Search Results (2,455)

This article evaluates the influence of replicated natural structures, produced by micro-machining, on the wettability of plastic parts made from hydrophilic and hydrophobic polymer materials under various temperature and pressure conditions. Although many studies have focused on biomimetic surface design, the effect of specific processing parameters on the accurate replication of natural topologies and their resulting wettability has been only partially explored. This study addresses this gap by systematically analyzing the effect of melt temperature and packing pressure on the functional replication of micro-machined biomimetic structures. The research describes the design of hierarchical microstructures inspired by biomimetics and their fabrication by micro-milling on molded parts. Test samples were prepared from polypropylene (PP), acrylonitrile butadiene styrene (ABS), and polyamide 6.6 (PA 6.6) under different processing parameters, and wettability was assessed using contact angle (CA) measurements. The results confirmed significant variations in surface wettability depending on polymer type, melt temperature, and packing pressure. For the hydrophilic relief (Rock Moss), contact angles below 90° were obtained for all tested polymers, including PP, which decreased from 98.7° on a flat surface to 82.4° at 220 °C and 500 bar. In PA 6.6, a reduction of up to 12% in contact angle was observed compared to smooth samples at 310 °C and 500 bar. For hydrophobic reliefs (Three-part Hibiscus and Tricolor Pansy), contact angles exceeded 100–110°, with the highest value of 108.3 ± 1.6° for PP at 200 °C and 500 bar. Suitable combinations of melt temperature and packing pressure enabled accurate replication of microstructures while preserving their functional wettability, demonstrating the possibility of tuning surface properties through topological design. Full article

Bumblebees are important pollinating insects in crop pollination. Chemical attractants can effectively improve the flower-visiting efficiency of bumblebees, thereby increasing blueberry yields. To identify volatile compounds that attract bumblebees, we collected volatile compounds from blueberry flowers using headspace extraction. Gas chromatography– mass spectrometry (GC–MS) identified 32 volatile compounds, with Linalool and Styrene being the primary substances that accounted for 25.93% and 14.28%, respectively. The olfactory threshold of bumblebee antennae was assessed using electroantennography (EAG), and the behavioral responses from bumblebees were investigated using a Y-tube olfactometer. Results indicate that among the six classes of volatiles—alcohols, aldehydes, esters, ketones, aromatic compounds, and olefins—alcohols constituted the predominant proportion. Among these, six compounds—benzaldehyde, phenylpropylaldehyde, citral, linalool, α-terpineol, and geraniol—induced significant antennal responses in bumblebees. Our assays showed that geraniol, linalool, and α-terpineol at concentrations of 0.1 μg/μL, 1 μg/μL, and 10 μg/μL elicited attraction, whereas higher concentrations of benzaldehyde, benzenepropanal, and citral had repellent effects. Full article

Single-type viscosity reducers often fail to meet the application requirements of specific oilfields for high-viscosity heavy oils. This study focused on Henan heavy oil, systematically investigating the viscosity reduction performances of oil-soluble viscosity reducers, emulsifiers, and their composite systems. Experimental results indicated that the oil-soluble ethylene-vinyl acetate copolymer (EVA) achieved optimal efficiency at a concentration of 500 ppm, with a viscosity reduction rate of 44.2%. Among the screened emulsifiers, acrylonitrile-ethylene-styrene (AES) exhibited the highest viscosity reduction rate (99.9%), which basically complied with relevant industrial application standards. When EVA and AES were compounded, the resulting composite reducer showed a significantly higher viscosity reduction rate than single EVA, and the stability of the formed oil-in-water (O/W) emulsion was further enhanced. The synergistic mechanism was clarified as follows: EVA first disrupts the aggregation of heavy components (resins and asphaltenes) and modifies wax crystal morphology, creating a favorable microfoundation for subsequent emulsification; AES then promotes the formation of stable O/W emulsions, ultimately achieving a “1 + 1 > 2” synergistic viscosity reduction effect. Furthermore, the potential action mechanism of the EVA-AES composite system was verified using multiple characterization techniques. This study provides a valuable reference for the selection and practical application of heavy oil viscosity reducers in oilfield operations. Full article

