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Smart textiles capable of both energy harvesting and multifunctional sensing are highly desirable for next-generation portable electronics. However, there are still challenges that need to be conquered, such as the innovation of an energy-harvesting model and the optimization of interface bonding between fibers and active materials. Herein, inspired by the spiral structure of natural vines, a highly stretchable triboelectric helical yarn (TEHY) was manufactured by twisting the carbon nanotube/polyurethane nanofiber (CNT/PU NF) Janus membrane. The TEHY had a zebra-stripe-like design that was composed of black interval conductive CNTs and white insulative PU NFs. Due to the different electron affinity, the zebra-patterned TEHY realized a self-frictional triboelectric effect because the numerous microscopic CNT/PU triboelectric interfaces generated an alternating current in the external conductive circuit without extra external friction layers. The helical geometry combined with the elastic PU matrix endowed TEHY with superelastic stretchability and outstanding output stability after 1000 cycles of the stretch–release test. By virtue of the robust mechanical and electrical stability, the TEHY can not only be used as a high-entropy mechanical energy harvester but also serve as a self-powered sensor to monitor the stretching or deforming stimuli and human physiological activities in real time. These merits manifested the versatile applications of TEHY in smart fabrics, wearable power supplies, and human–machine interactions.

Multistage thermomechanical treatment experiments were conducted on Cu–Ni–Co–Si–Mg alloy strip prepared by the Heating Cooling Combined Mold (HCCM) horizontal continuous casting-cold rolling process. Effects of various heat treatments on the microstructure, mechanical properties, and electrical conductivity of the alloy were studied. The strengthening mechanisms and factors influencing the performance of each process has been analyzed. The tensile strength, yield strength, and electrical conductivity of Cu–Ni–Co–Si–Mg alloy can reach 894 MPa, 855 MPa, and 47.1 %IACS after a third-stage of thermomechanical treatment (TTMT). The cold rolling in first-stage of thermomechanical treatment (FTMT) not only caused work hardening of the alloy but also promoted the precipitation of solute atoms and the growth of second phase particles, limiting the increase in strength. Second-stage of thermomechanical treatment (STMT) effectively hindered the excessive growth of second phase particles in FTMT but shortened recrystallization process. The superior performance of Cu–Ni–Co–Si–Mg alloy after TTMT was attributed to dispersive precipitation of Ni, Co, and Si elements as (Ni, Co) 2Si phases in the copper matrix, strengthening the interaction between the precipitates and dislocations. A short process of HCCM horizontal continuous casting-cold rolling-thermomechanical treatment was developed to produce a high strength and highly electrically conductive Cu–Ni–Co–Si alloy strip used in lead frames.

Perovskite monocrystalline films are regarded as desirable candidates for the integration of high-performance optoelectronics due to their unique photophysical properties. However, the heterogeneous integration of a perovskite monocrystalline film with other semiconductors is fundamentally limited by the lattice mismatch, which hinders direct epitaxy. Herein, the van der Waals (vdW) integration strategy for 3D perovskites is developed, where perovskite monocrystalline films are epitaxially grown on the mother substrate, followed by its peeling off and transferring to arbitrary semiconductors, forming monocrystalline heterojunctions. The as-achieved CsPbBr3–Nb-doped SrTiO3(Nb:STO) vdW p–n heterojunction exhibited comparable performance to their directly epitaxial counterpart, demonstrating the feasibility of vdW integration for 3D perovskites. Furthermore, the vdW integration could be extended to silicon substrates, rendering the CsPbBr3–n-Si and CsPbCl3–p-Si p–n heterojunction with apparent rectification behaviors and photoresponse. The vdW integration significantly enriches the selections of semiconductors hybridizing with perovskites and provides opportunities for monocrystalline perovskite optoelectronics with complex configurations and multiple functionalities.

Twins play a crucial role in elucidating the structure and deformation characteristics of materials. However, in materials with low-symmetry crystal structures, solving the twin relationships remains a challenging task. In this study, we propose a general method for determining twin elements K1, η1, K2, and η2, which are essential for twin analysis. The proposed method involves three main steps: (1) representing misorientation data measured by electron back-scattered diffraction (EBSD) and transmission electron microscopy (TEM) in matrix form, (2) identifying additional 180° rotation elements related to twin elements K1or η1by traversing all symmetrically equivalent misorientations, and (3) using a minimum and crystal structure-dependent uniform shear as the constraint to determine the other twin elements (K2andη2). By combining the experimental data and the proposed method, we systematically analyze the complex twin relationships of Cu–Zn–Al shape memory alloys (SMAs) with monoclinic martensite (M18R). This methodology has been demonstrated to be effective and possesses broad applicability.

