Search Results (5,774)

This study aims to enhance the performance of an innovative steel slag–ceramsite foam concrete (SSCFC) to advance sustainable green building materials. An eco-friendly composite construction material was developed by integrating industrial by-product steel slag (SS) with lightweight ceramsite. Employing a three-factor, three-level orthogonal experimental design at a fixed density of 800 kg/m³, 12 mix proportions (including a control group) were investigated with the variables of water-to-cement (W/C) ratio, steel slag replacement ratio, and ceramsite replacement ratio. The governing mechanisms of the W/C ratio, steel slag replacement level, and ceramsite replacement proportion on the SSCFC’s fluidity and compressive strength (CS) were elucidated. The synergistic application of range analysis and analysis of variance (ANOVA) quantified the significance of factors on target properties, and partial least squares regression (PLSR)-based prediction models were established. The test results indicated the following significance hierarchy: steel slag replacement > W/C ratio > ceramsite replacement for fluidity. In contrast, W/C ratio > ceramsite replacement > steel slag replacement governed the compressive strength. Verification showed R² values exceeding 65% for both fluidity and CS predictions versus experimental data, confirming model reliability. Multi-criteria optimization yielded optimal compressive performance and suitable fluidity at a W/C ratio of 0.4, 10% steel slag replacement, and 25% ceramsite replacement. Full article

The textile industry’s reliance on synthetic dyes contributes significantly to pollution, highlighting the need for sustainable alternatives like biopigments. This study investigates the production and application of the biopigment prodigiosin, which was produced by Pseudomonas putida with a yield of 1.85 g/L. Prodigiosin was prepared under acidic, neutral, and alkaline conditions, resulting in varying protonation states that influenced its affinity for cotton and polyester fibers. Three surfactants (anionic, cationic, non-ionic) were tested, with non-ionic Tween 80 yielding a promising color strength (above 4) and fastness results with neutral prodigiosin at 1.3 g/L. Cotton and polyester demonstrated good washing (color difference up to 14 for cotton, 5 for polyester) and light fastness (up to 15 for cotton, 16 for polyester). Cellulose acetate, used in the conventional printing process as a thickener, produced superior color properties compared to commercial thickeners. Neutral prodigiosin achieved higher color strength, and cotton fabrics displayed halochromic properties, distinguishing them from polyester, which showed excellent fastness. Prodigiosin-printed samples also exhibited strong antimicrobial activity against Pseudomonas aeruginosa and retained halochromic properties over 10 pH cycles. These findings suggest prodigiosin as a sustainable dye alternative and pH sensor, with potential applications in biomedical materials, such as antimicrobial and pH-responsive wound dressings. Full article

Tea cultivation faces significant threats from red spider mite (RSM: Oligonychus coffeae) infestations, which reduce yields and economic viability in major tea-producing regions. Current automated detection methods rely on supervised deep learning models requiring extensive labeled data, limiting scalability for smallholder farmers. This article proposes AIM-Net (AI-based Infestation Mapping Network) by evaluating SwAV (Swapping Assignments between Views), a self-supervised learning framework, for classifying RSM infestation severity (Mild, Moderate, Severe) using a geo-referenced, field-acquired dataset of RSM infested tea-leaves, Cam-RSM. The methodology combines SwAV pre-training on unlabeled data with fine-tuning on labeled subsets, employing multi-crop augmentation and online clustering to learn discriminative features without full supervision. Comparative analysis against a fully supervised ResNet-50 baseline utilized 5-fold cross-validation, assessing accuracy, F1-scores, and computational efficiency. Results demonstrate SwAV’s superiority, achieving 98.7% overall accuracy (vs. 92.1% for ResNet-50) and macro-average F1-scores of 98.3% across classes, with a 62% reduction in labeled data requirements. The model showed particular strength in Mild_RSM-class detection (F1-score: 98.5%) and computational efficiency, enabling deployment on edge devices. Statistical validation confirmed significant improvements (p < 0.001) over baseline approaches. These findings establish self-supervised learning as a transformative tool for precision pest management, offering resource-efficient solutions for early infestation detection while maintaining high accuracy. Full article

Aronia melanocarpa (black chokeberry) is a medicinally valuable small fruit species, yet its commercial propagation remains limited by low rooting and genotype-specific responses. This study developed an efficient, callus-free micropropagation and rooting protocol using a Shrub Plant Medium (SPM) supplemented with 5 mg/L BAP in large 660 mL jars, which yielded up to 27 shoots per explant. Optimal rooting (100%) was achieved with 0.5 mg/L NAA + 0.25 mg/L IBA in half-strength SPM. In the second phase, supervised machine learning models, including Random Forest (RF), XGBoost, Gaussian Process (GP), and Multilayer Perceptron (MLP), were employed to predict morphogenic traits based on culture conditions. XGBoost and RF outperformed other models, achieving R² values exceeding 0.95 for key variables such as shoot number and root length. These results demonstrate that data-driven modeling can enhance protocol precision and reduce experimental workload in plant tissue culture. The study also highlights the potential for combining physiological understanding with artificial intelligence to streamline future in vitro applications in woody species. Full article

