Search Results (6)

The development of slippery surfaces has been widely investigated due to their excellent icephobic properties. A distinct kind of an ice-repellent structure known as a slippery liquid-infused porous surface (SLIPS) has recently drawn attention due to its simplicity and efficacy as a passive ice-protection method. These surfaces are well known for exhibiting very low ice adhesion values (τice < 20 kPa). In this study, pure Polytetrafluoroethylene (PTFE) fibers were fabricated using the electrospinning process to produce superhydrophobic (SHS) porous coatings on samples of the aeronautical alloy AA6061-T6. Due to the high fluorine–carbon bond strength, PTFE shows high resistance and chemical inertness to almost all corrosive reagents as well as extreme hydrophobicity and high thermal stability. However, these unique properties make PTFE difficult to process. For this reason, to develop PTFE fibers, the electrospinning technique has been used by an PTFE nanoparticles (nP PTFE) dispersion with addition of a very small amount of polyethylene oxide (PEO) followed with a sintering process (380 °C for 10 min) to melt the nP PTFE together and form uniform fibers. Once the porous matrix of PTFE fibers is attached, lubricating oil is added into the micro/nanoscale structure in the SHS in place of air to create a SLIPS. The experimental results show a high-water contact angle (WCA) ≈ 150° and low roll-off angle (αroll-off) ≈ 22° for SHS porous coating and a decrease in the WCA ≈ 100° and a very low αroll-off ≈ 15° for SLIPS coating. On one hand, ice adhesion centrifuge tests were conducted for two types of icing conditions (glaze and rime) accreted in an ice wind tunnel (IWT), as well as static ice at different ice adhesion centrifuge test facilities in order to compare the results for SHS, SLIPs and reference materials. This is considered a preliminary step in standardization efforts where similar performance are obtained. On the other hand, the ice adhesion results show 65 kPa in the case of SHS and 4.2 kPa of SLIPS for static ice and <10 kPa for rime and glace ice. These results imply a significant improvement in this type of coatings due to the combined effect of fibers PTFE and silicon oil lubricant. Full article

In recent years, the field of construction engineering has experienced a significant paradigm shift, embracing the integration of machine learning (ML) methodologies, with a particular emphasis on forecasting the characteristics of steel-fiber-reinforced concrete (SFRC). Despite the theoretical sophistication of existing models, persistent challenges remain—their opacity, lack of transparency, and real-world relevance for practitioners. To address this gap and advance our current understanding, this study employs the extra gradient (XG) boosting algorithm, crafting a comprehensive approach. Grounded in a meticulously curated database drawn from 43 seminal publications, encompassing 420 distinct records, this research focuses predominantly on three primary fiber types: crimped, hooked, and mil-cut. Complemented by hands-on experimentation involving 20 diverse SFRC mixtures, this empirical campaign is further illuminated through the strategic use of partial dependence plots (PDPs), revealing intricate relationships between input parameters and consequent compressive strength. A pivotal revelation of this research lies in the identification of optimal SFRC formulations, offering tangible insights for real-world applications. The developed ML model stands out not only for its sophistication but also its tangible accuracy, evidenced by exemplary performance against independent datasets, boasting a commendable mean target-prediction ratio of 99%. To bridge the theory–practice gap, we introduce a user-friendly digital interface, thoroughly designed to guide professionals in optimizing and accurately predicting the compressive strength of SFRC. This research thus contributes to the construction and civil engineering sectors by enhancing predictive capabilities and refining mix designs, fostering innovation, and addressing the evolving needs of the industry. Full article