The use of bionic drag-reducing microstructures in artificial blood vessels can effectively reduce their resistance to blood flow. The characteristics of the blood vessel are analysed and simplified, and the resistance reduction effects of three bionic microstructure models, namely V-shaped, rectangular and semi-circular, are compared and analysed by numerical simulations, and the resistance reduction effects of the three groove structures in the tubular model are verified. The results show that the V-shaped groove structure occupies a smaller volume compared to the rectangular and semi-circular structures of the same size, has a significant drag reduction effect, is highly achievable and stable, and is the best choice as a drag reduction microstructure for artificial blood vessels. In addition, the wall shear stresses of the V-groove structure were further analysed to verify the shear effect of this microstructure in artificial blood vessels and to reveal the shear mechanism of the V-groove microstructure.

Creeping bentgrass (Agrostis stolonifera) is sensitive to supra‐optimal temperature, which makes summer bentgrass decline (SBD) a main conundrum troubling turf manager. Diethyl aminoethyl hexanoate (DA‐6) is an artificial and bioactive plant growth regulator affecting tolerance to various abiotic stresses. It is commercially available for field application due to multiple advantages such as low cost, environmentally friendly compound, and sustainable effect. However, the positive effect and mechanism of DA‐6‐mediated heat tolerance in cool‐season grass species and SBD are not yet been explored. Objectives of the study were to screen the optimal dose of DA‐6 for improvement in thermotolerance and to investigate roles of DA‐6 in regulating photosynthesis, osmotic balance, and antioxidant homeostasis in two creeping bentgrass cultivars (heat‐tolerant 13 M and heat‐sensitive Seaside II) in controlled heat condition. Summer heat tolerance induced by the DA‐6 was further evaluated for 2 years under field conditions in a subtropical zone. Results demonstrated that the optimal dose of DA‐6 was screened as 0.1 mM based on analyses of chlorophyll content, photochemical efficiency, and cell membrane stability under heat stress. Foliar application of DA‐6 significantly alleviated heat‐induced leaf senescence by improving photosynthetic performance, accumulation of sugars (sucrose, fructose, and glucose) for osmotic homeostasis, and total antioxidant capacity for reactive oxygen species scavenging in the two cultivars. A 2‐year field test was further carried out to demonstrate that turf quality of the two cultivars was significantly improved after being treated by foliar DA‐6 during hot summer months in 2020 and 2021. Current findings suggested that DA‐6‐mediated thermo‐resistant mechanism was associated with photosynthesis, osmotic adjustment, and antioxidant in cool‐season grass species. Foliar application of DA‐6 could be a cheap, effective, and environmentally friendly strategy to alleviate SBD. Foliar application of Diethyl aminoethyl hexanoate (DA‐6) could be a cheap, effective, and environmentally friendly strategy to alleviate summer bentgrass decline (SBD).DA‐6‐mediated thermo‐resistant mechanism was associated with photosynthesis, osmotic adjustment, and antioxidant.The optimal dose of DA‐6 for thermotolerance of creeping bentgrass was screened as 0.1 mM.

Catalytic therapy based on piezoelectric nanoparticles has become one of the effective strategies to eliminate tumors. However, it is still a challenge to improve the tumor delivery efficiency of piezoelectric nanoparticles, so that they can penetrate normal tissues while specifically aggregating at tumor sites and subsequently generating large amounts of reactive oxygen species (ROS) to achieve precise and efficient tumor clearance. In the present study, we successfully fabricated tumor microenvironment-responsive assembled barium titanate nanoparticles (tma-BTO NPs): in the neutral pH environment of normal tissues, tma-BTO NPs were monodisperse and possessed the ability to cross the intercellular space; whereas, the acidic environment of the tumor triggered the self-assembly of tma-BTO NPs to form submicron-scale aggregates, and deposited in the tumor microenvironment. The self-assembled tma-BTO NPs not only caused mechanical damage to tumor cells; more interestingly, they also exhibited enhanced piezoelectric catalytic efficiency and produced more ROS than monodisperse nanoparticles under ultrasonic excitation, attributed to the mutual extrusion of neighboring particles within the confined space of the assembly. tma-BTO NPs exhibited differential cytotoxicity against tumor cells and normal cells, and the stronger piezoelectric catalysis and mechanical damage induced by the assemblies resulted in significant apoptosis of mouse breast cancer cells (4T1); while there was little damage to mouse embryo osteoblast precursor cells (MC3T3-E1) under the same treatment conditions. Animal experiments confirmed that peritumoral injection of tma-BTO NPs combined with ultrasound therapy can effectively inhibit tumor progression non-invasively. The tumor microenvironment-responsive self-assembly strategy opens up new perspectives for future precise piezoelectric-catalyzed tumor therapy.

