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The interpenetrating connection of icosahedra network (ICOIN) was termed as structural skeleton, which could quantify the strength and ductility of MGs. The impact of different rejuvenation methods on medium-range order (MRO) alterations was rarely studied. This work employed molecular dynamics simulations to examine the difference in MRO evolution of metallic glasses treated by recovery annealing and thermal-pressure treatment during uniaxial tension. All of the specimens obtain enhanced ductility due to improved potential energy. During tension, ICOI of all rejuvenated specimens exhibits an increased destruction rate and a decreased transformation rate. However, there are some converse characteristics in the specimens under different rejuvenation methods. The rejuvenated specimens treated by recovery annealing exhibit increased free volume and decreased ICOIN density. After thermal-pressure treatment, the rejuvenated specimens demonstrated decreased free volume and enhanced ICOIN density. During tension, the enhancement of icosahedral free volume in specimens treated by thermal pressure largely decreased the ICOIN density, thereby increasing the ductility. After tension, the rejuvenated specimens under high pressure have a significant reduction in ICOIN density compared to those under recovery annealing. The significance of this work is to accurately regulate the ICOIN density of rejuvenated specimens.

Purpose: Image registration is a critical component in medical image analysis applications. Optimization algorithms for energy functions play a crucial role in registration. Most registration methods improve the performance by modifying the energy function and optimizing it directly, neglecting the impact of the optimization algorithm. This paper is to investigate how to efficiently design an attention allocation strategy and improve the convergence of the optimization algorithm. Methods: This paper introduces a novel image registration method that leverages the distributed alternating direction method of multipliers to perform optimization, named DADMMreg. Compared to the optimization algorithm using the alternating direction method of multipliers (ADMM), the optimization algorithm used in DADMMreg achieves better convergence by altering the optimization order of the similarity and regularization terms within the energy function. To overcome the limitations of intensity-based or structural-based similarity metrics, a modified structural similarity measure (SSIM) is proposed that takes into account both intensity and structural information. Considering that homogeneous smoothing prior at the sliding surface leads to inaccurate registration, a novel vector-modulus-based regularization metric is proposed to avoid physically implausible displacement fields. Results: Experimental results on 4D-CT image dataset and COPD image dataset demonstrate the satisfactory registration performance of DADMMreg, with an average target registration error (TRE) of 0.9105 mm and 0.9201 mm, respectively. Meanwhile, the experimental results show that the DADMMreg method exhibits better convergence performance than other registration methods. Conclusion: Compared to classical methods, the attention allocation strategy of DADMMreg enables faster convergence with comparable registration accuracy.

Purpose: In order to reduce the influence of respiratory motion artifacts on lung ventilation estimation method, a lung ventilation estimation method based on multi-feature fusion of supervoxels (MFFS) and CT image registration is proposed. Methods: In MFFS, the Simple Linear Iterative Clustering (SLIC) algorithm is used in the initial layer of supervoxel clustering to solve the problem of large errors produced voxel level pulmonary ventilation estimation method. Combined with geometric feature and gradient feature of CT lung images, an objective function of local weighted multi-feature fusion that contains clustering prior knowledge is designed to optimize and subdivide initial supervoxel. The inspiratory and expiratory peak images are registered using deformable image registration (DIR) method to obtain the image deformation field, which is then used to calculate the variations of CT values in the supervoxel region for obtaining ventilation volume of supervoxel region. The expiratory peak image is represented by multiple layers of supervoxels, and the final CT ventilation estimation image (CTVI) is acquired throuogh averaging all supervoxel layers, which can effectively enhance the robustness of the MFFS method. Results: Experimental results demonstrate that the proposed MFFS method combined with CT image registration can obtain an average Spearman coefficient of 0.43 between the CTVIs and public VAMPIRE dataset. Conclusion: In contrast to classical lung ventilation estimation methods, MFFS method completely considers the contribution of multiple features of supervoxel regions in lung images to clustering centres, resulting in more regular lung tissue shapes.

Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP–MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP–MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP–MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex–complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.

Active polymetallic atomic clusters can initiate heterogeneous catalytic reactions in the tumor microenvironment, and the products tend to cause manifold damage to cell metabolic functions. Herein, bimetallic PtPd atomic clusters (BAC) are constructed by the stripping of Pt and Pd nanoparticles on nitrogen-doped carbon and follow-up surface PEGylation, aiming at efficacious antineoplastic therapy through heterogeneous catalytic processes. After endocytosed by tumor cells, BAC with catalase-mimic activity can facilitate the decomposition of endogenous H2O2into O2. The local oxygenation not only alleviates hypoxia to reduce the invasion ability of cancer cells but also enhances the yield of •O2–from O2catalyzed by BAC. Meanwhile, BAC also exhibit peroxidase-mimic activity for •OH production from H2O2. The enrichment of reactive oxygen species (ROS), including the radicals of •OH and •O2–, causes significant oxidative cellular damage and triggers severe apoptosis. In another aspect, intrinsic glutathione (GSH) peroxidase-like activity of BAC can indirectly upregulate the level of lipid peroxides and promote ferroptosis. Such deleterious redox dyshomeostasis caused by ROS accumulation and GSH consumption also results in immunogenic cell death to stimulate antitumor immunity for metastasis suppression. Collectively, this paradigm is expected to inspire more facile designs of polymetallic atomic clusters in disease therapy.

Embedded phase-change random-access memory (ePCRAM) applications demand superior data retention in amorphous phase-change materials (PCMs). Traditional PCM design strategies have focused on enhancing the thermal stability of the amorphous phase, often at the expense of the crystallization speed. While this approach supports reliable microchip operations, it compromises the ability to achieve rapid responses. To address this limitation, we modified ultrafast-crystallizing Sb thin films by incorporating Sc dopants, achieving the highest 10-year retention temperature (∼175°C) among binary antimonide PCMs while maintaining a sub-10-ns SET operation speed. This reconciliation of two seemingly contradictory properties arises from the unique kinetic features of the 5-nm-thick Sc12Sb88films, which exhibit an enlarged fragile-to-strong crossover in viscosity at medium supercooled temperature zones and an incompatible sublattice ordering behavior between the Sc and Sb atoms. By tailoring the crystallization kinetics of PCMs through strategic doping and nanoscale confinement, we provide new opportunities for developing robust yet swift ePCRAMs.

