Search Results (67)

With the development of space laser networks, miniaturization and lightweight design have become inevitable trends in laser terminal development. In laser links, functions such as spot position measurement, ranging, and data transmission are usually performed by multiple independent units. Integrating these three functions can effectively reduce the size of the opto-mechanical structure and save space within the optical transceiver, thereby supporting the lightweight and compact growth of laser terminals. This paper presents an integrated scheme based on an optical direct-sequence spread-spectrum (DSSS) quadrant detector (QD) and regenerative codes, which enables spot position measurement, ranging, and data transmission through an optical transceiver. The core of this approach involves using a code tracking loop to perform correlation gain calculation, phase comparison, and demodulation of the pseudo-noise code-modulated laser signal, thereby achieving all three functions simultaneously. A desktop experimental system was built to test and verify the scheme’s accuracy and precision. The system achieved a ranging accuracy of 14 mm (1σ), a spot position measurement accuracy of 0.83 μm (1σ) at the target center, and a communication sensitivity of −31 dBm at a 10⁻⁴ bit error rate (BER) with a data rate of 1 Kbps. This study provides a reference for future lightweight optical terminals. Full article

The widespread adoption of electric vehicles (EVs) has posed significant challenges to the security of distribution grid loads. To address issues such as increased grid load fluctuations, rising user charging costs, and rapid load surges around midnight caused by uncoordinated nighttime charging of household electric vehicles in communities, this paper first models electric vehicle charging behavior as a Markov Decision Process (MDP). By improving the state-space sampling mechanism, a continuous space mapping and a priority mechanism are designed to transform the charging scheduling problem into a continuous decision-making framework while optimizing the dynamic adjustment between state and action spaces. On this basis, to achieve synergistic load forecasting and charging scheduling decisions, a forecast-augmented deep reinforcement learning method integrating Gated Recurrent Unit and Twin Delayed Deep Deterministic Policy Gradient (GRU-TD3) is proposed. This method constructs a multi-objective reward function that comprehensively considers time-of-use electricity pricing, load stability, and user demands. The method also applies a single-objective pre-training phase and a model-specific importance-sampling strategy to improve learning efficiency and policy stability. Its effectiveness is verified through extensive comparative and ablation validation. The results show that our method outperforms several benchmarks. Specifically, compared to the Deep Deterministic Policy Gradient (DDPG) and Particle Swarm Optimization (PSO) algorithms, it reduces user costs by 11.7% and the load standard deviation by 12.9%. In contrast to uncoordinated charging strategies, it achieves a 42.5% reduction in user costs and a 20.3% decrease in load standard deviation. Moreover, relative to single-objective cost optimization approaches, the proposed algorithm effectively suppresses short-term load growth rates and mitigates the “midnight peak” phenomenon. Full article

Ge-doped CIGSe absorbers were fabricated using a two-step process of depositing sputtered stacked Ge-doped CIGSe precursors and selenization annealing. The effects of Ge doping on the crystallinity as well as defects of CIGSe absorbers and the performance of CIGSe buffer-free solar cells were investigated. The results show that Ge doping significantly promotes the grain growth of CIGSe absorbers. Due to Ge loss via volatilization during selenization annealing, Ge residue is undetectable in Ge-doped absorbers. Ge doping offers an effective approach to improve CIGSe crystallinity without introducing notable impurity phases or Ge-related defects. However, Ge doping also induces Se loss, and excessive Se vacancy defects adversely affect the performance of the absorber. In addition, Ge doping increases the contact potential difference at CIGSe grain boundaries and is beneficial for reducing carrier recombination at these sites. Analysis of recombination rates in Ge-doped CIGSe buffer-free solar cells reveals that the combined effects of enhanced crystallinity and optimized electrical properties at grain boundaries effectively suppress the recombination in the space charge region, at the interface, and in the quasi-neutral region, leading to improved device performance. Full article