The implementation of industrial robots across various sectors has ushered in unparalleled advancements in efficiency, productivity, and safety. This paper explores the domain of semantic trajectory planning in the area of industrial robotics. By adeptly merging physical constraints and semantic knowledge of environments, the proposed methodology enables robots to navigate complex surroundings with utmost precision and efficiency. In a landscape marked by dynamic challenges, the research positions semantic trajectory planning as a linchpin in fostering adaptability. It ensures robots interact safely with their surroundings, providing vital object detection and recognition capabilities. The proposed ResNet model exhibits remarkable classification performance, bolstering overall productivity. The study underscores the significance of this approach in addressing real-world industrial applications while emphasizing accuracy, precision, and enhanced productivity.

Synthetic aperture radar (SAR) image intelligence interpretation is always a challenging task due to its special imaging mechanism. This article focuses on the aircraft detection and recognition in large-scale SAR images. The objects in large-size SAR images are usually sparsely distributed and tend to be highly concentrated in certain areas. Therefore, the detection and classification in SAR images are affected easily by the imaging environment, leading to ineffective and instability. It suffers from time-consuming, high false-alarm rate, and low recognition rate. To alleviate these problems, a joint probability detector integrated with scattering attention (SA) is designed for aircraft detection and classification. Based on the fact that all aircraft are parked in the airport area, an airport detection method with mixed strategy is proposed to obtain the valid region (airport), narrowing down the scope of detection area, increasing the detection efficiency, as well as suppressing a lot of false alarms outside the airport. Considering that it is easy to generate false alarms within the airport on account of clutter scattering interference, a two-stage detector is introduced to improve the accuracy by replacing a stronger region proposal network and optimizing a lower bound to a joint probabilistic objective over two stages. Furthermore, the classification encoder module incorporates SA into a convolution neural network to leverage the distribution relation among strong scattered points to enhance the classification performance. Finally, extensive experiments on the Zhong Ke Xing Tu (ZKXT) and GaoFen-3 datasets verify the effectiveness and superiority of the proposed approach, and surpass runner up by 5.3% with the mF1 indicator. On a large GaoFen3 image (16 550 × 11 945 pixels), the proposed method improves the detection speed by 187.52%, without sacrificing the accuracy.

Peripheral nerve injury (PNI) is a common clinical challenge, requiring timely and orderly initiation of synergistic anti-inflammatory and reparative therapy. Although the existing cascade drug delivery system can realize sequential drug release through regulation of the chemical structure of drug carriers, it is difficult to adjust the release kinetics of each drug based on the patient's condition. Therefore, there is an urgent need to develop a cascade drug delivery system that can dynamically adjust drug release and realize personalized treatment. Herein, we developed a responsive cascade drug delivery scaffold (RCDDS) which can adapt to the therapeutic time window, in which Vitamin B12 is used in early controllable release to suppress inflammation and nerve growth factor promotes regeneration by cascade loading. The RCDDS exhibited the ability to modulate the drug release kinetics by hierarchically opening polymer chains triggered by ultrasound, enabling real-time adjustment of the anti-inflammatory and neuroregenerative therapeutic time window depending on the patient's status. In the rat sciatic nerve injury model, the RCDDS group was able to achieve neural repair effects comparable to the autograft group in terms of tissue structure and motor function recovery. The development of the RCDDS provides a useful route toward an intelligent cascade drug delivery system for personalized therapy.

Different stress states have a significant influence on the magnitude of the microscopic plastic strain and result in the development of the microstructure evolution. As a result, a comprehensive understanding of the different scale variation on microstructure evolution during bending deformation is essential. The advanced high strength dual-phase (DP1180) steel was investigated using multiscale microstructure-based 3D representative volume element (RVE) modelling technology with emphasis on understanding the relationship between the microstructure, localised stress–strain evolution as well as the deformation characteristics in the bending process. It is demonstrated that the localised development in bending can be more accurately described by microscopic deformation when taking into account microstructural properties. Microstructure-based 3D RVEs from each chosen bending condition generally have comparable localisation properties, whilst the magnitudes and intensities differ. In addition, the most severe localised bands are predicted to occur close to the ferrite and martensite phase boundaries where the martensite grains are close together or have a somewhat sharp edge. The numerically predicted results for the microstructure evolution, shear bands development and stress and strain distribution after 3-point bending exhibit a good agreement with the relevant experimental observations.