In this work, we report the effect of combining styrene-vinyl tetrazole copolymer (StVTz) and ammonium polyphosphate (APP) on the thermal degradation, mechanical properties, flame retardancy, and char formation of low-density polyethylene with ethyl vinyl acetate (LDPE/EVA) composites. The tetrazole heterocycle exhibits high thermal stability (>200 °C), and during its thermal decomposition, it releases non-toxic nitrogen gas. Its degradation generates reactive species capable of cross-linking the polymer chains, thereby promoting the formation of a protective char layer. To evaluate the influence of composition on the intumescent flame-retardant (IFR) properties of LDPE/EVA blends, different concentrations of APP and StVTz additives were incorporated. The composites were prepared in an internal mixer (Brabender Intelli-Torque Plasti-Corder). Test specimens were obtained by compression molding and subsequently cut into appropriate shapes for each analysis. Thermal stability was studied by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Mechanical properties were evaluated by tensile testing. Morphology of cone calorimetry (CC) residues was examined using SEM. Flammability properties, studied using CC, revealed a 70% reduction in the peak heat release rate (pHRR) and a 48% reduction in the total heat release (THR) compared to the neat LDPE/EVA blend. These results indicate that StVTz and APP act synergistically to improve the flame-retardant properties of LDPE/EVA. Full article

This paper presents an adapted methodology for the prediction of fracture loads in additively manufactured (fused filament fabrication) polymers that exhibit non-linear behavior. The approach is based on the Average Strain Energy Density (ASED) criterion, which is typically limited to materials which develop fully linear-elastic behavior. Thus, in those cases where the material has a certain (non-negligible) amount of non-linear behavior, the ASED criterion needs to be corrected. To extend its applicability, this work proposes a thorough calibration of the ASED characteristic parameters: the critical value of the strain energy and the volume of the corresponding control volume. This enables the extrapolation of the linear-elastic formulation to non-linear situations. The approach is validated using acrylonitrile-styrene-acrylate (ASA) and 10 wt.% carbon-fiber reinforced ASA specimens. Single-edge-notched bending (SENB) specimens with three different raster orientations (0/90, 45/−45, and 30/−60) and four U-notch radii (0.0 mm—crack-like, 0.50 mm, 1.0 mm, and 2.0 mm) were printed and tested. The results demonstrate that the proposed calibration of the ASED criterion allows for accurate predictions of failure loads, providing a reliable tool for the structural integrity assessment of 3D-printed components. Full article

The current global economic challenges and resource scarcity necessitate the development of cost-effective and sustainable pavement solutions. This study investigates the performance of asphalt mixtures modified with Low-Density Polyethylene (LDPE) and Styrene–Butadiene–Styrene (SBS) as binder modifiers, and Hydrated Lime (Ca(OH)₂) and Reclaimed Asphalt Pavement (RAP) as aggregate replacements. The research aims to optimize the combination of these materials for enhancing the durability, sustainability, and mechanical properties of asphalt mixtures under various climatic and traffic conditions. Asphalt mixtures were modified with 5% LDPE and 2–6% SBS (by bitumen weight), with 2% Hydrated Lime and 15% RAP added to the mix. The performance of these mixtures was evaluated using the Simple Performance Tester (SPT), focusing on rutting, cracking, and fatigue resistance at varying temperatures and loading frequencies. The NCHRP 09-29 Master Solver was employed to generate master curves for input into the AASHTOWare Mechanistic-Empirical Pavement Design Guide (MEPDG), allowing for an in-depth analysis of the modified mixes under different traffic and climatic conditions. Results indicated that the mix containing 5% LDPE, 2% SBS, 2% Hydrated Lime, and 15% RAP achieved the best performance, reducing rutting, fatigue cracking, and the International Roughness Index (IRI), and improving overall pavement durability. The combination of these modifiers showed enhanced moisture resistance, high-temperature rutting resistance, and improved dynamic modulus. Notably, the study revealed that in warm climates, thicker pavements with this optimal mix exhibited reduced permanent deformation and better fatigue resistance, while in cold climates, the inclusion of 2% SBS further improved the mix’s low-temperature performance. The findings suggest that the incorporation of LDPE, SBS, Hydrated Lime, and RAP offers a sustainable and cost-effective solution for improving the mechanical properties and lifespan of asphalt pavements. Full article

