Li⁺ ratio salt lakes.

Herein, we report water-assisted microphase separation of sodium acrylate (ANa) random copolymers bearing crystalline octadecyl or docosyl groups. The random copolymers are obtained from free radical copolymerization of t-butyl acrylate and octadecyl or docosyl acrylate (C18A or C22A), followed by the post-modification of the copolymers. The bulk random copolymers efficiently absorb water (13-37 wt.%) therein under humid conditions in relative humidity 90% above the melting temperature and induce the microphase separation of the hydrophobic alkyl groups and the hydrophilic ANa/main chains containing absorbed water. The phase separation bahavior, morphology, and domain spacing depend on the composition and weight fraction of the hydrophobic groups and hydrophilic segments. Typically, ANa/C18A (5/5 - 2/8) random copolymers form water-absorbed body-centered cubic or water-intercalated lamellar structures with 5-7 nm domain spacing. ANa/C18A (6/4) random copolymer not only forms a dry and crystalline lamellar structure below the melting temperature of the octadecyl groups but also stably maintains an amorphous lamellar structure above the melting temperature at least up to 150°C via the segregation of the polar main chains and octadecyl pendants.

Polyethylene glycol (PEG) plays a central role in nanomedicine, providing essential properties such as the stealth effect. However, the emergence of anti-PEG antibodies (APAs) increasingly undermines these benefits, raising concerns about safety and efficiency. This creates an urgent need for PEG alternatives. Randomized PEG (rPEG) represents a conceptually new strategy that preserves the PEG-like structure and performance while markedly reducing antigenicity. In this work, rPEG is employed as a non-antigenic A-block in ABA-type polymeric micelles (PMs). To enhance drug loading capacity beyond conventional PMs, the hydrophobic middle block is composed of poly(2-phenyl-2-oxazine) (PPheOzi). rPEG is synthesized by anionic ring-opening polymerization, PPheOzi by cationic ring-opening polymerization, and the combined rPEG-b-PPheOzi-b-rPEG triblock copolymers are linked via copper-catalyzed azide-alkyne cycloaddition. The formulations exhibit a distinct correlation between the solubilization of Efavirenz and the systematically varied rPEG composition, ranging from outstanding to moderate micelle drug loading capacities. A fundamental preclinical safety profile was established through investigations in murine fibroblasts and human peripheral blood mononuclear cells (PBMCs). Competitive enzyme-linked immunosorbent assays (ELISA) revealed a pronounced reduction in APA affinity in comparison to PEG. Taken together, the synergistic combination of rPEG and PPheOzi establishes a non-antigenic micellar platform capable of achieving high drug loadings.

The development of non-fullerene acceptors (NFAs) has driven significant advancements in organic solar cells (OSCs), resulting in power conversion efficiencies (PCEs) approaching 20% and positioning OSCs for practical applications. Notably, the recently introduced fused-ring A-DA'D-A type NFAs, especially those called Y-series NFAs, have propelled the field forward due to their strong near-infrared (NIR) absorption, adaptable structural features, and efficient molecular stacking, which collectively enhance charge transfer, minimize energy losses, and improve OSC performance. This review first summarizes the progression of Y-series NFAs from Y1 to the epoch-making acceptor Y6. Recent advances in fused-ring A-DA'D-A type NFAs are then discussed, with a focus on design strategies that modify structural parameters, such as side-chains, central cores, end-capping groups, and π-spacers. The advantages of each NFA are analyzed in relation to their corresponding polymer donors. The influence of molecular structure and optoelectronic properties of NFAs on the morphology of the donor/acceptor (D/A) active layer, charge transfer dynamics, and device performance is examined. Finally, the review identifies current challenges and outlines future directions for the development of Y-series NFAs in OSCs.