Image registration of liver dynamic contrast-enhanced computed tomography (DCE-CT) is crucial for diagnosis and image-guided surgical planning of liver cancer. However, intensity variations due to the flow of contrast agents combined with complex spatial motion induced by respiration brings great challenge to existing intensity-based registration methods. To address these problems, we propose a novel structure-aware registration method by incorporating structural information of related organs with segmentation-guided deep registration network. Existing segmentation-guided registration methods only focus on volumetric registration inside the paired organ segmentations, ignoring the inherent attributes of their anatomical structures. In addition, such paired organ segmentations are not always available in DCE-CT images due to the flow of contrast agents. Different from existing segmentation-guided registration methods, our proposed method extracts structural information in hierarchical geometric perspectives of line and surface. Then, according to the extracted structural information, structure-aware constraints are constructed and imposed on the forward and backward deformation field simultaneously. In this way, all available organ segmentations, including unpaired ones, can be fully utilized to avoid the side effect of contrast agent and preserve the topology of organs during registration. Extensive experiments on an in-house liver DCE-CT dataset and a public LiTS dataset show that our proposed method can achieve higher registration accuracy and preserve anatomical structure more effectively than state-of-the-art methods.

A start–end frame pair and a motion pattern-based motion synthesis scheme can provide more control to the synthesis process and produce content-various motion sequences. However, the data preparation for the motion training is intractable, and concatenating feature spaces of the start–end frame pair and the motion pattern lacks theoretical rationality in previous works. In this article, we propose a deep learning framework that completes automatic data preparation and learns the nonlinear mapping from start–end frame pairs to motion patterns. The proposed model consists of three modules: action detection, motion extraction, and motion synthesis networks. The action detection network extends the deep subspace learning framework to a supervised version, i.e., uses the local self-expression (LSE) of the motion data to supervise feature learning and complement the classification error. A long short-term memory (LSTM)-based network is used to efficiently extract the motion patterns to address the speed deficiency reflected in the previous optimization-based method. A motion synthesis network consists of a group of LSTM-based blocks, where each of them is to learn the nonlinear relation between the start–end frame pairs and the motion patterns of a certain joint. The superior performances in action detection accuracy, motion pattern extraction efficiency, and motion synthesis quality show the effectiveness of each module in the proposed framework.

Pyrroloquinoline quinone (PQQ) is a bioactive compound that has attracted significant attention due to its potential health benefits. In this study, we developed a new magnetic molecularly imprinted nanoparticle (MMIN) for the selective extraction and determination of PQQ from food samples. The MMIN was synthesized using a surface molecular imprinting technique with PQQ as the template molecule, Fe3O4nanoparticles as the magnetic core, and methacrylic acid as the functional monomer. The MMIN exhibited high selectivity and affinity towards PQQ, allowing for efficient extraction and preconcentration of PQQ from complex food matrices. The extracted PQQ was then quantified using HPLC-DAD. The developed method showed good linearity (R2= 0.9985) and low limits of detection (0.03 μg L−1). The accuracy and precision of the method were evaluated by analyzing spiked food samples, with average recoveries close to 89.8%. The MMIN also demonstrated good reusability, with negligible decrease in extraction efficiency after five cycles of use. Overall, the developed MMIN-based method provides a reliable and efficient approach for the analysis of PQQ in food samples.

Motion compression technologies can significantly reduce the redundant information of motion data and increase the efficiency of storage and transmission. Current methods mainly utilize some ready-made universal algorithms, such as signal processing and dimensionality reduction, to model the statistical characteristics of motion data, while the individual structure of motion data is ignored. In this paper, we propose to use a deep neural network with specially designed architecture to represent motion data considering the similarity between the articulated structure of a human skeleton and the architecture of neural networks. The network parameters are then taken as the compressed data. We design a structurally connected network which just looks like a human skeleton. Within the network, only the neurons corresponding to the joints connected to each other in a human skeleton are connected. It effectively exploits the correlations between connected joints to cut down the unnecessary connections between the neurons, which leads to the significant improvement of compression efficiency. Additionally, we extract the two inherent DOFs instead of the original three DOFs of each joint by representing its movement on a sphere according to the rigidity of the articulated human skeleton. This actually achieves the theoretically lossless pre-compression with the ratio of 3:2. Extensive experiment results demonstrate the superior performances of the proposed model at the high compression ratios over other state-of-the-art methods.

The high strength and stability of the full-lamellar structure guarantee the industrial application of the β-solidifying γ-TiAl alloys. However, it is a huge challenge to design an alloy with good hot-deformability as well as the full-lamellar structure. The low-cost Ti–42.5Al–2Mn–0.4Mo–0.1B–0.1C (at.%) alloy was designed, which undergoes both β and α single-phase region during the solidification. It is found that the full-lamellar structure can be obtained by the solution heat treatment at 1230 °C for 20 min and then aging treatment at 800 °C for 3 h. Interestingly, a new microstructure, namely, the pearlitic-like microstructure (PM) induced by the α2/γ → βo+ γ cellular reaction was observed when the aging temperature is increased to above 800 °C. The volume fraction of the PM is gradually increased from 0% to 25.5%, 65%, and 94% according to elevated aging temperature from 800 to 900, 1000, and 1050 °C, respectively. The mechanism of the reduced α2/γ lamellae and PM formation was discussed regarding the heterogeneous distribution of β stabilizing elements and the interface energy stored in α2/γ lamellae.

A high-sensitivity fiber optic strain sensor based on chirped fiber Bragg grating-Fabry Perot interferometer (CFBG-FPI) and vernier effect is proposed and has been demonstrated to have a strain sensitivity of −123.8 pm/μϵ. With femtosecond laser direct writing technology, two pairs of CFBGs with the same reflectivity, length, chirp rate and center wavelength are inscribed inside the single-mode fiber core, forming two separated CFBG-FPIs. Combined with the vernier effect principle, the interferometric cavity lengths of the two CFBG-FPIs were designed at about 1.7 mm and 1.68 mm as the reference arm and sensing arm, respectively, to form the vernier effect system, and the spacing between the reference arm and the sensing arm was 1 m. Experimental results show that in this vernier effect system, the strain sensitivity gain due to the vernier effect reaches a staggering 91-fold relative to a single CFBG-FPI, resulting in an ultra-high sensitivity of −123.8 pm/μϵ. In addition to being compact and convenient to manufacture, the sensor exhibits a low temperature cross-sensitivity down to −0.14 μϵ/°C. The many advantages make this sensor extremely promising for high-precision strain measurement applications.