Rapidly exploring Random Trees (RRT) provide probabilistic completeness but often explore inefficiently in high-DOF manipulation tasks. We address this by proposing a contact-aware, two-level planner that couples a learned toggle–subgoal predictor with a conditional diffusion sampler in joint space under a completeness-preserving mixture with uniform sampling. An upper ResNet-based network predicts task-relevant milestones from RGB images: grasp/release “toggle” configurations and intermediate joint-space subgoals that serve as phase-wise, receding-horizon targets between consecutive contact events. Conditioned on these predictions and the current state, a lower-level diffusion model samples tree-extension segments—joint-space directions and step lengths—instead of absolute configurations. These proposals act as a drop-in replacement for uniform sampling in standard RRT/RRT-Connect, while a nonzero fraction of uniform samples preserves probabilistic completeness. By biasing growth toward contact-relevant regions, the planner concentrates the search near feasible approach manifolds without altering nearest-neighbor, steering, or collision-checking primitives. In mug pick-and-place simulations, the proposed method achieves higher success rates than diffusion and other sequence-based policies trained by imitation learning, and requires fewer RRT expansions than uniform and goal-biased RRT as well as prior learning-guided samplers based on CVAE and conditional GAN, under identical collision checking and iteration limits. Full article

This study investigates the differences in photosynthetic characteristics of Paphiopedilum parishii (Rchb.f.) Stein during its reproductive and nutrient growth periods. Using plants from the same individual, we compared light response curves, chlorophyll content, leaf epidermal structure, and leaf anatomical structure between these two growth stages. The results show the following: (1) The overall shape of the light response curves was similar across both periods, but plants in the nutrient growth period exhibited higher net photosynthetic rates (P_n) at all light intensities compared to those in the reproductive growth period. (2) During the nutrient growth period, apparent quantum efficiency (AQY), maximum net photosynthetic rate (P_max), and light saturation point (LSP) were all significantly higher than in the reproductive growth period, while the light compensation point (LCP) and dark respiration rate (Rd) showed no significant differences. (3) Structurally, during the nutrient growth period, stomatal density significantly increased, while stomatal area decreased. Additionally, leaf thickness and mesophyll tissue thickness both markedly increased, indicating enhanced carbon assimilation efficiency through improved CO₂ uptake capacity and expanded photosynthetic area. (4) Significant differences in leaf anatomical structure between the two periods were primarily observed in leaf thickness and mesophyll tissue thickness, providing more space for energy accumulation during the post-flowering recovery phase. This study systematically reveals the dynamic changes in photosynthetic physiology and structural characteristics of P. parishii across different phenological stages, offering a theoretical foundation for its reintroduction and cultivation management. Full article

TiAl alloys are ideal candidates to replace nickel-based superalloys in aero-engines due to their low density and high specific strength, yet their industrial application is hindered by narrow heat treatment windows and unbalanced mechanical performance. To address this, this study investigates the microstructure and mechanical properties of Ti-44.9Al-4.1Nb-1.0Mo-0.1B-0.05Y-0.05Si (TNM-derived) alloys hot-rolled in the (α₂ + γ) two-phase region. The research employs varying heat treatment temperatures (1150–1280 °C) and cooling rates (0.1–2.5 °C/s), combined with XRD, SEM, EBSD characterization, and 800 °C high-temperature tensile tests. Key findings: Discontinuous dynamic recrystallization (DDRX) of γ grains is the primary mechanism refining lamellar colonies during deformation. Higher heat treatment temperatures reduce γ/β phases (which constrain colony growth), increasing the volume fraction of lamellar colonies but exerting minimal impact on interlamellar spacing. Faster cooling shifts γ lamella nucleation from confined to grain boundaries to multi-sites (grain boundaries, γ lamella peripheries, α grains) and changes grain boundaries from jagged and interlocking to smooth and straight, which boosts nucleation sites and refines interlamellar spacing. Fine lamellar colonies and narrow interlamellar spacing enhance tensile strength, while eliminating brittle βo phases and promoting interlocking boundaries with uniform equiaxed γ grains improve plasticity. Full article