This research develops a dual physics-based machine learning system to forecast fuel consumption and CO₂ emissions for a 100 m oil tanker across six operational scenarios: Original, Paint, Advanced Propeller, Fin, Bulbous Bow, and Combined. The combination of hydrodynamic calculations with Monte Carlo simulations provides a solid foundation for training machine learning models, particularly in cases where dataset restrictions are present. The XGBoost model demonstrated superior performance compared to Support Vector Regression, Gaussian Process Regression, Random Forest, and Shallow Neural Network models, achieving near-zero prediction errors that closely matched physics-based calculations. The physics-based analysis demonstrated that the Combined scenario, which combines hull coatings with bulbous bow modifications, produced the largest fuel consumption reduction (5.37% at 15 knots), followed by the Advanced Propeller scenario. The results demonstrate that user inputs (e.g., engine power: 870 kW, speed: 12.7 knots) match the Advanced Propeller scenario, followed by Paint, which indicates that advanced propellers or hull coatings would optimize efficiency. The obtained insights help ship operators modify their operational parameters and designers select essential modifications for sustainable operations. The model maintains its strength at low speeds, where fuel consumption is minimal, making it applicable to other oil tankers. The hybrid approach provides a new tool for maritime efficiency analysis, yielding interpretable results that support International Maritime Organization objectives, despite starting with a limited dataset. The model requires additional research to enhance its predictive accuracy using larger datasets and real-time data collection, which will aid in achieving global environmental stewardship. Full article

The polytetrafluoroethylene/aluminum (PTFE/Al) granular composite, a common formulation in impact-initiated energetic materials, undergoes mechanochemical coupling reactions under sufficiently strong dynamic loading. This investigation discusses the dynamic properties and the constitutive relationship of the PTFE/Al granular composite to provide a preliminary guide for the research on mechanical properties of a series of composite materials based on PTFE/Al as the matrix. Firstly, the 26.5Al-73.5PTFE (wt.%) composite specimens are prepared by preprocessing, mixing, molding, high-temperature sintering, and cooling. Then, the quasi-static compression and Hopkinson bar tests are performed to explore the mechanical properties of the PTFE/Al composite. Influences of the strain rate of loading on the yield stress, the ultimate strength, and the limited strain are also analyzed. Lastly, based on the experimental results, the material parameters in the Johnson–Cook constitutive model are obtained by the method of piecewise fitting to describe the stress–strain relation of the PTFE/Al composite. Combining the experimental details and the obtained material parameters, the numerical simulation of the dynamic compression of the PTFE/Al composite specimen is carried out by using the ANSYS/LS-DYNA platform. The results show that the computed stress–strain curves present a reasonable agreement with the experimental data. It should be declared that this research does not involve the energy release behavior of the 26.5Al-73.5PTFE (wt.%) reactive material because the material is not initiated within the strain rate range of the dynamic test in this paper. Full article

Lattice-based metamaterials have attracted much attention due to their excellent mechanical properties. Nevertheless, designing lattice materials with desired properties is still challenging, as their mesoscopic topology is extremely complex. Herein, the bidirectional evolutionary structural optimization (BESO) method is adopted to design lattice structures with maximum bulk modulus and elastic isotropy. Various lattice configurations are generated by controlling the filter radius during the optimization processes. Afterwards, the optimized lattices are fabricated using Stereo Lithography Appearance (SLA) printing technology. Experiments and numerical simulations are conducted to reveal the mechanical behavior of the topology-optimized lattices under quasi-static compression, which are compared with the traditional octet-truss (OT) and body-centered cubic (BCC) lattice structures. The results demonstrate that the topology-optimized lattices exhibited superior mechanical properties, including modulus, yield strength, and specific energy absorption, over traditional OT and BCC lattices. Moreover, apart from the elastic modulus, the yield stress and post-yield stress of the topology-optimized lattice structures with elastically isotropic constraints also present lower dependence on the loading direction. Accordingly, the topology optimization method can be employed for designing novel lattice structures with high performance. Full article