In clinical practice, it is desirable for medical image segmentation models to be able to continually learn on a sequential data stream from multiple sites, rather than a consolidated dataset, due to storage cost and privacy restrictions. However, when learning on a new site, existing methods struggle with a weak memorizability for previous sites with complex shape and semantic information, and a poor explainability for the memory consolidation process. In this work, we propose a novel Shape and Semantics-based Selective Regularization ( $\text{S}^{{3}}\text{R}$ ) method for explainable cross-site continual segmentation to maintain both shape and semantic knowledge of previously learned sites. Specifically, $\text{S}^{{3}}\text{R}$ method adopts a selective regularization scheme to penalize changes of parameters with high Joint Shape and Semantics-based Importance (JSSI) weights, which are estimated based on the parameter sensitivity to shape properties and reliable semantics of the segmentation object. This helps to prevent the related shape and semantic knowledge from being forgotten. Moreover, we propose an Importance Activation Mapping (IAM) method for memory interpretation, which indicates the spatial support for important parameters to visualize the memorized content. We have extensively evaluated our method on prostate segmentation and optic cup and disc segmentation tasks. Our method outperforms other comparison methods in reducing model forgetting and increasing explainability. Our code is available at https://github.com/jingyzhang/S3R.

The development of the β-solidifying γ-TiAl alloys with good oxidation resistance and thermal deformation ability has always been crucial for the practical application. However, increasing the content of the antioxidant elements, such as Nb, Al, etc., tends to be detrimental to the deformability of the alloys. In this work, a novel Nb, Mn containing β-solidifying TiAl alloy with the nominal composition of Ti-43Al-1.5Mn-3Nb-0.2C-0.2Si-0.1B (at. %) (named as NbMn-TiAl) is invented, which goes through the single β phase as well as the α phase during solidification, resulting in the final as-cast microstructure of nearly full lamellar structure (NFL). Subsequently, the isothermal compression tests were performed within a temperature range of 1100 °C–1300 °C and a strain rate range of 0.001 s−1-10 s−1, the hot processing maps and constitutive equation were established. Moreover, the deformation mechanisms were clarified, including the bending/kinking of the α2/γ lamellar colonies, the dynamic recrystallization (DRX) of γ phase and α phase at different temperatures. Rolled bars with a diameter of 12 mm were then directly fabricated from the ingot by conventional hot rolling process. The as-rolled bars exhibited excellent oxidation resistance and mechanical properties that outperform many available TiAl alloys manufactured using various methods.

Accurate switching device characterization is necessary for effectively utilizing the technological advantages of Silicon Carbide (SiC) Power Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) over their Silicon (Si) Insulated-Gate Bipolar Transistor (IGBT) counterparts. With switching times of few nanoseconds, the unprecedented switching speed of SiC semiconductor devices challenges today's converter and characterization setup designs in regard to parasitic layout inductances for optimal conversion and reliable characterization data. Furthermore, active gate driving is a key to unlock the potential of SiC MOSFETs, but requires performance assessment prior to integration. This article presents a low-inductive test platform for flexible and high-accuracy characterization of fast-switching SiC MOSFETs and active gate drivers evaluation. The test circuit delivers high quality characterization data that is comparable with a commercial dynamic power device characterizer. In addition to the conventional hard-switching double-pulse tests with a two-level voltage source gate driver, the test circuit offers soft-switching and gate driver evaluation capability in addition. This test platform is a valuable tool for obtaining reliable characterization data to develop more accurate SiC MOSFET simulation models, and evaluate the combination of gate driver and MOSFET prior to the prototyping phase of a converter.

Residual stress induced by welding easily causes deformation and even fracture failure in welded structures. In this paper, a three-dimensional thermal-mechanical coupling finite element model of friction stir welding (FSW) was developed. The effects of different welding processes, namely conventional friction stir welding (C-FSW), stationary shoulder friction stir welding (SS-FSW), and bobbin tool friction stir welding (BT-FSW), on the temperature, residual stress, and deformation of welded joints were investigated by employing a heat source model and a force model to the welding analysis. The results reveal that a discernible disparity in temperature gradient is observed in the region ahead of the tool and behind it among various welding processes. The peak values of longitudinal residual stress along the surface and bottom paths of SS-FSW are reduced by 35.7% and 34.1%, respectively. In addition, the deformation at the initial end of the weld is slightly larger than that at the final end along the welding direction in three welding processes. Compared with other FSW processes, SS-FSW exhibits the smallest deformation, which is advantageous for improving assembly accuracy and enhancing the load-bearing capacity of weldments. The above results provide an important theoretical reference for the FSW process optimization of Ti62A alloy.

Snapshot-type polarization spectral imaging is a crucial dynamic high-speed target detection method in remote sensing in space because it has a high temporal resolution. However, the sparse representation of snapshot-type imaging in spectral or spatial dimension leads to low spectral or spatial resolution. To resolve the problem, we propose double-channel complementary microarray coding for snapshot-type polarization spectral imaging by utilizing the transmission and reflection complementary principle of a single microarray coding plate, the dual-channel multispectral and hyperspectral (HS) image fused to enhance the resolution of polarization spectral imaging. This study combined with the principle of intensity modulation used in full polarization measurements and established the spectral modulation and reconstruction model of dual-channel complementary microarray coding. According to the principle of dual-channel complementary snapshot polarization spectral imaging proposed in this article, the dual-channel multispectral and HS image fusion model was set up. This study improved the snapshot polarization spectral imaging spectral and spatial resolutions, increased the spatial resolution PSNR by 3 dB, and made the spectral resolution significantly higher. The findings of this study can assist in achieving high temporal resolution, high spectral resolution, high spatial resolution, and fully polarized snapshot-type polarization spectral imaging.

