Search Results (3,086)

(Zr,Ti)B₂ ceramics with enhanced hardness and fracture toughness were prepared by spark plasma sintering using platelet TiB₂ and irregular ZrB₂ as starting powders. The effects of sintering temperature (1700–1900 °C) and platelet TiB₂ content (0–30 wt.%) on the sinterability, phase composition, microstructure, and mechanical properties of the (Zr,Ti)B₂ ceramics were investigated. With increasing sintering temperature, the relative density of the solid solution increased from 89.9 ± 0.5% at 1700 °C to 97.7 ± 0.4% at 1800 °C, followed by no significant change upon further temperature elevation; however, the relative density showed an initial increase and subsequent decrease with increasing TiB₂ content. Under optimized parameters (1800 °C, 3 min, 50 MPa, with a TiB₂ content of 30 wt.%), (Zr,Ti)B₂ ceramics achieve a maximum hardness of 24.9 ± 1.0 GPa, a fracture toughness of 5.0 ± 0.3 MPa·m^1/2, and a relative density of 96.5 ± 0.5%. The high content of platelet TiB₂ refined the (Zr,Ti)B₂ grain size, reducing the D50 by 25.8% to 1.70 μm compared to the 20 wt.% content. This study provides a novel perspective for the design and preparation of high-performance ceramics. Full article

High residual stresses significantly impact component performance during laser powder bed fusion (L-PBF) of GH3536 alloy. This study systematically investigates the effects of five scanning strategies (X-Scan, XY-Scan, R67, CB90, CB67) on residual stresses and deformation behavior in laser powder bed fusion-formed GH3536 high-temperature alloy. This is achieved by establishing a thermomechanically coupled mesoscale finite element model and combining it with experimental validation. The model was developed on the ANSYS APDL platform using a sequential coupling algorithm. It comprehensively considered melting latent heat, material nonlinearity, and dead-body element technology. While ensuring computational accuracy, significant computational efficiency gains were achieved through geometric scaling and reasonable simplifications (e.g., neglecting evaporation effects and assuming material isotropy). Results indicate that the 67° interlayer rotational scanning (R67) significantly reduces residual stresses, attributed to the breaking of thermal accumulation symmetry by asymmetric scanning. Component deformation is primarily governed by thermal stresses, with simulation results showing less than 10% deviation from experimental measurements. Despite the model’s medium-to-small scale and omission of size effects, its predicted trends highly correlate with X-ray diffraction measurements, validating its reliability for scan strategy optimization. Electron backscatter diffraction (EBSD) analysis further examined grain size and orientation differences at the microstructural level under the R67 strategy, revealing a more refined grain structure and KAM values. This provides theoretical support for L-PBF forming of nickel-based high-temperature alloys. Full article

In this study, we investigated the effect of heat treatment-induced grain size on the hydrogen embrittlement (HE) resistance of 30MnB5 steel, focusing particularly on the variation in prior austenite grain (PAG) size. As the heat treatment time increased, the PAGs coarsened, leading the martensite packets, blocks, and lath sizes to also coarsen. As the microstructure became more refined, the boundary density of the packet–block–lath structure increased along with a significant increase in the low-angle grain boundary (LAGB) fraction. The microstructure refinement accelerated the initial permeation rate of hydrogen, while the high density of LAGBs and trap sites effectively suppressed its long-term diffusion/localization. The slow strain rate tensile test confirmed that the tensile strength and elongation of 30MnB5 steel in a hydrogen environment were lower than those in air, indicating HE. Furthermore, the results showed that the HE sensitivity decreased in the fine microstructure condition, as evidenced by the smaller reduction in elongation compared to the coarse microstructure. The study results will enhance the understanding of hydrogen-induced degradation in hot-stamped automotive steels and offer fundamental insights for optimizing heat treatment strategies applied to 30MnB5 steel for mitigating HE. Full article