Titanium is widely recognized as an interesting material for electrodes due to its excellent corrosion resistance, mechanical strength, and biocompatibility. However, further functionalization is often necessary to impart advanced interfacial properties, such as selective ion transport or stimuli responsiveness. In this context, the integration of smart polymers, such as poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA)—noted for its dual pH- and thermo-responsive behavior—has emerged as a promising approach to tailor surface properties for next-generation devices. This work compares two covalent immobilization strategies for PDMAEMA on titanium: the “graft-to” method, involving the attachment of pre-synthesized polymer chains, and the “graft-from” method, based on surface-initiated polymerization. The resulting materials were characterized with size exclusion chromatography (SEC) for molecular weight, Fourier-transform infrared spectroscopy (FTIR) for chemical structure, scanning electron microscopy (SEM) for surface morphology, and contact angle measurements for wettability. Electrochemical impedance spectroscopy and polarization studies were used to assess electrochemical performance. Both strategies yielded uniform and stable coatings, with the mode of grafting influencing both surface morphology and functional stability. These findings provide valuable insights into the development of adaptive, stimuli-responsive titanium-based interfaces in advanced electrochemical systems. Full article

This study investigates the combined influence of superabsorbent polymers (SAPs) with distinct absorption kinetics and extended mixing sequences on the rheological, mechanical, and transport properties of high-performance concrete (HPC). Two SAPs—an ionic acrylamide-co-acrylic acid copolymer (SAP-P) and a non-ionic acrylamide polymer (SAP-B)—were incorporated at an internal curing level of 100%. The impact of extended mixing times (3, 5, and 7 min) following SAP addition was systematically evaluated. Results showed that longer mixing durations led to increased superplasticizer demand and higher plastic viscosity due to continued water absorption by SAPs. However, yield stress remained relatively stable owing to the dispersing effect of the added superplasticizer. Both SAPs significantly enhanced the static yield stress and improved fresh stability, as evidenced by reduced surface settlement. Despite the rheological changes, mechanical properties—including compressive and flexural strengths and modulus of elasticity—were consistently improved, regardless of mixing duration. SAP incorporation also led to notable reductions in autogenous and drying shrinkage, as well as enhanced electrical resistivity, indicating better durability performance. These findings suggest that a 3 min extended mixing time is sufficient for effective SAP dispersion without compromising performance. Full article

Low solar radiation, caused by climate change or dense planting patterns, now limits wheat production. Although wheat breeding has increased lodging resistance and yield potential through the introduction of dwarfing genes, it still reduces wheat yields. Few studies have been conducted to clarify the lodging sensitivity to shading of different-era wheat cultivars in China’s Huang-Huai-Hai region, as well as the characteristics of lodging resistance as affected by paclobutrazol under shading stress. To address this gap, the experiment included two wheat cultivars released in different decades, grown under shade and treated with or without paclobutrazol. The results showed that reductions in filling degree and lignin content, together with increases in length of the basal internode and gravity center height, markedly reduced the section modulus and breaking strength of shaded wheat culms. These changes impaired lodging resistance and raised lodging risk. However, paclobutrazol application effectively reduced lodging incidence and increased wheat yield under shading stress. Furthermore, these responses were more pronounced in the old cultivar (YZM) than in the modern cultivar (S28). This indicates that the culm mechanical parameters of the old cultivar were more shade-sensitive than those of the modern cultivar. Moreover, shading downregulated the relative expression levels of key genes associated with lignin biosynthesis to decrease the activities of key enzymes, thereby inhibiting the biosynthesis and deposition of lignin in culms to increase the risk of wheat lodging. Paclobutrazol application alleviated the inhibitory effects of shading on lignin biosynthesis, thereby strengthening culms and enhancing lodging resistance. These findings may provide a basis for exploring cultivation regulation methods to enhance wheat lodging resistance under overcast and low-sunshine conditions, and to offer guidance for the breeding of wheat cultivars with lodging resistance and shade tolerance. Full article

Graphene, a remarkable two-dimensional material, enhances the mechanical properties of high-entropy alloys as a reinforcing phase. This study investigated the influence of vacancy defects in graphene on the strengthening effect of FeNiCrCoCu high-entropy alloy through molecular dynamics simulations. The findings reveal that vacancy defects diminish graphene’s strength, resulting in its premature failure. In tensile tests, graphene with defects lowers the yield stress of the composite, yet it retains the ability to impede dislocations. Conversely, graphene exhibits a more pronounced strengthening effect during compression. Specifically, when the deletion of C atoms is less than 1%, the impact is negligible; between 1% and 6%, the strengthening effect diminishes; and when it surpasses 6%, the strengthening effect virtually ceases to exist. This research offers a theoretical foundation for optimizing graphene-reinforced composites. Full article