• The optimum process parameters for preparing AlCoCrFeNi 2.1 were determined. • Formation mechanism of regular eutectic lamella of AlCoCrFeNi 2.1 was revealed. • The printed AlCoCrFeNi 2.1 possessed excellent match of strength and plasticity. • The strain hardening effect caused by synergistic deformation was emphasized. Eutectic high entropy alloy (EHEA) possesses promising prospects for industrial application due to its controllable and near-equilibrium dual-phase structure. Due to the advantages of high material utilization, efficient production, and design freedom, the laser powder bed fusion (LPBF) technique provides a new path to prepare EHEA components with complex structure and excellent performance. In this study, near fully dense AlCoCrFeNi 2.1 samples were obtained by adjusting the process parameters of LPBF. Considering the balling phenomenon and powder splashing during the LPBF process, laser remelting was selected as an optimized scanning strategy to further improve the forming quality of AlCoCrFeNi 2.1. The microstructure of remelted AlCoCrFeNi 2.1 sample exhibited regular eutectic lamellae consisting of nano-scale face-centered-cubic (FCC) and B2 phases, in which the FCC phase accounted for a higher proportion. By investigating the tensile behavior and deformation mechanism, it was revealed that the ultrafine eutectic lamellae could induce a strong dual-phase synergistic strengthening, thereby significantly improving the strength of the sample. Compared with the vacuum induction melted (VIM) sample, the remelted sample showed a 54% increase in ultimate tensile strength (UTS -1518 MPa) and a 130% increase in yield strength (YS -1235 MPa) with reasonable plasticity. This study indicates that by combining the design and manufacturing freedom of LPBF with the EHEA, it is expected to fabricate high-property 3D EHEA parts, expanding the application field of EHEA. [ABSTRACT FROM AUTHOR]

• Microstructure entirely consists of fine equiaxed grains, reducing the anisotropy of tensile properties. • σ UTS , σ y , and elongation reach 618 MPa, 542 MPa, and 5.7% after T6 heat treatment. • The highest tensile and yield strengths achieved among the existing reported WAAM aluminum alloys. The utilization of wire-arc additive manufacturing (WAAM) technology for the preparation of Al-Zn-Mg-Cu aluminum alloy has made some progress in recent years. However, the challenge still remains to achieve ultra-high strength (600 MPa) in WAAM. In this study, the crack-free Al-Zn-Mg-Cu- Sc thin-wall component with ultra-high strength was successfully fabricated by the cold metal transfer (CMT) process using a self-prepared 7B55- Sc filler wire. The microstructures of both as-deposited and T6 heat-treated samples were all composed of fine equiaxed grains with an average size of about 6.0 μm. The primary Al 3 (Sc , Zr) particles acted as heterogeneous nuclei to promote the formation of equiaxed grains and refine the microstructures during the solidification process. A large amount of continuous eutectic structures rich in Al, Zn, Mg, and Cu elements formed along the grain boundaries under the as-deposited condition, and the precipitated second phases within the grains mainly included the equilibrium η phase, metastable η ′ phase and large-sized T phase. After T6 heat treatment, the majority of the second phases originally distributed within grains and along grain boundaries were dissolved into the Al matrix, and a large amount of fine GP zones, η ′ phase and secondary Al 3 (Sc ,Zr) particles were precipitated within the grains during the aging process. The tensile strength reached a recorded level of 618 MPa in the horizontal direction after T6 heat treatment, which was considered a breakthrough for the manufacturing of 600 MPa grade aluminum alloy by WAAM. [Display omitted] [ABSTRACT FROM AUTHOR]

Protein complexes constitute the primary functional modules of cellular activity. To respond to perturbations, complexes undergo changes in their abundance, subunit composition, or state of modification. Understanding the function of biological systems requires global strategies to capture this contextual state information. Methods based on cofractionation paired with mass spectrometry have demonstrated the capability for deep biological insight, but the scope of studies using this approach has been limited by the large measurement time per biological sample and challenges with data analysis. There has been little uptake of this strategy into the broader life science community despite its rich biological information content. We present a rapid integrated experimental and computational workflow to assess the reorganization of protein complexes across multiple cellular states. The workflow combines short gradient chromatography and DIA/SWATH mass spectrometry with a data analysis toolset to quantify changes in a complex organization. We applied the workflow to study the global protein complex rearrangements of THP-1 cells undergoing monocyte to macrophage differentiation and subsequent stimulation of macrophage cells with lipopolysaccharide. We observed substantial proteome reorganization on differentiation and less pronounced changes in macrophage stimulation. We establish our integrated differential pipeline for rapid and state-specific profiling of protein complex organization.

The microstructures, mechanical properties and corrosion behaviors of the ultra-high strength Al–Zn–Mg–Cu-Sc aluminum alloy fabricated by wire-arc additive manufacturing process using a self-prepared 7B55-Sc filler wire were systematically investigated under different heat treatments. The results showed that the microstructures of the as-deposited, T6, T73, and retrogression and re-aging (RRA) heat treatments were all composed of fine equiaxed grains with a size of about 6.0 μm. The grain boundary precipitates (GBPs) of the as-deposited sample were very coarse and continuously distributed along the grain boundaries, and the intragranular precipitates (IGPs) mainly consisted of a small amount of ηMg(Zn,Cu,Al)2and η′phases. After T6 heat treatment, the GBPs became much finer, but still continuously distributed along the grain boundaries. The IGPs mainly consisted of fine GP zones and η′phases. After RRA heat treatment, the GBPs became coarser and discontinuously distributed along the grain boundaries. The IGPs were composed of η′phases and ηMg(Zn,Cu,Al)2phases. After T73 heat treatment, the GBPs became much coarser and sparsely distributed along the grain boundaries. The IGPs mainly consisted of coarser ηMg(Zn,Cu,Al)2phases. The T6 heat-treated sample achieved the highest tensile strength of 618 MPa. While the strength of T73 heat-treated sample was sacrificed by up to 17% compared with the T6 heat-treated sample, but the corrosion resistance was the best of all heat-treated conditions. After RRA heat treatment, the strength was about 10% lower than the strength of the T6 condition, but the corrosion resistance was better than that of the T6 heat-treated sample.