Soybean lodging severely impairs yield and quality, and its precise grading is a key prerequisite for intelligent agricultural management and loss assessment in agricultural insurance. Most existing studies have focused primarily on soybean lodging identification and lodging resistance evaluation, whereas methods for the precise differentiation of lodging grades remain to be refined. This study presents an improved AlexNet model integrated with a Local Feature Aggregation (LFA) attention mechanism and a dynamic optimization strategy for the accurate grading of soybean lodging. RGB imagery of soybean canopies during the grain-filling to early maturity stages was acquired via a multispectral unmanned aerial vehicle (UAV). A dynamic Dropout strategy was adopted to enhance model stability and mitigate overfitting, and the Particle Swarm Optimization (PSO) algorithm was employed to intelligently optimize key hyperparameters of the model. The results demonstrate that the optimized model achieved an overall accuracy of 94.23% on the test set, with an average loss of 0.0682 and an inference speed of 0.422 s/step. In independent field validation, the grading accuracies for the five lodging grades were 90.12%, 86.35%, 89.47%, 88.93%, and 92.76%, respectively, with a mean accuracy of 89.53%. The proposed model enables the rapid and precise grading of soybean lodging under field conditions, thereby providing effective technical support for intelligent field management and disaster loss assessment in soybean production. Full article

With the development of science and technology, heat dissipation has become a bottleneck problem restricting the development of fields such as transportation, machinery, electronics, and aerospace. Aiming to resolve the bottleneck problem of low thermal conductivity in traditional commercial magnesium alloys, this paper designed alloy compositions to investigate the effects of the solid solubility of La and Ce, and the size, morphology, distribution, and volume fraction of the second phase in the microstructure of magnesium alloys during the heat dissipation performance of the Mg-RE binary system and the Mg-Mn-La(Ce) system. The research shows that through CAFE simulation calculations, regulation can be achieved via the following methods: increasing the average nucleation undercooling, which leads to larger grain sizes; reducing the nucleation density, which results in larger grain sizes; and increasing the standard deviation of the average nucleation undercooling, which reduces the area of small grains while increasing the area of large grains. The thermal conductivity of both as-cast and solid-solution Mg-La (Ce) binary alloys gradually decreases with the increase in the added elements. However, after solution treatment, the thermal conductivity of the Mg-La (Ce) binary alloys is higher than that of the as-cast alloys. The addition of the Ce element helps refine the as-cast microstructure of the Mg-0.5Mn alloy. With the increase in Ce addition, the volume fraction of the Mg12Ce phase also increases. The thermal conductivity of the as-cast Mg-0.5Mn-xCe alloy gradually increases with rising temperature. Meanwhile, at room temperature, the thermal conductivity of the as-cast Mg-0.5Mn alloy gradually decreases with the increase in Ce addition, and the rate of decline gradually slows down due to the precipitation of the Mg12Ce phase. Full article

This work systematically investigates the influence of Mn content (0.1, 0.3, and 0.5 wt.%) on the microstructure, mechanical properties, and high-temperature stability of asymmetric extruded Mg-4.0Al-0.8Sn-0.3Ca-xMn alloys. The results demonstrate that Mn addition effectively promotes the formation of multi-scale secondary phases. Increasing the Mn content refines the average grain size from ∼2.82 µm to ∼1.89 µm and significantly modulates the recrystallization behavior of the alloy. The ATX4103-05Mn alloy (0.5 wt.% Mn) exhibits an optimal strength–ductility synergy, achieving a yield strength of 281.8 MPa and an elongation of 19.1%. Quantitative analysis reveals that this enhancement is predominantly governed by dispersion strengthening (∆σ_p∼34.1 MPa), with supplementary contributions from grain boundary and dislocation strengthening. Furthermore, the ATX4103-05Mn alloy shows superior resistance to abnormal grain growth after thermal exposure at 400 °C for 10 h, which is attributed to effective Zener pinning by the uniform distribution of short rod-shaped Al8Mn5 phases along the grain boundaries. This study elucidates the multi-scale strengthening and thermal stabilization mechanisms enabled by Mn microalloying, providing a viable pathway for developing high-performance, thermally stable magnesium alloys. Full article

