Chinese Journal of Polymer Science最新文献

Although Ziegler-Natta (Z-N) polyolefins have been widely used as raw materials to produce pharmaceutical or food packaging, the migration of acid scavengers, an additive usually introduced in Z-N polyolefins, from the packaging to its contents has not been reported. In this work, the migration of the two most used acid scavengers, calcium stearate (CaSt₂) and zinc stearate (ZnSt₂), from a Z-N polypropylene random copolymer (PPR) into water during autoclaving at 121 °C were comparatively investigated. It was found that, for PPR plates containing 0.1 wt% CaSt₂ or ZnSt₂ (PPR-0.1CaSt₂, PPR-0.1ZnSt₂, respectively), the concentration of migrated calcium ion into water increased with autoclaving time, while that of zinc ion was much lower at same treatment durations and did not show a significant increase with treatment time. Interestingly, after removing all plates and acidification treatment, a considerable amount of stearic acid was detected in sterilized water for PPR-0.1ZnSt₂, but no such significant stearic acid was detected in sterilized water for PPR-0.1CaSt₂. Based on the structural evolution of the two soaps upon heating, possible mechanisms for the different migration behavior of CaSt₂ and ZnSt₂ from PPR into water during autoclaving treatment were proposed. Our results suggest that the migration issue of acid scavengers is worthy of attention in pharmaceutical packaging materials produced from Z-N polyolefins.

Polyelectrolytes (PEs) are polymers carrying ionizable groups along the chain backbone and play an important role in life and environmental sciences, industrial applications and other fields. Due to the complicated topological structure and electrostatic correlations of PEs, PEs exhibit very rich phase behavior and morphologies in both bulk and confined solutions. So far, many theories, simulations and machine learning approaches have been proposed to study the behavior of polyelectrolyte solutions, especially the intrinsic structure-property relationships. In this perspective, from a personal point of view, we present several recent trends in polyelectrolyte solutions. The main themes considered here are accelerated development of sequence-defined polyelectrolyte (SDPE) via artificial intelligence technology, liquid-liquid phase separation in bulk SDPE solutions, adsorption behaviors of SDPE in the vicinity of a single dielectric surface, and surface forces between two charged surfaces mediated by SDPE solutions.

In this study, we prepared unentangled and slightly entangled poly(_L-lactic acid) telechelic ionomer samples (M_n=5 and 16 kg/mol) based on sodium sulfonate groups. The telechelic samples exhibit extremely slow crystallization kinetics below the melting temperature T_m and above the glass transition temperature T_g, which enables us to examine the linear viscoelasticity of the ionomer melt samples therein. The application of either the shear flow (at 85 °C) or elongational flow (between 70 and 90 °C) strongly accelerates the crystallization, leading to strong strain hardening and formation of highly oriented α crystals. Depending on the relative average rates of the strain-induced dissociation and strain-induced crystallization, the stress evolution can be classified into two cases, and the critical work for strain-induced crystallization is higher in case where the strain-induced dissociation occurs earlier than the strain-induced crystallization.

The performance and corresponding applications of polymer nanocomposites are highly dominated by the choice of base material, type of fillers, and the processing ways. Carbon black-filled rubber composites (CRC) exemplify this, playing a crucial role in various industries. However, due to the complex interplay between these factors and the resulting properties, a simple yet accurate model to predict the mechanical properties of CRC, considering different rubbers, fillers, and processing techniques, is highly desired. This study aims to predict the dispersion of fillers in CRC and forecast the resultant mechanical properties of CRC by leveraging machine learning. We selected various rubbers and carbon black fillers, conducted mixing and vulcanizing, and subsequently measured filler dispersion and tensile performance. Based on 215 experimental data points, we evaluated the performance of different machine learning models. Our findings indicate that the manually designed deep neural network (DNN) models achieved superior results, exhibiting the highest coefficient of determination (R²) values (>0.95). Shapley additive explanations (SHAP) analysis of the DNN models revealed the intricate relationship between the properties of CRC and process parameters. Moreover, based on the robust predictive capabilities of the DNN models, we can recommend or optimize CRC fabrication process. This work provides valuable insights for employing machine learning in predicting polymer composite material properties and optimizing the fabrication of high-performance CRC.

The quest for scalable integration of monolayer graphene into functional composites confronts the bottleneck of high-fidelity transfer onto substrates, crucial for unlocking graphene’s full potential in advanced applications. Addressing this, our research introduces the camphor-assisted transfer (CAT) method, a novel approach that surmounts common issues of residue and structural deformation endemic to existing techniques. Grounded in the sublimation dynamics of camphor, the CAT method achieves a clean, contiguous transfer of centimeter-scale monolayer graphene onto an array of polymer films, including ultra-thin polyethylene films. The resultant ultrathin graphene-polyethylene (gPE) films, characterized by their exceptional transparency and conductivity, reveal the CAT method’s unique ability to preserve the pristine quality of graphene, underscoring its practicality for preparing flexible transparent electrodes by monolayer graphene. In-depth mechanism investigation into the camphor sublimation during CAT has led to a pivotal realization: the porosity of the target polymer substrate is a determinant in achieving high-quality graphene transfer. Ensuring that camphor sublimates initially from the polymer side is crucial to prevent the formation of wrinkles or delamination of graphene. By extensive examination of CAT on a spectrum of commonly used polymer films, including PE, PP, PTFE, PI and PET, we have confirmed this important conclusion. This discovery offers crucial guidance for fabricating monolayer graphene-polymer composite films using methods akin to CAT, underscoring the significance of substrate selection in the transfer process.