A large portion of the produced Polypropylene (PP) is used in the form of fibers. In this industrially oriented study, the development of composite PP drawn fibers was investigated. Two types of fillers were used (ultra-fine talc and single-wall carbon nanotubes). Optimization of the thermal and mechanical properties of the produced composite drawn fibers was performed, based on the Box-Behnken design of experiments method (surface response analysis). The effect of additives, other than the filler, but typical in industrial applications, such as an antioxidant and a common compatibilizer, was investigated. The drawing ratio, the filler, and the compatibilizer or the antioxidant content were selected as design variables, whereas the tensile strength and the onset decomposition temperature were set as response variables. Fibers with very high tensile strength (up to 806 MPa) were obtained. The results revealed that the maximization of both the tensile strength and the thermal stability was not feasible for composites with talc due to multiple interactions among the used additives (antioxidant, compatibilizer, and filler). Additionally, it was found that the addition of talc in the studied particle size improved the mechanical strength of fibers only if low drawing ratios were used. On the other hand, the optimization targeting maximization of both tensile strength and thermal stability was feasible in the case of SWCNT composite fibers. It was found that the addition of carbon nanotubes improved the tensile strength; however, such improvement was rather small compared with the tremendous increase of tensile strength due to drawing. Full article

Drawing is a well-established method to improve the mechanical properties of wet-spun fibers, as it orients the polymer chains, increases the chain density, and homogenizes the microstructure. This work aims to investigate how drawing variables, such as the draw ratio, drawing speed, and temperature affect the elastic modulus (E) and the strain at break (ε_B) of biobased wet-spun fibers constituted by neat polylactic acid (PLA) and a PLA/poly(dodecamethylene 2,5-furandicarboxylate) (PDoF) (80/20 wt/wt) blend. Drawing experiments were conducted with a design of experiment (DOE) approach following a 2⁴ full factorial design. The results of the quasi-static tensile tests on the drawn fibers, analyzed by the analysis of variance (ANOVA) and modeled through the response surface methodology (RSM), highlight that the presence of PDoF significantly lowers E, which instead is maximized if the temperature and draw ratio are both low. On the other hand, ε_B is enhanced when the drawing is performed at a high temperature. Finally, a genetic algorithm was implemented to find the optimal combination of drawing parameters that maximize both E and ε_B. The resulting Pareto curve highlights that the temperature influences the mechanical results only for neat PLA fibers, as the stiffness increases by drawing at lower temperatures, while optimal Pareto points for PLA/PDoF fibers are mainly determined by the draw ratio and the draw rate. Full article

Spider silk has been a hotspot in the study of biomaterials for more than two decades due to its outstanding mechanical properties. Given that spiders cannot be farmed, and their low silk productivity, many attempts have been made to produce recombinant spidroins as an alternative. Herein, we present novel chimeric recombinant spidroins composed of 1 to 4 repetitive units of aciniform spidroin (AcSp) flanked by the nonrepetitive N- and C-terminal domains of the minor ampullate spidroin (MiSp), all from Araneus ventricosus. The spidroins were expressed in the form of inclusion body in E. coli with high yield. Remarkably, the aqueous solubility of the four spidroins ranged from 13.4% to over 50% (m/v). The four spidroins could self-assemble into silk-like fibers by hand-drawing. The secondary structures of these proteins, determined by circular dichroism spectrum (CD) and Fourier transform infrared spectrum (FTIR), indicated a prominent transformation from α-helix to β-sheet after fiber formation. The mechanical properties of the hand-drawn fibers showed a positive correlation with the spidroin molecular weight. In summary, this study describes promising biomaterials for further study and wide application. Full article

In liquid composite molding processes, such as resin transfer molding (RTM) and vacuum assisted resin transfer molding (VARTM), the resin is drawn through fiber preforms in a closed mold by an induced pressure gradient. Unlike the RTM, where a rigid mold is employed, in VARTM, a flexible bag is commonly used as the upper-half mold. In this case, fabric deformation can take place during the impregnation process as the resin pressure inside the preform changes, resulting in continuous variations of reinforcement thickness, porosity, and permeability. The proper approach to simulate the resin flow, therefore, requires coupling deformation and pressure field making the process modeling more complex and computationally demanding. The present work proposes an efficient methodology to add the effects of the preform compaction on the resin flow when a deformable porous media is considered. The developed methodology was also applied in the case of Seeman’s Composite Resin Infusion Molding Process (SCRIMP). Numerical outcomes highlighted that preform compaction significantly affects the resin flow and the filling time. In particular, the more compliant the preform, the more time is required to complete the impregnation. On the other hand, in the case of SCRIMP, the results pointed out that the resin flow is mainly ruled by the high permeability network. Full article