As a novel class of metallic materials, bulk metallic glasses (BMGs) have attracted a great deal of attention owing to their technological promise for practical engineering applications. In nature, biological materials exhibit inherent multifunctional integration, which provides some inspiration for scientists and engineers to construct multifunctional artificial materials. In this contribution, inspired by superhydrophobic self-cleaning lotus leaves, multifunctional bulk metallic glasses (BMG) materials have been fabricated through the thermoplastic forming-based process followed by the SiO2/soot deposition. To mimic the microscale papillae of the lotus leaf, the BMG micropillar with a hemispherical top was first fabricated using micro-patterned silicon templates based on thermoplastic forming. The deposited randomly distributed SiO2/soot nanostructures covered on BMG micropillars are similar to the branch-like nanostructures on papillae of the lotus leaf. Micro-nanoscale hierarchical structures endow BMG replica with superhydrophobicity, a low adhesion towards water, and self-cleaning, similar to the natural lotus leaf. Furthermore, on the basis of the observation of the morphology of BMG replica in the Si mould, the formation mechanism of BMG replica was proposed in this work. The BMG materials with multifunction integration would extend their practical engineering applications and we expect this method could be widely adopted for the fabrication of other multifunctional BMG surfaces.

A storage code over a graph maps $K$ independent source symbols, each of $L_{w}$ bits, to $N$ coded symbols, each of $L_{v}$ bits, such that each coded symbol is stored in a node of the graph and each edge of the graph is associated with one source symbol. From a pair of nodes connected by an edge, the source symbol that is associated with the edge can be decoded. The ratio $L_{w}/L_{v}$ is called the symbol rate of a storage code and the highest symbol rate is called the capacity. We show that the three highest capacity values of storage codes over graphs are $2, 3/2, 4/3$ . We characterize all graphs over which the storage code capacity is 2 and $3/2$ , and for capacity value of $4/3$ , necessary condition and sufficient condition (that do not match) on the graphs are given.

Combining high hardness carbide of high vanadium cast iron with nano pearlite, which has high strength and toughness, represents an innovative attempt to explore a new technology for preparing high vanadium alloy. In this study, a high-silicon high-vanadium wear-resistance alloy (HSHVWRA) was designed, incorporating a nano pearlite matrix and carbides composite structure. By increasing the vanadium content, numerous high hardness micrometer vanadium carbides were obtained The CCT curve was shifted to the left by increasing the silicon content in the alloy. Subsequently, the nano pearlite matrix was obtained by air cooling after austenite at 1100 °C. After heat treatment, the inter lamellar spacing of pearlite decreased from 500 to 1500 nm in the as-cast state to 50–200 nm. The heat treatment process significantly improved the wear resistance of HSHVWRA by obtaining a nano pearlite matrix. The weight loss due to abrasive wear in the nano pearlite matrix-based HSHVWRA was reduced by 26.9 % compared to the traditional micro-pearlite matrix-based alloy. In the impact wear test, the wear weight of the nano pearlite material was reduced by 63.7 % compared to the cast sample, resulting in a maximum relative wear resistance of 2.75. Nano pearlite has the ability to prevent crack initiation between the matrix and carbides and inhibit the propagation of fatigue cracks, thereby enhancing the fatigue resistance of the matrix. Additionally, with a higher number of layered sheets, nano pearlite can effectively withstand impact loads. Meanwhile, submicron carbides dispersed in the nano pearlite matrix contribute to a second phase strengthening role and cooperate with nano pearlite to enhance the wear resistance of the materials.

Silicon significantly affects the microstructure and properties of wear-resistant alloys. To investigate the effect of silicon content on the microstructure and properties of high-vanadium wear-resistant alloys (HVWA), three alloys with different silicon content (HVWA-0.66Si, HVWA-2.14Si and HVWA-5.17Si) were formulated and synthesized. And the solidification structure and wear behavior of HVWAs were researched. The increased content of silicon enhances the precipitation temperature of VC and therefore promotes the formation of more pellet/agglomerate primary VC in solidification and decreases the content of strip eutectic VC. The as-cast structure of HVWAs comprises of pearlite, with numerous submicron carbides dispersed on the pearlite matrix. The increased content of silicon increases the lamellar spacing of pearlite and the particle size of submicron carbides. The lamellar spacing of pearlite in HVWA-0.66Si, HVWA-2.14Si and HVWA-5.17Si measures 50–300 nm, 200–600 nm and 300–1800 nm, correspondingly, while the size of the submicron carbides is 0.3–0.9 μm, 0.5–1.3 μm and 0.3–1.9 μm, accordingly. The impact toughness of the alloy reduces as the silicon content increases. The HVWA-5.17Si matrix has a hardness of 49.3 HRC and boasts exceptional wear resistance. Taking HVWA-0.66Si as a reference, the relative wear resistance εof HVWA-5.17Si has the highest wear resistance, with εreaching 1.75. The strong wear resistance of HVWA-5.17Si stems mainly from the solid solution of silicon in the matrix that heightens its hardness. This feature works in tandem with the high-hardness primary VC and an abundance of finely formed secondary vanadium carbides that precipitate in the as-cast alloy.