Stalk lodging (the structural failure of plant stems prior to harvest) remains a major constraint to global cereal crop production, reducing yields, impairing grain quality, and increasing harvest losses. Since cellulose microfibrils are the primary load-bearing components in plant cell walls, the microfibril angle is widely considered a critical determinant of stalk mechanical properties. X-ray diffraction is a common technique for microfibril angle measurement, yet its applicability to cereal crops has not been fully validated. This study assessed the utility of X-ray diffraction based microfibril angle measurements for maize (Zea mays) and sorghum (Sorghum bicolor) stalks using the T-parameter method. Rind tissue samples from multiple maize and sorghum genotypes were analyzed using two diffractometers with copper (Cu) and molybdenum (Mo) X-ray sources. Corresponding internodes were also evaluated for rind penetration resistance, material bending stiffness, and bending strength to test whether measured microfibril angles reflected biologically meaningful variation. Across all genotypes and internodes, including preliminary observations from phenotypic extremes in select groups, microfibril angle values were highly uniform, with maize averaging 24.6° (Cu) and 29.1° (Mo) and sorghum averaging 24.3° (Cu) and 29.4° (Mo). microfibril angles exhibited extremely low variability (coefficient of variation < 3.3%), in stark contrast to the much higher variability observed in mechanical properties (CV = 20.5–47.1%). Systematic differences of ~20% between Cu- and Mo-based measurements were consistent across sample groups. Correlations between microfibril angle and mechanical properties were weak or absent; only Cu-derived microfibril angle showed a marginal relationship with bending stiffness, while Mo-derived microfibril angle showed no significant correlations. Pooled analyses further confirmed that microfibril angle remained nearly constant despite a wide range of mechanical property values. Collectively, these findings demonstrate that X-ray diffraction based microfibril angle measurements using the T-parameter method have limited applicability to cereal stalk tissues, as the method failed to capture biologically relevant variation. The uniformity of measured angles, lack of correlation with mechanical properties, and dependence on X-ray source raise concerns about the suitability of this method for maize and sorghum. These results highlight the need for refined or alternative microfibril angle measurement techniques to better understand the role of cellulose microfibril orientation in stalk lodging resistance. Full article

Fiscal transfers are a key policy instrument for supporting grain production, and a systematic assessment of their effects offers a critical basis for improving the design of incentive-based grain production policies. Unlike most existing studies, which primarily examine fiscal transfers from the perspective of improving farm households’ welfare and micro-level production decisions, this paper focuses on their impact on the grain production performance of major grain-producing counties, which account for over 80% of China’s grain output. Utilizing panel data from 1319 county-level units in China, this study employs a difference-in-differences (DID) approach to evaluate the impact of the “Reward Policy for Major Grain-Producing Counties (RPMGC)”, a central-to-county fiscal transfer program, on grain production. The empirical results indicate that: First, the reward policy significantly promotes grain production, and this finding remains robust across a series of robustness tests. Second, from a temporal perspective, the policy’s impact follows a trend of initially increasing and then decreasing over time, suggesting that the policy effects lack long-term sustainability. Third, mechanism analysis reveals that the policy enhances grain production by fostering technological advancement, mitigating production risks, and facilitating scaled-up production. Fourth, further analysis indicates that the policy effects are more pronounced in counties located within major grain-producing regions and those experiencing higher fiscal pressure. These findings provide valuable insights for improving the design of intergovernmental grain production incentives, refining grain production incentive mechanisms, and consolidating national food security. Full article

This study investigates the effects of current density on the microstructure and properties of electrodeposited NiCo-CeO₂ composite coatings. Results demonstrate that current density significantly influences coating composition, with higher CeO₂ and lower Co content increasing surface roughness (minimum at 30 mA/cm², maximum at 100 mA/cm²). Microstructural homogeneity improves with optimized Co/CeO₂ content, where the A30 coating (30 mA/cm²) exhibits the weakest texture among all coatings due to peak Co incorporation. Texture intensifies at higher current densities (30–100 mA/cm²) as Co and CeO₂ contents diminish. Internal stress depends on electrodeposition kinetics and particle dispersion, ranging from −2.22 MPa (A20) to 651 MPa (A50). Hardness correlates with (111) plane dominance and Co/CeO₂ content, reaching 449.8 HV for A30 but dropping to 288.8 HV for A100. Optimal current density tuning refines grains, enhances (111) texture, and improves compositional uniformity, endowing the A30 coating with balanced hardness and corrosion performance (corrosion potential: −224 mV; current density: 0.225 μA/cm²). These findings provide guidelines for tailoring high-performance NiCo-CeO₂ coatings through current density regulation. Full article