The rapid growth of data traffic in modern communication networks has led to the development of advanced high-capacity multiplexing methods. Orbital angular momentum (OAM)–based mode division multiplexing (MDM) offers a promising scheme by utilizing the orthogonality of helical phase modes to transmit independent data streams simultaneously. In this work, we introduce a novel adjacent mode separation method exploiting OAM’s concentric intensity characteristics for free-space optical (FSO) spatial multiplexing. This method enables the detection of each OAM channel based on its distinctive ring-shaped intensity distribution, contrary to the conventional on-axis phase flattening approach. Two spatially multiplexed signals with different modes are separated by aligning its concentric intensity ring with the active area of an avalanche photodiode (APD), effectively suppressing crosstalk from adjacent modes. Experimental measurements demonstrate that our method achieves a bit-error-rate (BER) performance not exceeding the forward error correction (FEC) threshold, $3.8\times {10}^{-3}$, at up to 160 Mbps of data rate, while the conventional detection scheme fails beyond 5 Mbps. The analysis of the eye diagram confirms that our concentric-ring demultiplexing system achieves a high signal-to-noise ratio (SNR) and mode selectivity. These results support the feasibility of the proposed concentric intensity-based mode separation methodology for constructing compact, high-throughput OAM-multiplexed FSO links. Full article

Quantum error correction (QEC) is crucial for achieving reliable quantum computation. Among topological QEC codes, color codes can correct bit-flip and phase-flip errors simultaneously, enabling efficient resource utilization. However, existing decoders such as the Union–Find (UF) algorithm exhibit limited accuracy under high noise levels. We propose a hybrid decoding framework that augments a modified UF algorithm—enhanced with a secondary growth strategy—with a lightweight recurrent neural network (RNN). The RNN refines the error chains identified by UF, improving resolution without significantly increasing computational overhead. The simulation results show that our method achieves notable accuracy gains over baseline UF decoding, particularly in high-error regimes, while preserving the near-linear runtime scaling and low memory footprint of UF. At higher physical error rates, RNN-based path optimization improves UF decoding accuracy by approximately 4.7%. The decoding threshold of the color code reaches 0.1365, representing an increase of about 2% compared to UF without RNN optimization. With its simple data structure and low space complexity, the proposed method is well suited for low-latency, resource-constrained quantum computing environments. Full article

The phase composition and morphological characteristics of eutectic carbides are key factors affecting the wear resistance and fatigue life of high-speed steel. In this study, a combination of experimental characterization and thermodynamic calculations was used to systematically reveal the dynamic regulation mechanism of cooling rate on eutectic carbides in M2Al high-speed steel. The results indicate that within a cooling rate range of 5 to 225 °C/min, the steel always contains a small amount of face-centered cubic-structured MC-type eutectic carbides and a large number of hexagonal close-packed structured M₂C-type eutectic carbides. The three-dimensional morphology of MC-type eutectic carbides is smooth and rod-like, and is insensitive to the cooling rate, while the three-dimensional morphology of M₂C-type eutectic carbides evolves from lamellar to dendritic with an increasing cooling rate. The increase in cooling rate significantly reduces the average size of eutectic carbides, increases the total area fraction, and improves the distribution uniformity. Additionally, the increase in cooling rate also promotes the significant refinement of secondary dendrites in M2Al high-speed steel, and the relationship between secondary dendrite arm spacing and cooling rate is ${\lambda }_{SDAS}=149.42\cdot {C_R}^{-0.39}$. Finally, combining thermodynamic calculations with kinetic analysis, this study found that the formation of eutectic carbides is dominated by the segregation of elements such as V, Mo, and C during the final stage of solidification, while the chemical composition and three-dimensional morphological evolution of M₂C-type eutectic carbides are synergistically controlled by the diffusion and competitive growth of elements such as W, Mo, and C in austenite. This study provides a theoretical basis for the solidification process and eutectic carbide control of M2Al high-speed steel. Full article