An improved X-ray apparatus that combines tensile testing and X-ray diffraction has been designed and constructed to conduct timeresolved experiments during uniaxial stretching. By utilizing mortise-like clamping jaws and dogbone-shaped specimens, this setup allows for the simultaneous recording of high-quality mechanical responses and 2D diffraction patterns due to the minimization of experimental errors from sample slippage or premature fracture. Furthermore, the local extension ratio can be accurately determined based on thickness variation, and the Hermans' orientation function was demonstrated to be a reliable method with high accuracy to calculate the segmental orientation parameter 〈P₂〉 in elastomeric samples under high degree of stretching. In summary, this innovative tensile-WAXD instrument has proven to be a promising and powerful technique for investigating the “stress-deformation-segmental orientation” relationship in elastomers with high extensibilities.

Tumor-associated carbohydrate antigens (TACAs) provide a special class of tumor-specific antigens that show promising applications in cancer immunotherapy. However, the weak immunogenicity and structural complexity of TACAs are obstacles to their clinical application. Here, based on a fast and low-cost purification strategy for oligosaccharide synthesis, the synthesis of tumour-associated carbohydrate antigens Globo H and mannobiose which resembles repeat unit of mannan was achieved. To enhance the immunogenicity and multivalent effect, Globo H and mannobiose were covalently attached to degradable polymer backbones. 2D spindle-like lamellar micelle and globular micelle were obtained from glycopolymer through a solvent-exchange method of self-assembly. The glyconanoparticle showed good biocompatibility and degradability. Immunological functions of these glyconanoparticles such as stimulation of BMDC to cause upregulation of inflammatory factors were preliminarily explored.

The effect of temperature on the electrical conductivity (σ) and Seebeck coefficient (S) of n-type vapor grown carbon nanofibers (CNFs) and poly(vinylidene fluoride) (PVDF) melt-mixed with 15 wt% of those CNFs is analyzed. At 40 °C, the CNFs show stable n-type character (S=−4.8 µV·K⁻¹) with an σ of ca.165 S·m⁻¹, while the PVDF/CNF composite film shows an σ of ca. 9 S·m⁻¹ and near-zero S (S=−0.5 µV·K⁻¹). This experimental reduction in S is studied by the density functional tight binding (DFTB) method revealing a contact electron transfer from the CNFs to the PVDF in the interface. Moreover, in the temperature range from 40 °C to 100 °C, the σ(T) of the CNFs and PVDF/CNF film, successfully described by the 3D variable range hopping (VRH) model, is explained as consequence of a thermally activated backscattering mechanism. On the contrary, the S(T) from 40 °C to 100 °C of the PVDF/CNF film, which satisfactorily matches the model proposed for some multi-walled carbon nanotube (MWCNT) doped mats; however, it does not follow the increase in S(T) found for CNFs. All these findings are presented with the aim of discerning the role of these n-type vapor grown carbon nanofibers on the σ and S of their melt-mixed polymer composites.

Owing to the significant increase in air pollutants and the spread of infectious diseases, it seems that the use of face masks will become an essential item in human societies. Therefore, there is a need to conduct more research to develop novel types of respirators utilizing up-to-date science such as nanotechnology. In this study, we fabricated a nanocomposite fibrous filter containing modified graphene oxide (GO) and zinc oxide (ZnO) nanoparticles. This layer was used as an active filter for absorbing and removing air pollutants, such as suspended submicron particles (below 2.5 microns) and CO₂, NO₂, and SO₂ gases. The synthesized nanostructures and fibrous filters were characterized by different analysis (FTIR, XRD, TGA, and FESEM), and the performance of the filters was surveyed by tests such as pressure drop, CO₂, NO₂, SO₂ gas rejection, and particulate removal. The results showed that the stabilization of the modified GO and ZnO nanostructures on the fibrous filter improved the effectiveness of this filter as a mask for removing toxic particles and gases, and the filter containing nanoparticles had the best performance.

Crosslinking natural rubber (NR) and styrene butadiene rubber (SBR) composites with carbon black (CB) have been utilized in the tire tread industry. A sulfur-based lightly crosslinker can potentially enhance the self-healing capabilities of rubber. Moreover, the rubber composites were studied for non-covalent interactions between the benzene rings of SBR and CB. In this research, rubber samples were prepared, and their structure was investigated using Fourier transform infrared (FTIR), and Raman spectroscopy. The red shift in Raman spectroscopy confirmed non-covalent interaction or hydrophobic interaction between SBR and CB in NR/SBR composites exposed to CB due to environmental change. The differential scanning calorimetry (DSC) thermograms showed that NR and SBR were incompatible. Additionally, the mechanical properties of these rubber blends were enhanced as the proportion of NR increased. The maximum self-healing performance reached 40% for the formulation containing 25 phr NR and 75 phr SBR, which also saved energy with low chain end movements. Therefore, these composites could be utilized as a semi-empirical model for studying crosslinked rubber blends, specifically in the rubber tire industry.