Mechanistic understanding of asymmetric induction plays a crucial role in designing new catalytic asymmetric reactions. Reported herein is atroposelective access to C–N axially chiral isoquinolones via rhodium-catalyzed C–H activation of N-alkoxy benzamides and annulation with imidoyl sulfoxonium ylides. The coupling system proceeded with excellent functional group tolerance, and different conditions were identified to afford one or the other enantiomeric product each in excellent enantioselectivity for a representative class of the sulfoxonium ylide reagent, thus making both enantiomers readily available using the same catalyst. Experimental and computational studies revealed a pathway of C–H alkylation and enantio-determining formal nucleophilic substitution-C–N cyclization that is mediated by the rhodium catalyst via σ-bond metathesis as the asymmetric induction mechanism. Computational studies indicated that the solvent-dependent enatiodivergence originated from different levels of σ-bond metathesis mediated by neutral versus cationic rhodium species.

• Distribution behavior of inclusions in CSP-produced martensitic steel was studied. • High inclusion density resulted in lower total elongation and impact toughness. • MnS inclusion with high aspect ratio led to stronger mechanical anisotropy. • Effect mechanism of inclusions features on the microcracks initiation was studied. The distribution behavior of inclusions in martensitic steel produced by compact strip production process (CSP-MS) and its influence on mechanical properties were systematically investigated. The inclusions in the CSP-MS specimen are mainly composed of spherical Al 2 O 3 −CaO−CaS, MnS with high aspect ratio and small-sized TiN, whereas many coarse cuboidal TiN inclusions do exist in conventional martensitic steel (Con-MS). The high inclusion density of the CSP-MS specimen resulted in lower total elongation and impact toughness, and the MnS inclusions with high aspect ratio led to significantly stronger mechanical anisotropy than that for Con-MS specimen. The in-situ tensile results indicated that when the fracture direction is parallel to MnS direction, the microcracks induced by MnS inclusions tend to propagate into the matrix, leading to the formation of valley-like features, which significantly deteriorate the properties such as the total elongation and impact toughness. The microcracks caused by TiN inclusions are sharper than those caused by spherical Al 2 O 3 −CaO−CaS inclusions, and are easy to propagate into the matrix. This work is expected to guide the optimization of the mechanical properties of martensitic steels produced by CSP process and provide a theoretical basis for the CSP process design. [ABSTRACT FROM AUTHOR]

In the present study, 2219-T87 Al alloy plates, 4 mm in thickness, were subjected to bobbin tool friction stir welding (BT-FSW) under relatively high welding speeds of 200 and 400 mm/min, with the aim to analyze the effect of welding speeds on fatigue properties of the joints. The results showed that the tension–tension high-cycle fatigue performance of the BT-FSW joints at room temperature was significantly enhanced compared to that of other joints of 2xxx series Al alloys counterparts. Particularly at a high welding speed of 400 mm/min, the fatigue strength of the joint reached 78% of the base material together with a high tensile strength of 311 MPa. It was found that the joint line remnants had no effects on the fatigue properties of the BT-FSW joints due to the elimination of root flaws under the action of the lower shoulder. Most of the samples with the welding speed of 200 mm/min failed at the thermo-mechanical zone (TMAZ) during fatigue tests, attributable to the coarsened grains and precipitates, but all of the samples with high welding speed of 400 mm/min randomly failed at the nugget zone due to the improved hardness value in the TMAZ.

Carbon fiber composites are widely used in aerospace, rail transportation, and other fields. In the three-dimensional weaving process of carbon fiber preforms, the collision and dislocation of weaving needle and guide bar caused by the deformation of guide bar directly affect the normal operation of weaving process. In order to improve the precast precision and quality, this paper intends to study the deformation mechanism of the outermost guide rod by combining theory and experiment. Based on statically indestructible beam theory, a mathematical model of the influence of the number of weaving layers on the deflection of the guide bar was established, and the influence of the number of weaving layers on the value range of the weaving region and the influence of the transverse precision of the precast was obtained. With the increase of weaving layers, the needle feeding range gradually decreases, the compacted layer is 100 layers compared with 20 layers, and the injection interval is reduced by 20.93%. When the compacted layer is 60 layers, the range of needle insertion decreases rapidly with the increase of the number of layers in each step. Compared with the 10 layers in each step, the range of needle insertion decreases 30.54% when the number of layers in each step is 25 layers, and it is better to control the number of layers in each step within 20 layers. When weaving 120 layers in different steps, the average deviation between the theoretical and experimental values of transverse accuracy is 5.06%, which verifies the correctness of the theoretical calculation. It provides a theoretical basis for the design of fiber prefabricated fabric weaving equipment and the improvement of weaving technology.

ABSTRACT The sintering process of belite sulphoaluminate cement ([CSA.sup.1]) clinker is still not clear to date. Besides, there are few reports concerning producing CSA by recycled BOF slag. Therefore, the [...]

Enzymes can activate otherwise unreactive substrates by using residues precisely located in the active sites. We herein report on a Ga porphyrin which bears a second-sphere sulfonic group (named as 1) and its high efficiency for the electrocatalytic hydrogen evolution reaction (HER). Complex 1can achieve a large TOF value of 1.3 × 105s−1at low 295-mV overpotential with weak acetic acid (HOAc) as the proton source. Notably, 1can catalyze H2generation at potentials close to the thermodynamic HER equilibrium, but the sulfonic-free analogues require >250 mV more cathodic potentials to initiate HER. Mechanistic studies showed that two-electron reduced Ga porphyrins were protonated to form GaIII-H. For 1, its GaIII-H underwent rapid protonolysis with HOAc to evolve H2, but for sulfonic-free analogues, their GaIII-H required further reduction at more cathodic potentials to trigger catalysis. This work presents a synthetic molecular catalyst to achieve high HER rates under low overpotentials by promoting the protonolysis of metal hydrides with otherwise unreactive weak acids.

In this article, an optimum ferrite beads design method is proposed to suppress the self-sustained turn-off oscillation of cascode gallium nitride high-electron-mobility transistors (GaN HEMTs). At first, the impacts of gate loop beads and power loop beads on the turn-off oscillation of cascode GaN HEMTs are analyzed. The analysis reveals the weak damping effect of gate loop beads on the turn-off oscillation. Next, an analytical method is proposed to design the power loop beads that can achieve maximum effective damping on the turn-off oscillation. The power loop beads introduce extra stray inductance in the power loop, which can induce high-voltage overshoot. To tackle the problem, an optimum design method is proposed, so that the power loop beads can suppress the oscillation while mitigating the voltage overshoot. The accuracy of the proposed model is validated by the experimental data in the end.