High entropy alloy (HEA) has high hardness, strength and excellent friction and wear properties, which also has broad application prospects in wear-resistant and high temperature coating, aerospace and military fields. However, one third of the world's total energy is consumed by various forms of friction or wear and tear, causing untold economic losses each year. The important way to reduce the wear is to increase the hardness of materials. The surface modification of high entropy alloy is an effective way to improve the friction and wear properties. In this paper, the research progress of high entropy alloys at home and abroad in recent years is reviewed, especially the surface treatment technology which can improve the friction and wear properties of high entropy alloys is introduced, and the influence of surface strengthening treatment on the friction and wear properties and mechanism of high entropy alloys is discussed. Surface treatment mainly includes surface mechanical strengthening, surface heat treatment strengthening, chemical heat treatment strengthening, surface laser cladding treatment, surface plasma treatment, surface electron beam treatment, vapor deposition technology. The purpose of this work is to provide a reference for the research on the friction and wear property of high entropy alloy, to provide corresponding ideas for the possible industrial demand in the future, and to provide the key research direction for future application.

With the rapid development of artificial intelligence and deep learning, image-text matching has gradually become an important research topic in cross-modal fields. Achieving correct image-text matching requires a strong understanding of the correspondence between visual and textual information. In recent years, deep learning-based image-text matching methods have achieved significant success. However, image-text matching requires a deep understanding of intra-modal information and the exploration of fine-grained alignment between image regions and textual words. How to integrate these two aspects into a single model remains a challenge. Additionally, reducing the internal complexity of the model and effectively constructing and utilizing prior knowledge are also areas worth exploring, therefore addressing the issues of excessive computational complexity in existing fine-grained matching methods and the lack of multi-perspective matching.

Accurate lane detection is crucial for the safety and reliability of multi-lane automated driving, where the complexity of traffic scenarios is significantly heightened. Leveraging the semantic segmentation capabilities of deep learning, we develop a modified U-Net architecture tailored for the precise identification of lane lines. Our model is trained and validated on a robust dataset from Kaggle, comprising 2975 annotated training images and 500 test images with masks. Empirical results demonstrate the model's proficiency, achieving a peak accuracy of 95.19% and a Dice score of 0.928, indicating exceptional precision in segmenting lanes. These results represent a notable contribution to the enhancement of safety in automated driving systems.

Biodegradable polymers (BPs), as fundamental materials for implantable biodegradable medical electronic device (IBMED) fabrication, can be used to prepare the encapsulation layer, substrate, and sensing materials of IBMEDs and the triboelectric materials of implantable triboelectric nanogenerators (TENGs) in particular. The basic properties of these materials determine IBMED performance and application. However, few studies have compared the basic properties of a comprehensive range of BPs, especially in terms of their triboelectric performances and related laws. Here, a comprehensive range of 40 kinds of triboelectric BP films were prepared and tested for triboelectric polarities and degradation in a uniform state. Particularly, we developed a triboelectric series based on these BPs and innovatively summarized the regularities and principles of influence of various main- or side-chain chemical groups on the triboelectric polarities of BPs. This study can not only help researchers to gain insight into the underlying mechanisms of triboelectrification of polymers but also provides important guidance for material selection, especially for the selection of triboelectric BPs for TENG-based IBMEDs in regard to basic research and application.

This prospective study aimed to investigate the combination of shear wave elastography (SWE) and BRAFV600E mutation testing for the diagnosis of papillary thyroid carcinoma (PTC). One hundred thyroid nodules with an American College of Radiology thyroid imaging reporting and data system classification of 4 or 5 were subjected to SWE measurement, BRAFV600E genotyping, fine-needle aspiration, and surgery. Nonparametric statistical tests were used to compare the differences in the elastic parameters and BRAF genotypes between benign and malignant thyroid nodules of PTC, and receiver operating characteristic curve analysis was conducted to compare the diagnostic efficacy. In addition, the correlations between elastic parameters and BRAFV600E mutation in PTC were analyzed using binary logistic regression. The SWE, BRAFV600E, and their combination exhibited sensitivities of 72.9%, 81.3%, and 85.4%, respectively, and specificities of 66.7%, 90.3%, and 86.5%, respectively, in the diagnosis of PTC (P< 0.05). The SWE, BRAFV600E, and their combination exhibited sensitivities of 50.0%, 24.1% and 56.3%, respectively, and specificities of 89.7%, 87.5% and 82.8%, respectively, in the diagnosis of central cervical lymph node metastasis (P< 0.05). The combined use of SWE and BRAFV600E detection had the largest area under the curve, indicating that this combination is more effective in diagnosing PTC and lymph node metastasis in the central region than either method alone. Furthermore, Emax was positively associated with the BRAFV600E genotype. In conclusion, the combination of SWE and BRAFV600E genotype detection can improve the diagnostic efficacy for PTC. Emax can predict the BRAFV600E mutation status.

