Line heating processes play a significant role in the fabrication of structural steel components, particularly in industries such as shipbuilding, aerospace, and automotive manufacturing, where dimensional accuracy and minimal defects are critical. Traditional methods, such as the finite element method (FEM) simulations, offer high-fidelity predictions but are hindered by prohibitive computational latency and the need for case-specific re-meshing. This study presents a physics-aware, data-driven neural network that delivers fast, high-fidelity temperature predictions across a broad operating envelope. Each spatiotemporal point is mapped to a one-dimensional feature vector. This vector encodes thermophysical properties, boundary influence factors, heatsource variables, and timing variables. All geometric features are expressed in a path-aligned local coordinate frame, and the inputs are appropriately normalized and nondimensionalized. A lightweight multilayer perceptron (MLP) is trained on FEM-generated induction heating data for steel plates with varying thickness and randomized paths. On a hold-out test set, the model achieves MAE = 0.60 °C, RMSE = 1.27 °C, and R2 = 0.995, with a narrow bootstrapped 99.7% error interval (−0.203 to −0.063 °C). Two independent experiments on an integrated heating and mechanical rolling forming (IHMRF) platform show strong agreement with thermocouple measurements and demonstrate generalization to a plate size not seen during training. Inference is approximately five orders of magnitude (~105) faster than FEM, enabling near-real-time full-field reconstructions or targeted spatiotemporal queries. The approach supports rapid parameter optimization and advances intelligent line heating operations.

Double gloving of disposable gloves occurs in healthcare when extra protection is required against carcinogens, sensitizers, pathogens and sharps. Triple gloving is much rarer. The resistances of single, double and triple layers of disposable nitrile glove material against 2-butoxyethanol (2-BE) were compared with the resistance of a single layer of Microflex 93-260 (Microflex). Three 2.54 cm ASTM F739 permeation cells with closed-loop water collection without recirculation in a moving tray water bath at 35.0 ± 0.5 °C facilitated the permeation relative to a blank cell. Capillary gas chromatography/mass spectrometry allowed the determination of the standardized breakthrough time (SBT), steady state permeation rate (SSPR) and cumulated permeated mass/area (CPM/A) by 30 min. Two nitrile layers (267 ± 14 µm) were about the same thickness as the Microflex layer (249 ± 6 µm). Statistical analysis showed equivalence at p ≤ 0.05 of the multiple layers and the Microflex layer relative to average SBT and CPM/A by 30 min, all such comparisons with the single nitrile layer also being statistically different. The triple layer had an average SSPR or post-breakthrough permeation rate 8 times lower than its single layer, while that for the Microflex layer was 1.5 times lower. Thus, the Microflex layer in terms of CPM/A by 30 min at 210 ± 40 µg/cm2 appeared closer to two nitrile layers (520 ± 560 µg/cm2) than three (93 ± 93 µg/cm2).

This study presents a novel structural framing solution designed to improve seismic energy dissipation and limit displacements, aiming to serve as an effective alternative to traditional precast systems employing pendulum-based isolation. While pendulum mechanisms mitigate seismic forces by decoupling the superstructure from ground motion, they are typically characterized by high implementation costs, mechanical complexity, and post-event maintenance challenges. In contrast, the proposed approach integrates seismic performance enhancements within the structural frame itself, removing the dependency on external isolation components. The system leverages a combination of pinned and semi-rigid beam-to-column joints that are tailored for use within dry precast construction technologies. These connection types not only support rapid and labor-efficient assembly but also, when properly detailed, offer robust hysteretic behavior and deformation control under dynamic loading. The research includes both experimental testing and numerical simulations focused on the cyclic response of these connections, enabling a comprehensive understanding of their role in dissipating energy and delaying damage progression. Recognizing the industry’s frequent emphasis on construction speed and upfront cost-efficiency, often at the cost of long-term reparability, this work introduces an alternative framework that emphasizes resilience without compromising construction practicality. The resulting system demonstrates improved post-earthquake functionality and reduced downtime, making it a promising and economically viable option for seismic applications in precast construction. This advancement supports current trends toward performance-based design and enhances the structural reliability of dry-assembled systems in seismic regions.

