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This investigation of hydroxyl and polysiloxane absorption peaks in elastic polymer composites reveals significant spectral shifts within the fingerprint region of FTIR spectra. Using poly(vinyl butyral) (PVB) as the base polymer and poly(vinyl acetate) (PVAc) and poly(vinyl alcohol) (PVA) as reference materials, solvent effects on polymer–solvent interactions were systematically analyzed. Among the tested alcohol solvents, PEG 400 induced the most pronounced spectral changes, with the C=O stretching band shifting from 1740 to 1732 cm−1 and the O–H band significantly broadening and downshifting to around 3300 cm−1, reflecting strong hydrogen-bonding interactions. Wavelet-based noise reduction effectively enhanced the signal-to-noise ratio, reducing the baseline standard deviation by over 90%. This study introduces a novel noise-enhanced FTIR recognition model that integrates baseline noise metrics to improve detection sensitivity. The model successfully uncovers subtle structural variations in polymer–solvent systems that are typically masked by conventional FTIR techniques, advancing materials analysis and providing a robust framework for future FTIR-based diagnostics and material characterization.

This study presents a comprehensive investigation into the large-scale production of synthetic and hybrid (nanoparticle-loaded) nanofibers using needleless electrospinning. A diverse range of polymers, including polyamide 6 (PA6) and its other polymer combinations, recycled PA6, polyamide 11 (PA11), polyamide 12 (PA12), polyvinyl butyral (PVB), polycaprolactone (PCL), polyacrylonitrile (PAN), polyvinylidene fluoride (PVDF), polyurethane (PU), polyvinyl alcohol (PVA), and cellulose acetate (CA), were utilized to fabricate nanofibers with tailored properties such as polymer solution concentrations and various solvent systems. Furthermore, an extensive variety of nano- and micro-particles, including TiO2, ZnO, MgO, CuO, Ag, graphene oxide, CeO2, Er2O3, WO3, MnO2, and hyperbranched polymers, were incorporated into the polymeric systems to engineer multifunctional nanofibers with enhanced structural characteristics. The study examines the impact of polymer–nano/micro-particle interactions, fiber morphology, and the feasibility of large-scale production via needleless electrospinning. The resulting nanofibers exhibited diameters starting from 80 nm, depending on the polymer and processing conditions. The incorporation of TiO2, CeO2, WO3, Ag, and ZnO nanoparticles into 15% PA6 solutions yielded well-dispersed hybrid nanofibers. By providing insights into polymer selection, nano- and micro-particle integration, and large-scale production techniques, this work establishes a versatile platform for scalable hybrid nanofiber fabrication, paving the way for innovative applications in nanotechnology and materials science.

A superhydrophobic layered nanocarrier, SH-ZIF-NL, was successfully synthesized, loaded with 2-mercaptobenzimidazole (2-MBI), and subsequently incorporated into polyvinyl butyral (PVB) resin to develop an advanced anti-corrosion composite coating tailored for magnesium alloy applications. The structural characteristics of the SH-ZIF-NL and its influence on the anti-corrosion performance of the PVB-based composite coatings were systematically investigated. The results indicate that the layered nanocarriers, with their stacked architecture, provide numerous active sites, which significantly enhance the loading capacity for the corrosion inhibitor. Furthermore, the hydrophobic functional groups on the surface modulate the release kinetics of the corrosion inhibitor, thereby prolonging its protective efficacy over an extended period. The 2-MBI@SH-ZIF-NL/PVB composite coating displayed remarkable advantages in enhancing the anti-corrosion performance of magnesium alloys. After immersion in a 3.5 wt.% NaCl solution for two months, the low-frequency impedance modulus of this composite coating remained stable without significant reduction. Even when the coating was damaged, it continued to provide short-term corrosion protection for the underlying magnesium alloy substrate. The exceptional anti-corrosion performance of this coating can be attributed to the superior physical barrier properties of the superhydrophobic layered nanocarrier, the intelligent and controlled stepwise release of the corrosion inhibitor, as well as the improved adhesion between the coating and the substrate.

Machine learning algorithms for classification are employed in this study to generate different models that can predict the surface roughness of parts manufactured from polyvinyl butyral by means of Fused Deposition Modeling (FDM). Five input variables are defined (layer height, print speed, number of perimeters, wall angle, and extruder temperature), and 16 parts are 3D printed, each with three different surfaces (48 surfaces in total). The print values used to print each part were defined by a fractionated orthogonal experimental design. Using a perthometer, the average value of surface roughness, Ra , on each surface was obtained. From these experimental values, 40 models were trained and validated. The model with the best prediction results was the one generated by bagging and Multilayer Perceptron (BMLP), with a Kappa statistic of 0.9143. The input variables with the highest influence on the surface finish are the wall angle and the layer height.

For effective application of electrospinning and electrospun fibrous meshes in wound dressing, we have in situ electrospun poly(vinyl pyrrolidone)/iodine (PVP/I), PVP/poly(vinyl pyrrolidone)-iodine (PVPI) complex, and poly(vinyl butyral) (PVB)/PVPI solutions into fibrous membranes by a handheld electrospinning apparatus. The morphologies of the electrospun fibers were examined by SEM, and the hydrophobicity, gas permeability, and antibacterial properties of the as-spun meshes were also investigated. The flexibility and feasibility of in situ electrospinning PVP/I, PVP/PVPI, and PVB/PVPI membranes, as well as the excellent gas permeabilities and antibacterial properties of the as-spun meshes, promised their potential applications in wound healing.