A Cu–1.3Ni–1.2Co–0.7Si–0.3Cr–0.1Mg alloy with high strength and medium conductivity was designed and prepared. The effects of multistage thermomechanical treatment on the microstructure and properties of the alloy and its strengthening mechanism were studied. The results showed that a large number of nanoscale β-Ni3Si, δ-(Ni,Co)2Si and Cr phase particles precipitated in the high-density dislocation region and sub-grain boundaries during aging, and submicron Cr3Si phase particles formed during solidification of the alloy. The tensile strength, yield strength and electrical conductivity of the alloy were 882 MPa, 857 MPa and 46.7% (IACS), respectively. The main strengthening mechanisms of the alloy were precipitation strengthening, strain strengthening and sub-structure strengthening through the strengthening model calculation and measured strength.

Conditional disclosure of secrets (CDS) is the problem of disclosing as efficiently as possible, one secret from Alice and Bob to Carol if and only if the inputs at Alice and Bob satisfy some function. The information theoretic capacity of CDS is the maximum number of bits of the secret that can be securely disclosed per bit of total communication from Alice and Bob to Carol. All CDS instances, where the capacity is the highest and is equal to 1/2, are recently characterized through a noise and signal alignment approach and are described using a graph representation of the function. In this work, we go beyond the best case scenarios and further develop the alignment approach to characterize the linear capacity of a class of CDS instances to be $(\rho -1)/(2\rho)$ , where $\rho $ is a newly introduced and highly specific covering parameter of the graph representation of the function.

The addition of the second phase into tungsten can significantly refine the grain size of tungsten alloys, and also play a role in dispersion strengthening, thus improving the properties of tungsten alloy. As a preparation method of tungsten alloy powder, liquid-phase method avoids the disadvantage of mechanical alloying, and the obtained powder composition is accurate and controllable, with high purity and excellent uniformity. At present, the second phase particles used for dispersion strengthening tungsten alloys are mainly composed of oxides. Oxide particles can be synthesized and precipitated in nitrate solution through in situ chemical reaction, and are uniformly distributed in composite powder by mixing and stirring. Finally, the oxide dispersion strengthened tungsten alloy (ODS-W) was obtained by reduction and sintering. Liquid-phase methods for preparing ODS-W alloys include azeotropic distillation, sol–gel methods, freeze-drying, hydrothermal synthesis, spray-drying, etc. In this paper, several liquid-phase methods for preparing tungsten alloy composite powder precursors are reviewed, and their latest research progresses are discussed. In addition, the morphologies and properties of tungsten alloys prepared by different methods are compared, which provides guidance for preparing high-performance tungsten alloys.

Chiral hybrid perovskites combine the advantages of chiral materials and halide perovskites, offering an ideal platform for the design of circularly polarized light (CPL) detectors. The pyro-phototronic effect, as a special mechanism of the photoexcited pyroelectric signal, can significantly improve the performance of photodetectors, whereas it remains a great challenge to achieve pyroelectricity-based CPL detection. In this work, the chiroptical phenomena and the pyro-phototronic effect are combined in chiral–polar perovskites to achieve unprecedented pyroelectric-based CPL detection. Two novel two-dimensional (2D) lead-free chiral-polar double perovskites, S/R-[(4-aminophenyl)ethylamine]2AgBiI8·0.5H2O, are successfully designed and synthesized by introducing chiral organic ligands into metal halide frameworks. Strikingly, the photoresponse is substantially boosted with the support of the pyro-phototronic effect, showing an increased pyro-phototronic current that is 40 times greater than the photovoltaic current. Furthermore, the pyroelectric-based detector possesses excellent CPL detection capacity to distinguish different polarization states of CPL photons, which achieve an impressive glphof up to 0.27 at zero bias. This study provides a brand new process for CPL detection by utilizing the pyro-phototronic effect in chiral–polar perovskites, which opens a new avenue for chiral materials in optoelectronic applications.

