Carboxymethyl cellulose (CMC) is a plant-derived polymer known for its excellent anti-adhesive properties, making it suitable for dressings for highly exudative lesions. However, CMC alone is considered an un-spinnable biopolymer due to its complex intermolecular interactions. This study explored the spinnability of CMC through electrospinning by blending it with poly(vinyl alcohol) (PVA) at an 8:2 (PVA/CMC) ratio. Two types of PVA with varying molecular weights and degrees of hydrolysis were used at different concentrations. Solutions were prepared with Milli-Q water at 90 °C for about 2 h, followed by electrospinning under different voltages and flow rates. Scanning electron microscopy (SEM) was used to assess spinning ability, while Fourier-transform infrared spectroscopy (FTIR-ATR) characterized the mats’ chemical composition. Thermal behavior was analyzed using thermogravimetry analysis (TGA) and differential scanning calorimetry (DSC). Results showed that the neat PVA.1 solution produced smaller nanofibers (~217.9 nm), while the PVA.1/CMC blend resulted in a smaller fiber diameter (129.9 nm) but with more defects due to higher surface tension. In contrast, PVA.2 and PVA.2/CMC exhibited larger diameters (448.6 nm and 270.1 nm, respectively) and better thermal and morphological stability, indicating their potential for anti-adhesive chronic wound dressings.

The development of sustainable vitrimers from bio-based sources addresses the need for high-performance recyclable materials. This research describes eugenol-derived epoxy vitrimers cross-linked with adipic acid as a curing agent, focusing on comparative effects of caffeine and zinc acetate as transesterification catalysts at 5 and 10% concentrations versus a non-catalyzed control. Both catalysts acted as curing accelerators, confirmed by FTIR and DSC analyses, revealing polyhydroxyester network formation through associative ester exchange enabling topological reorganization. Zinc acetate at 10% proved most efficient, achieving the lowest apparent activation energy (116.0 kJ/mol), highest crosslinking density (ν_e = 3.42 × 10⁻³ mol/cm³), improved thermal stability with unimodal degradation profile, and substantially reduced topology freezing transition temperature (T_v = 132 °C), confirming enhanced dynamic properties. Caffeine demonstrated catalytic activity, reducing apparent activation energy to 124.4 kJ/mol at 10% and promoting rapid epoxide conversion during initial curing at moderate temperatures. Although its catalytic efficiency is moderate compared to zinc acetate, its bio-based origin and non-toxic nature make it a promising green alternative for sustainable vitrimer applications. Results demonstrate that catalyst selection is crucial for tailoring curing kinetics, network structure, and final vitrimeric properties, providing key guidelines for designing advanced circular materials from bio-based precursors.

Polyaniline is a conductive polymer that attracts the attention of many researchers around the world. The history of this polymer begins in 1862 when Letheby first reported this material. Since then, a myriad of studies has been conducted on this material, and new works continue to investigate the potential of this material. Polyaniline has been improved with the help of Nanotechnology. The use of nanofillers has been seen as a quick and economical way to modify materials, driving innovations based on new physical and chemical properties from the conductive polymer materials and nanoparticles joining. Several works address the use of different nanoparticles, which leads to the practical impossibility of sifting through all this information. Thus, this work proposes to systematically collect data in the literature and investigate which nanoparticles can increase the electrical conductivity of Polyaniline (PAni). The results obtained demonstrate that among the possible nanofillers, graphene and carbon nanotubes have great prominence. Furthermore, the results of the meta-analysis prove that PAni's conductivity increases when this polymer is modified with the aforementioned nanofillers. This work was developed using VOSViewer, a classification and grouping tool, and Jamovi, a new 3rd generation statistical tool used here for the meta-analysis calculation.