This paper focuses on analyzing the corrosion mechanism of stone cutting tool surfaces. Rare earth oxide films were prepared on the tool surface using the electrophoretic deposition–sintering method, and their corrosion resistance was investigated. Microstructural and compositional analyses of the surface layer of shot-peened tools and rare earth oxide films were conducted using characterization techniques such as SEM, EBSD, and XRD. The corrosion resistance of the rare earth oxide films was evaluated via an electrochemical workstation. The results indicate that the corrosion morphology on the stone cutting tool surface is pitting corrosion, which is significantly influenced by the friction of the tool coolant. Shot-peening treatment refines the grains in the tool surface layer, promoting the growth of rare earth oxide films. The rare earth oxide film is mainly composed of cerium oxide (CeO₂), presenting a continuous and dense structure with slight peeling after sintering. The Group 3 (0.1 mol/L, 3000 V/m, 5 min) rare earth oxide film exhibits the optimal electrochemical behavior and excellent corrosion resistance, with a corrosion potential (Ecorr) of −0.49 V and a corrosion current density (icorr) of 1.445 × 10⁻⁷ A/cm². Full article

This study addresses the issue of rare earth (RE) resource wastage caused by the aggregation of the commonly used diffusion source, Dy, at the triangular grain boundary region during grain boundary diffusion (GBD). The approach involves Ti doping to refine the grain size and increase the volume fraction of RE₆Fe₁₃Ga, thereby improving the efficiency of Dy utilization. The results show that when 0.2 wt% Ti is doped, Dy diffusion is applied to the magnet, and the magnet achieves excellent magnetic properties, with Br = 14.03 kGs, Hcj = 20.24 kOe, Q = 0.96, and (BH)max = 47.15 MGOe. The coercivity shows an enhancement of 8.66 kOe compared to the pristine magnet. Research and analysis indicate that doping Ti into the magnet promotes the formation of the RE6Fe13Ga phase, leading to the creation of continuous thin grain boundaries that weaken the exchange coupling between adjacent grains. Additionally, the presence of RE₆Fe₁₃Ga suppresses the segregation of Dy in the RE-rich phases, encouraging its further incorporation into the main phase and improving Dy utilization. This study demonstrates that appropriate Ti doping can effectively optimize Dy distribution within the magnet, reduce its aggregation in the triangular grain boundary region, and promote its incorporation into the main phase. This significantly reduces the amount of Dy required and provides a feasible approach to enhancing the efficiency of heavy rare earth resource utilization, thereby offering a path to the design of high-performance GBD magnets. Full article

Multimodal object detection utilizing RGB and infrared (IR) imagery has become a critical research area for unmanned aerial vehicle (UAV) surveillance applications, providing reliable perception under various lighting and environmental conditions. Nevertheless, current methods encounter three primary challenges: (1) insufficient utilization of frequency-domain properties in heterogeneous modalities, (2) restricted adaptability in crossmodal feature integration across different environmental scenarios, and (3) inadequate modeling of fine-grained spatial relationships for accurate object localization. To overcome these limitations, we introduce MFE-DETR, a novel Multimodal Feature-Enhanced Detection Transformer that achieves superior RGB-IR fusion through three complementary innovations. First, we present the Dual-Modality Enhancement Module (DMEM) with two specialized processing streams: the Haar wavelet decomposition stream (HWD-Stream) that conducts multi-resolution frequency-domain analysis to independently enhance low-frequency structural components and high-frequency textural information, and the Attention-guided Kolmogorov–Arnold Refinement Stream (AKR-Stream) that employs learnable spline-parameterized activation functions for adaptive nonlinear feature refinement. Second, we enhance the Cross-scale Channel Feature Fusion module by integrating an Adaptive Feature Fusion Module (AFAM) with complementary gating mechanisms that dynamically adjust modality contributions according to spatial informativeness. Third, we introduce the Bilinear Attention-Enhanced Detection Module (BADM) that models second-order feature interactions through factorized bilinear pooling, facilitating fine-grained crossmodal correlation analysis. Extensive experiments on the DroneVehicle benchmark show that MFE-DETR attains 78.6% mAP${}_{50}$ and 57.8% mAP${}_{50:95}$, outperforming state-of-the-art approaches by 5.3% and 3.7%, respectively. Additional evaluations on the VisDrone dataset further confirm the excellent generalization performance of our method, especially for small object detection with 18.6% AP${}_S$, achieving a 1.5% improvement over existing techniques. Comprehensive ablation studies and visualizations offer detailed insights into the effectiveness of each proposed component. Full article