The isothermal oxidation behavior of single crystal DD6 film-cooling blades was investigated. The isothermal oxidation tests were conducted at 1050 °C, and the phase analysis was performed by XRD, while SEM (EDS) was employed to observe the material. In addition to experimental studies, a numerical simulation using three-dimensional finite element analysis based on Abaqus software (Version 6.13) was implemented to model the growth stress in specimens during the isothermal test. The obtained results showed that the average oxidation rate of specimens rose with increments in film hole spacing, up to a maximum value at a film hole spacing of 0.75 mm, and then fell, which could be interpreted with the concepts of the oxidation-affected zone and the growth stress. The results obtained from the numerical simulation of the growth stress agreed with the experimental results of the average oxidation rate. The oxide scale of film-cooling specimens mainly consisted of three layers, the NiO outer layer, the spinel sublayer containing cracks, and the non-continuous thin Al₂O₃ inner layer. The surface of the oxide scale commonly underwent spallation of the NiO outer layer, and the exposed sublayer could grow new NiO particles. The size of the NiO particles on the edge of the film holes was larger than those on the walls of the film holes. SEM images clearly showed that electro-hydraulic beam drilling on DD6 superalloy specimens could erode the γ phase in the γ/γ′ two-phase matrix, thereby inducing damages in regions near film holes. Full article

Tutton salts have received considerable attention due to their potential applications in thermochemical energy storage (TCHS) systems. This technology requires high-purity materials that exhibit reversible dehydration reactions, significant variations in dehydration enthalpy, and high-temperature melting points. In this study, K₂Cu(SO₄)₂(H₂O)₆ Tutton salt in the form of single crystals was grown using the slow solvent evaporation method. Their structural, morphological, and thermal characteristics are presented and discussed, as well as temperature-induced phase transformations. At room temperature, the salt crystallizes in a monoclinic structure belonging to the P2₁/a space group, which is typical for Tutton salts. The lack of precise control over the solvent evaporation rate during crystal growth introduced structural disorder, resulting in defects on the crystal surface, including layer discontinuities, occlusions, and pores. Thermoanalytical analyses revealed two stages of mass loss, corresponding to the release of 4 + 2 coordinated H₂O molecules—four weakly coordinated and two strongly coordinated to the copper. The estimated dehydration enthalpy was ≈ 80.8 kJ/mol per mole of H₂O. Powder X-ray diffraction measurements as a function of temperature showed two phase transformations associated with the complete dehydration of the starting salt occurring between 28 and 160 °C, further corroborating the thermal results. The total dehydration up to ≈ 160 °C, high enthalpy associated with this process, and high melting point temperature make K₂Cu(SO₄)₂(H₂O)₆ a promising candidate for TCHS applications. Full article

High-carbon hardline steels are primarily used for the manufacture of tire beads for both automobiles and aircraft, and vanadium (V) microalloying is an important means of adjusting the microstructure of high-carbon hardline steels. Using scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM), the microstructure and precipitation phases of continuous cooled high-carbon steels were characterized, and the vanadium content, carbon diffusion coefficient, and critical precipitation temperature were calculated. The results showed that as the V content increased to 0.06 wt.%, the interlamellar spacing (ILS) of the pearlite in the experimental steel decreased to 0.110 μm, and the carbon diffusion coefficient in the experimental steel decreased to 0.98 × 10⁻³ cm²·s⁻¹. The pearlite content in the experimental steel with 0.02 wt.% V reached its maximum at a cooling rate of 5 °C·s⁻¹, and a small amount of bainite was observed in the experimental steel at a cooling rate of 10 °C·s⁻¹. The precipitated phase was VC with a diameter of ~24.73 nm, and the misfit between ferrite and VC was 5.02%, forming a semi-coherent interface between the two. Atoms gradually adjust their positions to allow the growth of VC along the ferrite direction. As the V content increased to 0.06 wt.%, the precipitation-temperature-time curve (PTT) shifted to the left, and the critical nucleation temperature for homogeneous nucleation, grain boundary nucleation, and dislocation line nucleation increased from 570.6, 676.9, and 692.4 °C to 634.6, 748.5, and 755.5 °C, respectively. Full article