In this article, an analytical model is proposed to model collector–emitter voltage rising slope ( $dV_{\text {CE}}/dt$ ) of field-stop insulated gate bipolar transistor (FS IGBT) during the turn-off transient. Thanks to TCAD simulation, the internal physics of the FS IGBT during $V_{\text {CE}}$ rise transient is investigated. Based on the improved understanding of the $V_{\text {CE}}$ rise transient, an analytical solution of the excess carrier distribution in the N-base region and field-stop (FS) layer is derived. An analytical model for $dV_{\text {CE}}/dt$ of FS IGBT is also proposed. The temperature dependency of various silicon material and device parameters is included in the model. In the end, the double-pulse tests are performed on 650-V/40-A and 1200-V/40-A FS IGBTs. The test results are compared with the analytical predictions and good agreement is obtained.

In this article, a complete expression for $dV_{CE}/dt$ and $dI_{C}/dt$ at turn-on transient of field-stop (FS) insulated gate bipolar transistor (IGBT) is proposed. With numerical simulation utilized, the critical stray elements and internal physics which have a significant impact on turn-on behavior of FS IGBT are identified. Based on the improved understanding on the turn-on behavior, the turn-on transient is divided into two phases and the equivalent circuits of each phase are obtained. The analytical expressions of $dV_{CE}/dt$ and $dI_{C}/dt$ during the turn-on transient are thereby derived based on the equivalent circuits. The temperature dependency on the turn-on characteristics of FS IGBT is identified by the experimental data. The temperature-dependent models of various device parameters are proposed to describe the temperature dependency. In the end, the double-pulse test is performed on a 650-V FS IGBT and a 1200-V FS IGBT. The good agreement between the test and analytically derived results validates that the proposed FS IGBT model can accurately predict the $dV_{CE}/dt$ and $dI_{C}/dt$ during the turn-on transient.

To solve the problem of a single light source, phase compensator, and detector, among others—which cannot meet the ellipsometry measurement requirements over a wide spectral range [from visible light (VIS) to short-wave infrared (SWIR) and even midinfrared (MIR; 400–3200 nm)]—a wide-spectrum thin-film ellipsometry measurement solution based on two parallel channels was proposed. Full spectral coverage was achieved through a combination of the VIS-SWIR (400–2100 nm) and SWIR-MIR (2100–3200 nm) dual-band ellipsometry—that is, the ellipsometry measurements in the VIS-SWIR and SWIR-MIR bands were integrated in the same system. Consequently, the ellipsometry parameters for full spectral coverage could be obtained using a single measurement. A SiO2 thin-film sample on a Si substrate of thickness 103.2 nm was used to evaluate the proposed ellipsometry system. The results showed that the thin-film thickness measurement accuracy was high (±0.5 nm in the range of 400–3200 nm), the thickness repeatability measurement accuracy was 0.03 nm, the refractive index repeatability measurement accuracy was 0.003, and the measurement time was approximately 0.5 s/ $\lambda $ , and the proposed system has the advantages of high integration, simple operation, and high measurement speeds.

Achieving the pathological type diagnosis of pulmonary nodules on chest CT is a critical step in the early detection of lung cancer and treatment of patients. Based on a small and unbalanced self-constructed dataset, we achieved intelligent diagnosis of five pathological types including adenocarcinoma, squamous cell carcinoma, small cell carcinoma, inflammatory and other benign diseases for the first time. In order to reduce the dependence of deep convolutional neural network (DCNN) on a large amount of training data, a reverse adversarial classification network (RACN) was proposed based on semi-supervised learning, which consists of a reverse generative adversarial network (RGAN) for unsupervised regression and a supervised classification network (CN). In RGAN, five specific normal distributions P with different means and variances were assigned to represent the five pathological types, and then a special regression task was designed by mapping pulmonary nodules to the random sampling Z of P. The input of generator in RGAN is set to 3D nodule volume data, the inputs of discriminator are set to Z and the output of generator. The regression task enables RGAN to extract specific features, which will be deeply integrate into CN to improve the classification performance. Experiments showed that the average sensitivity of RACN in detecting malignant nodules was 0.6525, where the sensitivity of adenocarcinoma, small cell carcinoma and squamous cell carcinoma was 0.8426, 0.5604 and 0.5543. Besides, the RACN can achieve 93.21% accuracy for diagnosing malignant nodules on the public LIDC-IDRI dataset, obtaining the state-of-the-art results.

To accurately diagnose pneumonia patients on a limited annotated chest X-ray image dataset, a prior knowledge-based active attention network (PKA2-Net1) was constructed. The PKA2-Net uses improved ResNet as the backbone network and consists of residual blocks, novel subject enhancement and background suppression (SEBS) blocks and candidate template generators, where template generators are designed to generate candidate templates for characterizing the importance of different spatial locations in feature maps. The core of PKA2-Net is SEBS block, which is proposed based on the prior knowledge that highlighting distinctive features and suppressing irrelevant features can improve the recognition effect. The purpose of SEBS block is to generate active attention features without any high-level features and enhance the ability of the model to localize lung lesions. In SEBS block, first, a series of candidate templates T with different spatial energy distributions are generated and the controllability of the energy distribution in T enables active attention features to maintain the continuity and integrity of the feature space distributions. Second, Top-n templates are selected from T according to certain learning rules, which are then operated by a convolution layer for generating supervision information that can guide the inputs of SEBS block to form active attention features. We evaluated the PKA2-Net on the binary classification problem of identifying pneumonia and healthy controls on a dataset containing 5856 chest X-ray images (ChestXRay2017), the results showed that our method can achieve 97.63% accuracy and 0.9872 sensitivity.

In this paper, the oxidation thermodynamics and oxidation kinetics of Au-20Sn solder at various temperatures were analyzed. The results indicated that the critical oxygen partial pressure to form SnO and SnO2in Au-20Sn solder could be 1 × 10−44 Pascal (Pa) and 1 × 10−91 Pa at the temperature of 298 K, respectively. The oxidation kinetics analysis results indicated that the oxide on the surface of Au-20Sn solder consists mainly SnO2, while the major constituent of internal oxide is SnO. The reliability test results under salt spray environment have showed that the hermeticity of the package device gradually decreased with the increasing oxygen content in Au-20Sn solder. Meanwhile, the measured leakage rate of the packaging device could be lowered than 5 × 10−9 Pa·m–3·s–1when the oxygen content in Au-20Sn solder is less than 28 ppm after high temperature aging.