The slow swelling rate of styrene–butadiene–styrene (SBS) in asphalt prolongs the modification process and increases energy consumption. This study proposes a novel method using benzoyl peroxide (BPO) and benzoyl methane (BPA) to accelerate SBS swelling through a radical initiation–capture mechanism. BPO generates free radicals that relax the SBS network, while BPA captures excess radicals, maintaining system stability. Molecular dynamics simulations based on the COMPASS II force field were used to analyse diffusion, radius of gyration, and solubility parameters, revealing that BPO/BPA improved SBS–asphalt compatibility and increased the diffusion coefficient by 76%. Macroscopic viscosity tests confirmed that the swelling time decreased by 40% and equilibrium viscosity increased by 39% compared with the conventional process. The modified asphalt also exhibited enhanced high- and low-temperature performance and ageing resistance. This simple and efficient synergistic technique provides a promising approach for the rapid preparation of SBS-modified asphalt and offers practical potential for industrial production. Full article

In injection molding, draft angle design plays a critical role in ensuring smooth de-molding and maintaining surface quality. With the growing emphasis on aesthetics and the increasing demand for the appearance of plastic products, the need for textured plastic components has continuously risen. The coupling between surface texture replication and dimensional accuracy has become an important indicator of product performance. However, systematic studies on the interaction between different polymer materials and draft angle design remain limited. This study aims to investigate the influence of draft angle variation on the surface texture quality and dimensional stability of injection-molded parts by comparing the differences between crystalline and amorphous thermoplastic materials, as well as between commodity and engineering plastics. Four representative polymers, namely polypropylene (PP), polyoxymethylene (POM), acrylonitrile-butadiene-styrene (ABS), and polycarbonate (PC), were selected to examine the impact of material characteristics on surface texture replication after molding. In addition, product geometries incorporating eight draft angles (0° to 3.5°) were designed. Surface texture replication was analyzed using scanning electron microscopy (SEM) and surface profilometry, while dimensional deformation was measured with a high-precision optical measuring instrument. The results show that draft angle variation has a limited influence on the overall trend of dimensional deformation, but it has a significant effect on the clarity of surface replication. Crystalline polymers exhibited generally higher surface roughness than amorphous polymers, and the distinction between commodity and engineering plastics, particularly those requiring higher processing temperatures, also led to higher roughness (PP > POM; ABS > PC). Dimensional deformation was more pronounced in crystalline polymers (POM > PP > ABS > PC). SEM observations further confirmed that higher roughness corresponded to clearer and more distinguishable texture patterns, whereas lower roughness resulted in blurred or indistinct textures. Full article

Calcium oxalate (CaOx) crystals play a central role in urolithiasis, a pathological crystallization process that remains difficult to prevent. In this study, electrospun polymeric fiber (EPF) meshes of poly(acrylic acid-co-styrene sulfonate) P(AA-co-SS) were fabricated by electrospinning (ES) under controlled positive (+) or negative (−) voltages. The influence of PAA and PSS homopolymers, as well as P(AA-co-SS) copolymers with varying compositions, was evaluated as anionic scaffolds in in vitro CaOx electrocrystallization (EC) experiments. The structural and morphological features of the EPF meshes were characterized by scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Our results demonstrate that specific EPF meshes can effectively guide CaOx crystal growth, promoting the selective stabilization of either calcium oxalate monohydrate (COM) or calcium oxalate dihydrate (COD) phases. These findings highlight the potential of tailored EPF meshes as anionic scaffolds for modulating pathological CaOx crystallization. Full article