An augmentative biological control program using the egg parasitoid Telenomus podisi Ashmead (Hymenoptera: Platygastridae) is a promising tool for the management of the brown stink bug, Euschistus heros (Fabricius) (Hemiptera: Pentatomidae) in soybeans. The T. podisi are released as adults or pupae within lab-reared E. heros eggs. Because of the small size of the parasitoid and potentially limited dispersal ability, determining the optimal release pattern is critical for biological control of the target pest. This study used sentinel E. heros eggs to investigate T. podisi dispersal within soybean crops during two distinct phenological stages: the beginning of flowering (Vn–R1) and the grain-filling phase (R5–R6). Data were analyzed using semi-variograms and kriging maps. The results indicate significant differences in parasitism rates between the two plant growth stages and among different matrices. The maximum dispersal range for T. podisi was calculated at 39.0 m in the Vn–R1 stage with a maximum parasitism rate of 42%, while in the R5–R6 stage, the maximum dispersal range was calculated to be 30.9 m with a maximum parasitism of 73%. Therefore, it is recommended that release points for T. podisi be spaced no further than 30 m apart. These results provide valuable insights for future research and applications in biological control strategies, including adjustment of the logistics and release technique depending upon the crop phenological stage. Full article

This paper investigates the effect of the element La on plasma nitriding of the CoCrCuFeNi high-entropy alloy (HEA) at 440 °C for 8, 16, and 24 h. The phase composition, morphology, and hardness distribution of the nitrided layer are characterized using XRD, optical microscopy, and a microhardness tester. Furthermore, the corrosion resistance is tested using an electrochemical workstation. The study evaluated the friction and wear performance using a testing machine and scanning electron microscope. The thickness of the effective hardening layer after 16 h of treatment with La was similar to that after 24 h of treatment without La. The addition of La significantly increased the growth rate constant of the effective hardening layer from 0.53 × 10⁻¹⁴ m²/s to 0.72 × 10⁻¹⁴ m²/s. In addition, an expanded FCC phase with greater interplanar spacing can be formed on the surface of the sample by introducing La into the plasma nitriding process. This indicates that the expanded FCC phase, with a higher concentration of interstitial nitrogen atoms, can effectively improve the corrosion resistance of the specimen surface. The corrosion rate of the specimen surface was reduced by 27.5% and the wear rate was reduced by 41.7% after 16 h of treatment with the addition of La compared to 24 h of nitriding without the addition of La. It has been shown that the addition of La to the plasma nitriding process results in a higher quality nitrided layer in a shorter time and also demonstrates that La has the potential to optimize the surface properties of plasma nitrided HEAs. Full article

Economic development and urbanization naturally give rise to expanding demand for new buildings, whose construction and operation inevitably lead to significant increases in energy consumption and greenhouse gas emissions. To better conserve resources and protect the environment, technologies for green buildings have evolved significantly in the past two decades. In this study, a scientometric analysis of green buildings research from 2003 to 2023 was performed using CiteSpace. A total of 1986 articles retrieved from the Web of Science (WoS) core collection database were used as the data source for an in-depth analysis of research trends, hotspots, and future directions, showing changes in publication numbers, core journals, key countries, and institutions that have made remarkable contributions in this field. The results showed that the field of green buildings research is in a phase of rapid growth. The current research hotspots include the adoption of the green buildings paradigm, rating systems, energy performance, greenhouse gas emissions, indoor environmental quality, and green roofs/walls. Based on the keywords citation bursts and literature review, we believe that government promotion measures, use of renewable energy, integration with plants, and application of artificial intelligence (AI) in green buildings will be the most promising development directions in the future. Full article