The development of high-energy continuous wave (CW) laser has enabled the generation of output powers ranging from 300 to 500 kW. Understanding the ablation mechanism of CW lasers at high laser fluence is crucial for the design of effective high-energy laser protection materials. We note that the particle-like impurities present in the protective coating material can induce defects on the ceramic-like target surface during high-energy CW laser ablation, which can alter the laser absorptivity and manifest a completely different ablation mechanism. Here, we systematically investigate the mechanism of high-energy CW laser ablation of alumina ceramic, with a specific focus on the roles of defect induction, energy transfer, and impact sputtering in the dynamic ablation of target. Specifically, the transient processes between high-energy CW laser and ceramic target will be investigated in terms of the evolution results of the ablation region, the microscopic characteristics of the ablated material, the high time-resolved on-line monitoring, and the multiphase hydrodynamics simulation. Finally, the transparent property of molten alumina ceramic to laser is proved to allow for penetrating damage to ceramic-metal composites.

The bionic-inspired Ti–15Mo gradient porous structures were fabricated by selective laser melting (SLM) for the first time in this work. The compression-compression fatigue behavior of functional gradient Ti–15Mo porous structures is investigated, with emphasis on understanding the relationship between fatigue performance and microstructure. The microstructure of the samples was analyzed both before and after fatigue, and correlated with the fatigue performance. During cyclic deformation, the pillars exhibited a non-uniform local stress distribution, primarily attributed to the disparity of gradient density distribution. Fatigue cracks typically initiate at the place with the defects and subsequently propagate until structural damage occurs. Fatigue ratcheting effect occurs throughout the entire fatigue process while the fatigue damage typically initiates at a later stage in the fatigue process. The results indicated that the fatigue performance of the lateral gradient (LG) structure was superior to that of the homogeneous structure, while the vertical gradient (VG) structure exhibited the poorest fatigue performance.

Existing models still exhibit a deficiency in capturing more detailed contextual information when processing architectural images. This paper introduces a model for architectural image segmentation and retrieval based on an image segmentation network. Primarily, spatial attention is incorporated into the U-Net segmentation network to enhance the extraction of image features. Subsequently, a dual-path attention mechanism is integrated into the U-Net backbone network, facilitating the seamless integration of information across different spaces and scales. Experimental results showcase the superior performance of the proposed model on the test set, with average dice coefficient, accuracy, and recall reaching 94.67%, 95.61%, and 97.88%, respectively, outperforming comparative models. The proposed model can enhance the U-Net network's capability to identify targets within feature maps. The amalgamation of image segmentation networks and attention mechanisms in artificial intelligence technology enables precise segmentation and retrieval of architectural images.

Three kinds of molybdenum alloy are doped with 2.0 wt.% different ultrafine oxide particles (Al2O3, ZrO2and La2O3) via hydrothermal synthesis, co-precipitation, co-decomposition, powder metallurgy, and rotary swaging. Three nano-oxides refine molybdenum grains by more than 70% and change the fracture modes from brittle fracture to ductile fracture, thereby dramatically improving the integrated mechanical properties of the alloys. Moreover, the trade-off between strength and ductility is offset. Mo−ZrO2alloy has the highest strength and plasticity, which is attributed to fine ZrO2particles and a semi-coherent interface between ZrO2and molybdenum matrix. Moreover, a quantitative strengthening model correlating dislocation density, oxide volume fraction and size, and molybdenum grain size is established.

In this study, the effects of differences in grain size, grain boundary type and misorientation on the initiation of discontinuous precipitates are investigated for the Cu–5Ni–1.25Si alloy. Samples with different grain sizes are obtained by thermomechanical treatment, and the smaller the grain size, the higher the percentage of discontinuous precipitate at the same aging time, while there is no significant difference in the growth rate of the reaction front of discontinuous precipitates. EBSD is used to study the effect of grain boundary misorientation on discontinuous precipitates, the characteristics of discontinuous precipitates initiation on different grain boundaries are investigated by multivariate statistical analysis. It is found that discontinuous precipitates only initiate from random grain boundaries instead of coincident site lattice boundaries, where random grain boundaries with misorientation angles of 30–50° are more prone to discontinuous precipitates. And the initiation of DPs at different misorientation axes is different. There is a clear borderline for the axes such as <102>, <103>, and <203>. The grain boundaries below this borderline do not initiate DP, while all grain boundaries below this angle initiate DPs. The cases for axes such as <112>, <114>, and <214> are more complicated. On these misorientation axes, grain boundaries with lower or higher misorientation angles do not initiate DPs, while grain boundaries at intermediate range misorientation angles do initiate DPs.