Power electronics have been and will continue to be an enabling technology for energy production, storage, transmission, distribution, and consumption. Power electronic converters are usually the critical links in electrical energy systems, affecting system security, safety, energy efficiency, and cost-of-ownership. As a result, the reliability requirements for power electronic components and converter systems generally become more stringent, for example, in e-mobility, renewable energy generation, and power system applications. Testing is one of the vital reliability engineering tools to investigate failure mechanisms, identify weakest points, and demonstrate robustness margins. It contributes to reliability growth along the product development process and the likelihood of failure reduction in field operation. The required resources (i.e., testing time, sample size, and testing facility) and the relevance of the testing results to field operation are two crucial considerations in implementing a reliability test. This article introduces the emerging application-oriented testing concepts and facilities through several component-level and converter-level examples.

Dual-band electrochromic smart windows that can dynamically and independently control incident solar irradiation and visible light are envisioned as intelligent technology to reduce power consumption of buildings. However, there is still a great challenge to put the dual-band electrochromic technology into practice due to some limits in material systems and preparation techniques. Herein, a new electrochromic material of Li4Ti5O12is developed to implement the dual-band optical modulation behavior, which could be further improved by a precise control of the lithium content in the active material. It could separately modulate the light and heat based on regulation of the transmittance of visible and near-infrared light. This enables Li4Ti5O12to operate in three distinct modes of bright, cool, and dark, so as to meet various indoor needs. The optical transmittance contrast reaches over 60% at both visible- and near-infrared-light regions between different modes, and a large range of apparent temperature adjustments (7 °C) could be achieved. The prototype device based on dual-band electrochromic Li4Ti5O12is further developed into a smart window of a house model, which exhibits good optical and thermal modulation behaviors in response to a high-temperature environment. This work provides a new material system for achieving dual-band electrochromic optical modulation toward smart energy-saving window applications.

Developing highly efficient electrocatalysts for the CO2reduction reaction (CO2RR) has attracted increasing interest in the past decade. Herein, we report on the design and synthesis of Fe porphyrin 1with an appended N,N-di(2-picolyl)ethylenediamine (DPEN) unit that boosts electrocatalytic activity for CO2-to-CO conversion in acetonitrile with water as the proton source. By mimicking carbon monoxide dehydrogenase (CODH), 1has poly-pyridine/amine units located at the active site to form hydrogen-bonded water-containing networks that enable fast proton transfer. The protonated and positively charged DPEN unit can also stabilize CO2reduction intermediates through electrostatic and hydrogen-bonding interactions. These factors make 1a highly active electrocatalyst for the CO2RR by achieving a TOFmaxof 5.0 ​× ​104 ​s−1with water providing the protons. These critical roles of the DPEN unit in the CO2RR are further supported by theoretical studies. This work is significant to highlight the benefits of using molecular catalysts to elucidate structural effects.

Commercial 6061 Al alloy and SiCp reinforced 6092 Al matrix composite (AMC) were joined by friction-stir welding (FSW) with different tool offsets. Results show offsetting the pin to Al alloy side could significantly reduce tool wear, while maintaining ultimate tensile strength of the joint around 180 MPa. As tool offset increased from zero to 3 mm, pin and shoulder wear length reduced from 0.17 mm to almost zero and from 0.28 to 0.02 mm, respectively. The corresponding estimated maximum safe welding length increased from 568 to 3125 mm. Fe debris were generated from the steel pin by the sharp SiC particles, then transferred into the nugget zone, eventually formed Al8Fe2Si particles during the FSW process.

To solve the problems of whale optimization algorithm (WOA) with slow convergence speed, low accuracy, and poor global search ability, a multistrategy hybrid adaptive whale optimization algorithm (MHWOA) was proposed. In this algorithm, the logistic–tent hybrid chaos algorithm was used to initialize the population, which could make the population distribution more random and uniform. The opposition-based learning strategy was adopted to expand the population of individuals and complete the population selection. To balance the exploitation phase and exploration phase, a dynamic parameter was constructed based on the sigmoid excitation function, and an active adaptive weight was added to adjust the global and local search, which accelerated the convergence speed also. The perturbation mechanism of the Student T-distribution was introduced with random perturbation to expand the search range and improve the global search ability of the algorithm. In total, 23 benchmark functions were selected to conduct convergence performance and optimization performance experiments of the proposed algorithm. The average value and standard deviation were determined as evaluation indexes. The MHWOA was compared with other improved WOA variants and advanced algorithms. The results showed that the proposed MHWOA had better iterative convergence and optimization performance than different algorithms on the optimization of unimodal functions, multimodal functions, and fixed dimension functions. Meanwhile, the MHWOA was applied to the optimal designs of pressure vessels and springs. The experimental results displayed that the MHWOA obtained better solutions than other meta-heuristic algorithms. This study has practical solid application value, which can be applied to solving various engineering problems.Graphical Abstract

The effects of trace addition of Al2O3nanoparticles (NPs) on thermal reliabilities of Sn-0.5Ag-0.7Cu/Cu solder joints were investigated. Experimental results showed that trace addition of Al2O3NPs could increase the isotheraml aging (IA) and thermal cyclic (TC) lifetimes of Sn-0.5Ag-0.7Cu/Cu joint from 662 to 787 h, and from 1597 to 1824 cycles, respectively. Also, trace addition of Al2O3NPs could slow down the shear force reduction of solder joint during thermal services, which was attributed to the pinning effect of Al2O3NPs on hindering the growth of grains and interfacial intermetallic compounds (IMCs). Theoretically, the growth coefficients of interfacial IMCs in IA process were calculated to be decreased from 1.61×10-10to 0.79×10-10cm2/h in IA process, and from 0.92×10-10to 0.53×10-10cm2/h in TC process. This indicated that trace addition of Al2O3NPs can improve both IA and TC reliabilities of Sn-0.5Ag- 0.7Cu/Cu joint, and a little more obvious in IA reliability.