Prepreg tack is an important process quality parameter for prepregs during laying. Aiming at the current lack of standardized testing for prepreg tack, this paper established a quantitative testing method for prepreg tack—a compression-to-tension method—and proposed a parameter of Compression Tack Index as a quantitative evaluation index for prepreg tack. The prepreg/prepreg tack and prepreg/metal tack of carbon fiber reinforced epoxy prepregs were evaluated and the applicability of this compression-to-tension method was verified, comparing it with the qualitative testing method by vertical metal plates. The results show that the compression-to-tension method is suitable for quantitative testing of the tack for unidirectional prepregs and fabric prepregs, with good repeatability and stability of test results, and is not affected by personnel changes. Considering that tack characterization based only on the separation process cannot accurately evaluate the tack of different materials, Compression Tack Index is an accurate parameter that characterizes the prepreg tack because it can reflect the process of tack formation and tack separation. Compared with the vertical metal plate method, the discrimination of the test results by the compression-to-tension method is significant. The tack of the slitting prepreg without polyethylene film coating is lower than that of the mother prepreg (one-meter-width prepreg) with polyethylene film.

The aim of this study was the valorization of brewer’s yeast waste as a low-cost, biodegradable filler for polylactide (PLA) and the evaluation of the effect of yeast biomass on the processing, mechanical, thermal properties, and biodegradation of the resulting composites. The materials were prepared using extrusion and injection molding techniques, with the addition of brewer’s yeast (Saccharomyces cerevisiae) in amounts ranging from 5 to 30 wt%. Fourier-transform infrared spectroscopy (FTIR) analysis revealed the absence of strong interfacial chemical interactions, indicating physical dispersion of the filler within the matrix. The addition of biomass significantly modified the properties of PLA. The results demonstrated increased melt flowability (melt flow rate increased from 18.8 to 39.8 g/10 min) and stiffness (a 13% increase in Young’s modulus for 20 wt%), accompanied by a considerable reduction in tensile strength (from 63.2 to 20.2 MPa) and impact strength (from 22.8 to 6.2 kJ/m2). Thermal analyses showed a systematic decrease in the glass transition temperature by approximately 5 °C and a dual effect of the filler on crystallization behavior. At low concentrations, the waste acted as a nucleating agent, while at higher loadings it limited crystallinity, leading to an amorphous structure. Thermal stability decreased with increasing biomass content (from 329.3 °C to 266.8 °C). Industrial composting tests indicated that at a 30 wt% yeast content, the mass loss (27.5%) was higher than that of neat PLA (25.5%), suggesting accelerated biodegradation. Despite the deterioration of mechanical performance, the developed biocomposites represent a promising material for single-use applications, combining low cost, easy processability, and an environmentally favorable profile consistent with the principles of the circular economy.

This study presents evaluation of biochar derived from silkworm cocoons for the adsorption of organic and inorganic contaminants from rainwater. The material was characterised using BET surface area analysis, scanning electron microscopy (SEM), and the point of zero charge (pHPZC). The prepared biochar exhibited a well-developed surface area and demonstrated adsorption capacity toward both heavy metals and benzotriazole. The model rainwater was prepared by spiking real rainwater samples with Cu(II), Ni(II), Zn(II) ions, and benzotriazole (BT). Adsorption experiments were carried out under laboratory conditions to evaluate the effects of contact time, pH, and sorbent dosage. The experimental data were fitted to pseudo-first-order and pseudo-second-order kinetic models, as well as Langmuir/and Freundlich isotherms. The results showed that the adsorption of Cu(II) followed the Langmuir/Freundlich model, while the adsorption of Ni(II) benzotriazole was more consistent with the Freundlich model. Adsorption kinetics were best described by the pseudo-second-order model. The highest removal efficiencies were observed for Cu(II) (96%) and Ni(II) (88.8%), while Zn(II) removal was limited. Benzotriazole was also effectively adsorbed (97%), rapid adsorption occurred mainly within the first minute. Overall, the study highlights the selective adsorption behaviour of silkworm cocoon biochar and provides a comparative insight into the removal of organic and inorganic pollutants using a waste-derived adsorbent with surface properties comparable to those of activated carbon.

Laser powder bed fusion (L-PBF) is an additive manufacturing technique that enables the fabrication of complex geometries through a layer-by-layer approach, overcoming limitations of conventional manufacturing. In this study, multiaxial low-cycle fatigue (MLCF) tests were conducted on L-PBF Ti-6Al-4V (Ti64) specimens built in four different orientations, selected based on critical plane orientations identified from rolled titanium. Under proportional strain-controlled loading, the cyclic softening behavior, mean stress response, and fracture mechanisms of the material were systematically investigated. The results show that L-PBF Ti64 exhibits a three-stage softening characteristic (continuous softening, stable, and rapid softening). Fatigue cracks primarily initiate from inner-surface lack-of-fusion defects. Crack propagation shows cleavage and quasi-cleavage characteristics with tearing ridges, river patterns, and multi-directional striations. Proposed KBMP life prediction model, incorporating λ and building direction parameters, was developed. The KBMP-λ model demonstrates optimal accuracy, providing a reliable tool for the design of L-PBF titanium components subjected to complex multiaxial fatigue loading with relative errors within 20%.