Oral delivery of hydrophobic compounds remains challenging due to their poor aqueous solubility and the potential toxicity associated with conventional surfactant-based emulsions. To address these issues, we present a surfactant-free encapsulation strategy using electrosprayed alginate hydrogel beads for the stable and controlled delivery of hydrophobic oils. Hydrophobic compounds were dispersed in high-viscosity alginate solutions without surfactants via ultrasonication, forming kinetically stable oil-in-water dispersions. These mixtures were electrosprayed into calcium chloride baths, yielding monodisperse hydrogel beads. Higher alginate concentrations improved droplet sphericity and suppressed phase separation by enhancing matrix viscosity. The resulting beads exhibited stimuli-responsive degradation and controlled release behavior in response to physiological ionic strength. Dense alginate networks delayed ion exchange and prolonged structural integrity, while elevated external ionic conditions triggered rapid disintegration and immediate payload release. This simple and scalable system offers a biocompatible platform for the oral delivery of lipophilic active compounds without the need for surfactants or complex fabrication steps. Full article

Zwitterionic hydrogels have emerged as eco-friendly anti-fouling materials owing to their superior hydration-mediated resistance to biofouling. Nevertheless, their practical utility remains constrained by intrinsically poor mechanical robustness. Herein, this study proposes a novel strategy to develop novel tough zwitterionic hydrogels by freezing the gels’ polymer network. As a proof of concept, a zwitterionic hydrogel was synthesized via copolymerization of hydrophobic monomer phenyl methacrylate (PMA) and hydrophilic cationic monomer N-(3-dimethylaminopropyl) methacrylamide (DMAPMA), followed by post-oxidation to yield a zwitterionic structure. At service temperature, the rigid and hydrophobic PMA segments remain frozen, while the hydrophilic zwitterionic units maintain substantial water content by osmotic pressure. Synergistically, the zwitterionic hydrogel achieves robust toughness and adhesiveness, with high rigidity (66 MPa), strength (4.78 MPa), and toughness (2.53 MJ/m³). Moreover, the hydrogel exhibits a distinct temperature-dependent behavior by manifesting softer and more stretchable behavior after heating, since the thawing of the gel network at high temperatures increases segmental mobility. Therefore, it achieved satisfactory adhesiveness to substrates (80 kPa). Additionally, the hydrogel demonstrated remarkable anti-fouling performance, effectively suppressing biofilm formation and larval attachment. In summary, this work opens up promising prospects for the development of zwitterionic hydrogels with high application potential. Full article

This study examines the effect of elevated printing speeds (100–600 mm/s) on the dimensional accuracy and tensile strength of PLA components fabricated via fused deposition modeling (FDM). To isolate the influence of printing speed, all other parameters were kept constant, and two filament variants—natural (unpigmented) and black PLA—were analyzed. ISO 527-2 type 1A specimens were produced and tested for dimensional deviations and ultimate tensile strength (UTS). The results indicate that printing speed has a marked impact on both geometric precision and mechanical performance. The optimal speed of 300 mm/s provided the best compromise between dimensional accuracy and tensile strength for both filaments. At speeds below 300 mm/s, under-extrusion caused weak layer bonding and air gaps, while speeds above 300 mm/s led to over-extrusion and structural defects due to thermal stress and rapid cooling. Black PLA yielded better dimensional accuracy at higher speeds, with cross-sectional deviations between 2.76% and 5.33%, while natural PLA showed larger deviations of up to 8.63%. However, natural PLA exhibited superior tensile strength, reaching up to 46.59 MPa, with black PLA showing up to 13.16% lower UTS values. The findings emphasize the importance of speed tuning and material selection for achieving high-quality, reliable, and efficient FDM prints. Full article

In this work, the W element, with a larger atomic radius compared to Co, Fe, and Ni, was added to modify the microstructure and enhance the yield strength of CoFeNi medium entropy alloy (MEA). A detailed study was conducted to clarify the effects of W additions and annealing temperatures on the microstructure evolution and mechanical properties of CoFeNiW_x (x = 0, 0.1, and 0.3) MEAs. CoFeNiW_0.1 retained a single FCC structure without the formation of precipitates in the FCC phase, indicating that W, with a larger atomic radius, can completely dissolve in CoFeNiW_0.1. For CoFeNiW_0.3 MEA, coarse particles with an average diameter of ~2 μm appeared after homogenizing. Nevertheless, when the alloy was annealed at 800 °C and 900 °C, fine particles formed, with the average diameters of approximately 144 nm and 225 nm, respectively. After annealing at 800 °C, the CoFeNiW_0.3 with a partially recrystallized microstructure exhibited better comprehensive mechanical properties. Full article