The β grain size in titanium alloys during industrial forging is critical for balancing toughness, cost-effectiveness, and processability. To address the industrial challenge of high cost and difficulty in refining β grains to the tens of micrometers scale, this study investigates the feasibility of achieving a superior strength–ductility balance in TC18 alloy with near-industrial coarse β grains (296~857 μm) under room temperature tension. A pronounced inverse correlation is observed between β grain size and both strength and ductility. The yield strength–grain size relationship follows the Hall–Petch effect, while the anomalous increase in ductility for fine-grained specimens is attributed to three factors. First, smaller grains provide a higher grain boundary density, promoting stress redistribution and mitigating stress concentrations. Second, more uniform stress distribution induces thinner, denser kink bands that enhance plasticity. Third, strain-induced martensite evolves from discrete nanoscale particles to discontinuous lines and ultimately coalesces into continuous planar bands along the (112)β and (110)β planes. This phase transformation, which initiates below a critical grain size of ~500 μm, further alleviates stress concentrations towards slip bands and contributes to dynamic work hardening. The findings demonstrate that coordinated deformation mechanisms enable excellent mechanical performance even in coarse-grained microstructures, providing a practical pathway for optimizing industrial-grade titanium alloys. Full article

CoCuNiTi HEACs reinforced by different diamond contents were prepared on the surface of 45 steel substrate by laser cladding. Their phase composition, microstructure, elemental composition, and wear/corrosion resistance were investigated using XRD, OM, SEM, EDS, a friction and wear testing machine, and an electrochemical workstation, respectively. The results show that after adding diamond, the phase composition of the sample transforms from the original dual-phase structure of the FCC main phase and BCC to the dual-phase structure of the BCC main phase and FCC. With an increase in the diamond content, the diffraction peak intensity of the alloy phases first increases and then decreases. This behavior is related to the significant enhancement of the alloy phase crystallinity with low diamond addition and the intensified crystal lattice distortion caused by excessive diamond addition. The CoCuNiTi + x Diamond (C) (x = 0, 0.5, and 1.0 wt.%) high-entropy alloys have a dendritic structure. After the addition of diamond, no hole defects were observed in the microstructure, and the dendritic structure was significantly refined. Ti and C are enriched in the primary phase, Cu is enriched in the interdendrite regions, and Co exhibits the highest concentration in the dendrite regions. The segregation coefficients of Ni in all three alloys are relatively small. As the diamond content increases, the friction coefficient of the samples decreases significantly. The 1 wt.% diamond sample exhibits the best wear resistance, primarily owing to the combined effects of superhard phase strengthening, solid solution strengthening, and fine grain strengthening resulting from diamond addition. The sample with 0.5 wt.% diamond addition has the lowest self-corrosion current density, highest polarization resistance, and lowest annual corrosion rate, indicating the best corrosion resistance. This performance is mainly attributed to the refinement of the microstructure, reduction in defects, and formation of a dense passivation film caused by the addition of a small amount of diamond. Full article

To advance automatic tomato leaf disease detection in precision agriculture, this study addresses critical challenges in complex field environments, such as variable lesion scales, background interference, and deployment constraints. We propose MSP-Net, a task-driven detection framework with targeted architectural refinements integrating three specific optimizations. First, a Multi-Scale Perception Convolution Module (MSPCM) is introduced to capture diverse disease features across early-to-late infection stages. Second, SimAM-enhanced C3k2 layers are utilized to suppress background noise and focus on fine-grained lesion cues. Third, a Multi-Scale Feature Enhancement Module (MSFEM) bridges the semantic gap between shallow and deep features to improve fusion efficacy. Furthermore, we construct a lightweight variant, L-MSP-Net, using architectural migration and structured pruning for edge efficiency. Experimental results on the real-world Tomato-Village dataset show that MSP-Net achieves 92.0% mAP@0.5, outperforming the YOLOv11s baseline by 2.0%. L-MSP-Net attains 86.1% mAP@0.5, improving by 3.6% over the lightweight YOLOv11n baseline while reducing parameters by 10.5%, and is successfully deployed on the RK3588 edge platform. Additional cross-dataset experiments on PASCAL VOC and MS COCO evaluate the transferability of the proposed architectural refinements to generic object detection tasks. Full article