Atmospheric window (8-13 μm) spectrally selective radiative-cooling textiles can minimize heat gain from the surroundings, especially under the urban heat-island conditions. However, perspiration can substantially degrade this selectivity because sweat has broadband emissive properties. Here, we design an integrated spectrally selective radiative cooling textile with directional sweating capability. Embedded conical microstructures drive rapid sweat transport and shedding, maintaining a dry radiative surface and thereby preserving spectral selectivity. By incorporating 20 wt% silicon nitride particles into polyvinyl butyral fibers, the textile achieves 83.8% emissivity within atmospheric window, 43.3% emissivity within non-atmospheric window (2.5-8 µm and 13-20 µm), and 92.8% solar reflectivity. After sweating, it still possesses 84.4% atmospheric-window emissivity and 45.4% non-atmospheric window emissivity, demonstrating robust spectral preserving capabilities. Outdoor experiments demonstrate that the spectrally selective textile is 2.8 °C and 7.3 °C cooler than broadband textile and cotton, respectively, highlighting its potential for personal radiative cooling in hot urban environments. Integrating optical properties and conical structural design constructs a radiative cooling textile with self-sustaining spectral selectivity, enabling efficient directional sweat transport that mitigates sweat’s impact on its spectral performance.

Recent explosions and impact events have highlighted the exposure of civil structures, prompting the need for resilient new constructions and retrofitting of existing ones. Laminated glass panels, particularly in glazed facades, are increasingly used to enhance blast resistance. However, the understanding of glass fragments and their interaction with the interlayer is still incomplete. This paper investigates experimentally the quasi-static and dynamic responses of cured and uncured polymers for seven different materials—two different products of polyvinyl butyral (PVB), two ethylene vinyl acetate products (EVA), one product of thermoplastic polyurethane (TPU), and two SentryGlas products (SG)—that were tested between 21 and 32 °C (69.8 and 89.6 °F), which is the recommended room temperature. In these experiments, the responses of PVB, EVA, TPU, and SG were evaluated under a quasi-static strain rate of 0.033 s−1 and compared to the results under a relatively higher strain rate of 2 s−1. Moreover, the high strain rate loading of the materials was accomplished using a drop-weight testing appliance to evaluate the engineering stress–strain response under strain rates between 20 and 50 s−1. The results demonstrated that with strain rates of 20 s−1, PVB behaved like a material with viscoelastic characteristics, but at 45 s−1 strain rates, PVB became a non-elastic material. SG, on the other hand, offered both a high stiffness and a high level of transparency, making it a very good alternative to PVB in structural applications. In contrast, after the maximum stress point, the response to the failure of the seven materials differed significantly. The tests provided ample information for evaluating alternative approaches to modeling these different materials in blast events.

Manufacturing a flexible, light, large-area, and high-efficiency electromagnetic shielding materials in a straightforward and cost-effective manner presently remains a significant challenge. In this work, we propose a conductive network design and verify its electromagnetic interference (EMI) shielding effectiveness (SE) by simulation. Using the structure and parameters obtained by simulation, we prepare a flexible EMI shielding material using silver nanowires (AgNWs)/polyvinyl butyral (PVB) ethanol solution and textile substructure via a facile immersing method. In the frequency range of 5–18 GHz, the AgNWs/PVB textile with 1.4 mm thickness achieves an EMI SE of 59 dB, which exceeds the requirements for commercial applications. Due to the low density of 56 mg/cm 3 , specific shielding effectiveness (SSE) of this material reaches 1053 dB m 3 /g. It is found that the AgNWs/PVB textile is more resistant to washing with water and oxidation than AgNWs textile without a PVB protector. As a result, the conductivity of AgNWs/PVB textile exhibits no change after washing with water and varies slightly after being kept in hot air. We find that a signal monitor is unable to detect a signal emitted by a mobile phone from a jacket lined with AgNWs/PVB textile. AgNWs/PVB textile with these properties can be mass-produced as high-efficiency EMI shielding material for commercial applications.

Aluminum nitride (AlN) nanofibers were formed by heating polyvinyl alcohol (PVA)/boehmite precursor nanofibers at various temperatures in nitrogen gas flow. We designed AlN nanofiber as an effective thermal conductive filler to create long linear heat-transfer pathways in the resin. Aligned AlN nanofiber mats were fabricated using electrospinning of PVA/boehmite composite aqueous solution and were impregnated with polyvinyl butyral (PVB) solutions. The obtained sheets containing the aligned AlN nanofiber 47, 52, and 54 vol% had excellent thermal conductivity, 22, 21, and 19 W/(m·K), for aligned nanofibers direction in the sheet. The PVB/AlN nanofibers composite sheet also showed good electrical insulating properties below 1.0 × 10 12 Ω/cm 2 . Graphical Abstract

In additive manufacturing (AM), the removal of support structures is a critical post-processing step that significantly impacts the quality and functionality of the final product. This study investigates high-efficiency techniques for removing support structures in fused deposition modeling printed parts, focusing on polyvinyl butyral as a support material. Four distinct support geometries were evaluated using three removal methods: manual removal, ethanol-based solvent treatment, and a hybrid approach combining mechanical and chemical techniques. The hybrid method demonstrated the highest efficiency, reducing removal time by up to 70.3% and increasing the removal rate by 4.07 times compared to manual removal. These findings highlight the potential of hybrid methods for optimizing support material removal in AM, particularly for complex geometries. The study provides valuable insights for improving post-processing efficiency and product quality in AM applications.