We have investigated the evolution of CDW states and structural phases in a Cu-deficient Cu1-δTe (δ = 0.016) by employing high-pressure experiments and first-principles calculations. Raman scattering results reveal that the vulcanite structure at ambient pressure starts to change into the Cu-deficient rickardite (r-CuTe) structure from 6.7 GPa, which then becomes fully stabilized above 8.3 GPa. Resistivity data show that TCDW1 (≈333 K) is systematically suppressed under high pressure, reaching zero at 5.9 GPa. In the pressure range of 5.2–8.2 GPa, a sharp resistivity drop due to superconductivity occurs at the onset temperature TC = ~2.0–3.2 K. The maximum TC = 3.2 K achieved at 5.6 GPa is clearly higher than that of CuTe (2.3 K), suggesting the importance of charge fluctuation in the vicinity of CDW suppression. At 7.5 GPa, another resistivity anomaly appears due to the emergence of a second CDW (CDW2) ordering at TCDW2 = ~176 K, which exhibits a gradual increase to ~203 K with pressure increase up to 11.3 GPa. First-principles calculations on the Cu-deficient Cu11Te12 with the r-CuTe structure show that including on-site Coulomb repulsion is essential for incurring an unstable phonon mode relevant for stabilizing the CDW2 order. These results point out the important role of charge fluctuation in optimizing the pressure-induced superconductivity and that of Coulomb interaction in creating the competing CDW order in the Cu-deficient CuTe system.

Adhesively bonded joints between galvanized steel and carbon fiber-reinforced polymers (CFRPs) are critical in modern lightweight structures, but their performance is often limited by failure at the zinc–adhesive interface. This study presents a parametric analysis to investigate the influence of key geometric parameters on interfacial cracking in a single-lap joint (SLJ) configuration, employing a simplified analytical methodology based on Interface Fracture Mechanics (IFM). The model combines the Goland–Reissner approach for estimating crack-tip loads with highly simplified, constant shape functions to calculate the energy release rate (Gint) and phase angle (ψ). To provide a practical reference, experimental data from shear tests on S350 GD galvanized steel bonded to CFRP were used to estimate the range of interfacial fracture toughness for this material system. The parametric results demonstrate that, for a constant load, increasing the overlap length reduces the crack driving force (Gint), while increasing the adhesive thickness raises it. Crucially, the model indicates that a thicker adhesive layer shifts the fracture mode from shear- to opening-dominated, a trend consistent with the established mechanics of SLJs, where increased joint rotation amplifies peel stresses. The study concludes that while the use of constant shape functions limits the model’s quantitative accuracy, this simplified analytical framework effectively captures the qualitative influence of key geometric parameters on the joint’s fracture behavior. It serves as a valuable and resource-efficient tool for preliminary design explorations and for interpreting experimentally observed failure trends in galvanized steel–CFRP joints.

Hypoeutectic Al-Si-Mg alloys are among the most widely used casting materials in the automotive and aerospace industries due to their low density, high strength-to-weight ratio, corrosion resistance, and good castability. A critical challenge during solidification is shrinkage porosity, which arises from insufficient feeding and significantly reduces casting reliability. While the role of silicon in altering the phase diagram of Al-Si-Mg alloys is well-understood, its direct impact on feeding behavior has not been previously quantified in detail. In this study, the influence of silicon content (5–9 wt.%) on feeding ability was systematically investigated using thermal analysis (TA). By analyzing cooling curves, first derivatives, and ΔT curves, key solidification temperatures, including the liquidus, dendrite coherency, rigidity, and solidus, were precisely identified. For the first time, these data were used to quantitatively define all five feeding regions (liquid, mass, interdendritic, burst, and solid feeding) as a function of silicon content. The results demonstrate that increasing the Si content decreases the liquidus and dendrite coherency temperatures, raises the rigidity and solidus temperatures, and shortens the overall feeding ranges, particularly the interdendritic region (~32 °C reduction). This novel TA-based quantification of feeding regions provides insights that extend beyond classical phase diagram interpretation. The findings confirm that higher Si contents improve feeding ability by narrowing the freezing range and reducing the risk of porosity, while also providing a unique dataset for validating casting simulation software. The results also confirm that increasing the silicon content enhances feeding ability and improves castability by narrowing the freezing range and promoting more uniform solidification in Al-Si-Mg alloys. The study therefore bridges fundamental solidification science with industrial practice, supporting improved alloy design and defect control in Al-Si-Mg castings.