Cu–Al2O3–TiB2is an important high-performance dual-phase dispersion strengthened copper alloy. The problem of serious coarseness and agglomeration of TiB2and Al2O3particles is a bottleneck that restricts the preparation of high-performance Cu–Al2O3–TiB2alloys by traditional liquid-phase in-situ reaction method. In this paper, an idea of combining the split cavity melting of complex reactants and efficient solidification of melt was proposed, and a new liquid phase in-situ reaction technology for dual-phase strengthened metal matrix composites was invented. Compared with the traditional liquid phase in-situ reaction method, the strengthening particles in the Cu-0.75Al2O3-0.75TiB2(wt.%, nominal composition) prepared by the new liquid phase in-situ reaction technology were more uniform, and the tensile strength and hardness were significantly improved. Large-deformation cold rolling can improve distribution of particles. With the increase of deformation, the main deformation mode of the composite changed from matrix plastic deformation to matrix-particle shear deformation, with the main fracture mechanism changing from particle-matrix interface fracture to particle shear fracture. The new liquid phase in-situ reaction technology effectively solved the problem of particle coarsening and agglomeration in Cu–Al2O3–TiB2composites. The new liquid phase in-situ reaction technology combined with large deformation is a new process with high efficiency and short flow for preparing dual-phase dispersion strengthened copper alloys.

The popular single-atom catalyst (SAC) Fe–N4 is generally believed to be an excellent oxygen reduction reaction (ORR) electrocatalyst, which is less active in the oxygen evolution reaction (OER). Herein, FeM–N6 configuration catalysts (M = Fe, Co, Ni, Cu, Ag, and Au) were constructed for the oxygen evolution reaction by embedding M dopants on Fe–N4 systems based on the density functional theory. The electronic structure analysis reveals that the Fe–M metal interactions play dominant roles in regulating the d orbital distributions of Fe sites, which in turn alter the catalytic OER performance. Subsequent thermodynamic results indicate that the potential-determining step (PDS) for all catalysts is the formation of OOH*, which exhibits a tendency of decreased overpotentials with enhanced metal interactions. Apart from these, the effects of axial ligands on the OER activity of the catalysts in practical conditions were considered. Generally, most of the axial ligands are found to be thermodynamically favorable for the OER process. Interestingly, a competitive relationship of the electrons from the d orbital of Fe sites was found between the axial ligand and the adsorbed intermediate species during the reaction, which raises the energy barrier for OH* to O* conversion and can even alter the PDS in certain cases. The present work sheds new light on the design of future high-performance OER catalysts.

As a warm‐season turfgrass, bermudagrass (Cynodon) is sensitive to low ambient temperature. The objectives of this study were to evaluate cold tolerance of a new variant Chuannong‐3 under field condition and to further elucidate metabolic and molecular bases of cold tolerance in the Chuannong‐3 as compared to triploid Tifdwarf (Cynodon transvaalensis× Cynodon dactylon) and tetraploid common bermudagrass 001 (C. dactylon). The Chuannong‐3 was identified as a triploid bermudagrass based on ploidy analysis. Chuannong‐3, Tifdwarf, or common bermudagrass 001 exhibited different tolerance to low temperature in field (Chuannong‐3 > common bermudagrass 001 > Tifdwarf). The Chuannong‐3 maintained significantly lower oxidative damage to cell membrane system, chlorophyll loss, and inhibition of photochemical efficiency as well as higher water‐soluble carbohydrate content than Tifdwarf or common bermudagrass 001 in winter of 2022 and 2021. Further study found that Chunanong‐3 exhibited the highest glucose, fructose, sucrose, raffinose content, raffinose synthase activity, and CdSPS1expression as compared to Tifdwarf and common bermudagrass 001, which provided potential protection against chilling and freezing damages. Chilling and freezing stresses significantly up‐regulated ABA‐dependent (endogenous ABA level, CdABF1, CdDHN4, and CdLEA3) and ABA‐independent (CdWRKY2, CdCBF1, and CdCOR440) pathways in three bermudagrasses, but the most pronounced effects were detected in the Chuannong‐3. These findings indicated that Chuannong‐3 had better ability to acclimate to low temperature stress in relation to up‐regulation of sugar accumulation and metabolism, ABA signaling, and CBF‐CORpathway. This new variant Chuannong‐3 could be a valuable bermudagrass grown in temperate and transition zones. New bermudagrass variant Chuannong‐3 has dwarf phenotype and strong cold tolerance.Chuannong‐3 is identified as a triploid bermudagrass based on ploidy analysis.Chuannong‐3, common bermudagrass 001, or Tifdwarf is classified as a cold‐tolerant, medium, or sensitive genotype.Chunanong‐3 exhibits strong tolerance to low temperature associated with enhanced sugar metabolism.Chunanong‐3 has strong cold tolerance related to up‐regulation of ABA and CBF pathways.