Nano- and microplastics (NMPs) in waterways reflect the impact of anthropogenic activities. This study examined spatial variations in the presence and types of NMPs in Galveston Bay (Texas, USA) surface waters and eastern oysters (Crassostrea virginica). The results reveal most MPs carried by surface waters are fibers > films > fragments. Up to 200 MPs were present in individual oysters [=1.88 (± 0.22 SE) per g wet weight]. Oyster health, based on condition index, varied spatially, but was not correlated with MP load. Based on attenuated total reflectance—Fourier-transform infrared spectroscopy, polyamide and polypropylene were frequently found in waters in the upper bay while ethylene propylene and polyethylene terephthalate were more common in the lower parts of the bay. Pyrolysis–gas chromatography–mass spectrometry revealed a very large range in concentrations of NMPs, from 28 to 10,925 µg ∑NMP/g wet weight (or 172 to 67,783 µg ∑NMP/g dry weight) in oysters. This chemical analysis revealed four main types of plastics present in oysters regardless of location: polypropylene, nylon 66, polyethylene and styrene butadiene rubber. Based on this finding, the average daily intake of NMPs estimated for adult humans is 0.85 ± 0.45 mg NMPs/Kg of body weight/day or a yearly intake of 310 ± 164 mg NMPs/Kg of body weight/year. These findings reveal higher body burdens of plastics in oysters are revealed by the chemical analysis relative to the traditional approach; this is not unexpected given the higher sensitivity and selectivity of mass spectrometry and inclusion of the nanoplastic particle range (i.e., <1 mm) in the sample preparation and analysis. Full article

This paper analyzes the combined effects of acetone vapor treatment and 3D printing process parameters (layer thickness and infill rate) on the hardness and surface roughness of acrylonitrile styrene acrylate (ASA) components by using different machine learning and deep learning strategies for the first time in the technical literature. Considering the high-performance materials and aesthetic requirements of manufacturers, post-processing operations are highly critical for 3D-printed samples. ASA is a promising alternative, especially for the structural parts utilized in outdoor conditions like car outer components, electronic part housing, extreme sports equipment, and construction materials. However, it has to sustain hardness features against outer scratching, peeling, and indentations without losing its gloss. Together with the rising competitiveness in the search for a high-performance design with a perfect outer view, the combination of additive manufacturing and machine learning methods was implemented to enhance the hardness and surface quality properties for the first time in the literature. Concordantly, in this study, four different vaporizing durations (15, 45, 90, and 120 min.), three different layer thicknesses (0.1, 0.2, and 0.4 mm), and three different infill rates (25, 50, and 100%) were determined. According to both experimental and multi-way learning approaches, the results show that the support vector regressor (SVR) combined with one-dimensional convolutional neural networks (1D-CNNs) was the best approach for predictions. Gradient boosting (GB) and recurrent neural networks (RNNs) may also be preferable for low-error forecasting. Moreover, although there was a positive relationship between the layer thickness/infill rate and Shore D hardness outcomes, the highest levels were obtained at 45 min of vaporizing. Full article

In this study, the thermal and structural behavior of battery module components produced from polymer-based composites was systematically evaluated using coupled Moldflow 2016 and ANSYS Fluent 2024 simulations. Three thermoplastics—metal-flake-reinforced PC+ABS (Polycarbonate/Acrylonitrile Butadiene Styrene), carbon-fiber-reinforced PEEK (Polyether Ether Ketone), and hybrid mineral-filled PP (Polypropylene)—were investigated as alternatives to conventional aluminum components. Moldflow simulations enabled the assessment of injection molding performance by determining injection pressure, volumetric shrinkage, warpage, residual stress, flow front temperature, and part weight. PEEK exhibited the best dimensional stability, with minimal warpage and shrinkage, while PP showed significant thermomechanical distortion, indicating poor resistance to thermally induced deformation. For thermal management, steady-state simulations were performed on a 1P3S pouch cell battery configuration using the NTGK/DCIR model under a constant heat load of 190 W. Material properties, including temperature-dependent thermal conductivity, density, and specific heat capacity, were defined based on validated databases. The results revealed that temperature distribution and Joule heat generation were strongly influenced by thermal conductivity. While aluminum exhibited the most favorable thermal dissipation, PC+ABS closely matched its electrical performance, with only a 1.3% lower average current magnitude. In contrast, PEEK and PP generated higher cell core temperatures (up to 20 K) due to limited heat conduction, although they had comparable current magnitudes imposed by the energy-conserving model. Overall, the findings indicate that reinforced thermoplastics, particularly PC+ABS, can serve as lightweight and cost-effective alternatives to aluminum in mid-range battery modules, providing similar electrical performance and thermal losses within acceptable limits. Full article

Rubberized concrete is a novel green building material that enhances many features when rubber particles are incorporated into cement mortar, simultaneously yielding economic benefits through the recycling of waste tires. This study applies styrene–butadiene latex (SBL) for toughening treatment. The investigation delves into the mechanism by which SBL improves the interface between rubber and cement, encompassing macroscopic mechanical properties, microscopic structural characteristics, and nano-scale interfacial interactions. Macroscopic mechanical tests reveal a significant increase in flexural strength, shear strength, and compressive strength of the composite concrete upon the introduction of SBL and rubber. Specifically, the compressive strength improved by 8.8%, shear strength by 13.7%, and flexural strength by 18.9% at 28 days. Through electron microscopy observation of corresponding polymer cement concrete sections, observations reveal that SBL reinforces both interfaces and elucidates its bonding impact at the micro-level interface. Molecular dynamics (MD) modeling of SBL/rubber/CSH is employed at the nanoscale to compute and examine the local structure, dynamic behavior, and binding energy of the interface. The findings indicate that SBL mitigates interface impacts, enhances interface hydrogen bonds, van der Waals interactions, $\mathrm{C}\mathrm{a}-\mathrm{H}$ coordination bonds, and stability, consequently improving interfacial adhesion and fortifying the feeble interface bonding between organic polymers (rubber) and inorganic silicates (CSH). Full article

Additive manufacturing is driving a significant change in industry, extending beyond prototyping to the inclusion of printed parts in final designs. Stereolithography (SLA) is a polymerization technique valued for producing highly detailed parts with smooth surface finishes. This study presents a hybrid intelligent framework for modeling and optimizing the SLA 3D printer process’s parameters for Acrylonitrile Butadiene Styrene (ABS) photopolymer parts. The nonlinear relationships between the process’s parameters (Orientation, Lifting Speed, Lifting Distance, Exposure Time) and multiple performance characteristics (ultimate tensile strength, yield strength, modulus of elasticity, Shore D hardness, and surface roughness), which represent complex relationships, were investigated. A Taguchi design of the experiment with an L18 orthogonal array was employed as an efficient experimental design. A novel hybrid fuzzy logic–Particle Swarm Optimization (PSO) algorithm, ARGOS (Adaptive Rule Generation with Optimized Structure), was developed to automatically generate high-accuracy Mamdani-type fuzzy inference systems (FISs) from experimental data. The algorithm starts by customizing Modified Learn From Example (MLFE) to create an initial FIS. Subsequently, the generated FIS is tuned using PSO to develop and enhance predictive accuracy. The ARGOS models provided excellent performances, achieving correlation coefficients (R²) exceeding 0.9999 for all five output responses. Once the FISs were tuned, a multi-objective optimization was carried out based on the weighted sum method. This step helped to identify a well-balanced set of parameters that optimizes the key qualities of the printed parts, ensuring that the results are not just mathematically ideal, but also genuinely helpful for real-world manufacturing. The results showed that the proposed hybrid approach is a robust and highly accurate method for the modeling and multi-objective optimization of the SLA 3D process. Full article