Rainfall infiltration is one of the most important driving factors of geological hazards, ecological environment problems, and engineering accidents. Understanding the principle of soil wetting during rainfall infiltration and its influence on soil mechanical properties is crucial for preventing geological hazards. In this study, micro-penetration tests coupled with moisture monitoring were performed to investigate the infiltration process during wetting through the measured change in mechanical characteristics. Results show that penetration resistance increases in the deep layer gradually. With increasing infiltration time, the wetting front keeps moving downward, and its range becomes wider. A slight increase of the penetration resistance in the shallow layer (d ≤ 17.5 mm) is observed. However, the penetration resistance in the middle layer (22.5 mm ≤ d ≤ 32.5 mm) decreases firstly before a slight increase. In the deep layer (d ≥ 37.5 mm), the penetration resistance decreases continuously during infiltration. Based on the measured water content profile during infiltration, it is found that the evolution of soil mechanical characteristics is fully responsible by the infiltration-induced re-distribution of water content along depth. Generally, the penetration resistance decreases exponentially with increasing water content in the soil. When the water content is low, wetting can weaken soil strength significantly, whereas this effect diminishes when the moisture surpasses a certain threshold. The results highlight that the penetration curves and water content profile show close inter-dependency and consistency, which verifies the feasibility of using micro-penetration to investigate rainfall infiltration and wetting process in surface soil layer or laboratory small-scale soil samples. This method enables fast, versatile and high-resolution measurements of infiltration process and moisture distribution in soil.

Anti-inflammatory drugs targeting inflammatory bowel disease (IBD) have attracted considerable attention but still face low therapeutic outcomes and frequent side effects. Astaxanthin (ATX), a natural ketone, possesses potent antioxidant and anti-inflammatory properties. However, it faces problems such as poor water solubility, photothermal instability, and low bioavailability. Here, we employed a supramolecular encapsulation strategy to create a nanoscale oral delivery system for ATX (referred to as FC-ATX NPs) by coupling fucoidan (FUC) with chitosan oligosaccharides (COS). The obtained FC-ATX NPs exhibited a particular “bean pod” structure with uniform size, good encapsulation efficiency, excellent physical and chemical stability, pH-triggered intestinal targeted slow-release properties, and potent antioxidant capacity. In vitrocell culture experiments showed that FC-ATX NPs promoted cellular uptake and scavenged excessive intracellular reactive oxygen species (ROS). In mouse models of colitis, FC-ATX NPs enhanced the drug absorption of intestinal epithelial cells and effectively accumulated at the site of inflammation. This work provides an efficient approach to enhance the bioavailability of ATX and has excellent application potential as an oral targeted delivery system for colitis therapy.

The kinetics of mass transfer in a stagnant fluid layer next to an interface govern numerous dynamic reactions in diffusional micro/nanopores, such as catalysis, fuel cells, and chemical separation. However, the effect of the interplay between stagnant liquid and flowing fluid on the micro/nanoscopic mass transfer dynamics remains poorly understood. Here, by using liquid cell transmission electron microscopy (TEM), we directly tracked microfluid unit migration at the nanoscale. By tracking the trajectories, an unexpected mass transfer phenomenon in which fluid units in the stagnant liquid layer migrated two orders faster during gas–liquid interface updating was identified. Molecular dynamics (MD) simulations indicated that the chemical potential difference between nanoscale liquid layers led to convective flow, which greatly enhanced mass transfer on the surface. Our study opens up a pathway toward research on mass transfer in the surface liquid layers at high spatial and temporal resolutions.

Nuclear factor E2-related factor 2 (Nrf2) is a transcription factor that functions as a master regulator of the cellular adaptive response to oxidative stress. Our previous studies showed that Nrf2 plays a critical role in adipogenesis by regulating expression of CCAAT/enhancer-binding protein β and peroxisome proliferator-activated receptor γ. To determine the role of Nrf2 in the development of obesity and associated metabolic disorders, the incidence of metabolic syndrome was assessed in whole-body or adipocyte-specific Nrf2-knockout mice on a leptin-deficient ob/ob background, a model with an extremely positive energy balance. On the ob/ob background, ablation of Nrf2, globally or specifically in adipocytes, led to reduced white adipose tissue (WAT) mass, but resulted in an even more severe metabolic syndrome with aggravated insulin resistance, hyperglycemia, and hypertriglyceridemia. Compared with wild-type mice, WAT of ob/ob mice expressed substantially higher levels of many genes related to antioxidant response, inflammation, adipogenesis, lipogenesis, glucose uptake, and lipid transport. Absence of Nrf2 in WAT resulted in reduced expression of most of these factors at mRNA or protein levels. Our findings support a novel role for Nrf2 in regulating adipose development and function, by which Nrf2 controls the capacity of WAT expansion and insulin sensitivity and maintains glucose and lipid homeostasis., White adipose tissue (WAT) is an active organ hat can store and release energy, maintain lipid and glucose homeostasis, and secrete variety of factors that influence appetite, insulin sensitivity, inflammation, [...]

It is of great challenge to develop the effective and stable sorbents for 99TcO4–sequestration from alkaline nuclear waste. In this work, we demonstrate a general strategy for the design of poly(ionic liquids)@COF composites, via in situpolymerization of imidazolium-based ionic liquids (ILs) encapsulated in the pores of covalent–organic frameworks (COFs). With regard to the polyILs@COF composites, the cross-linking polyILs endow the alkali-stable COF framework with numerous ionic fillers as the anion-exchange sites. Compared with the pristine COF, the optimized composite not only enhances the alkali resistance but also shows the excellent ReO4–(a surrogate of 99TcO4–) removal performances of fast exchange kinetics, high uptake capacity, superior selectivity, and good reusability, even in simulated high-level waste stream at the U.S. Savannah River Site (a typical alkaline nuclear waste). The alkaline stability and selectivity of the optimized composite can be further verified by the density functional theory (DFT) calculations, indicating its unique chemical recognition of TcO4–over other anions with higher charge density.

The ball valve is an important device in the pipeline transportation system of nuclear power plants. Its operational stability and safety directly affect the normal working of nuclear power plants. In this study, the transient numerical simulation of the opening and closing process of a ball valve was conducted on the basis of the flow interruption capability experiment of the ball valve by using the moving mesh method and inlet and outlet variable boundary conditions. The flow rate and pressure difference with time of the opening and closing process of the ball valve were studied. The internal flow characteristics of the ball valve under different relative openings were analyzed in conjunction with the typical back-step flow structure. Results show that the transient numerical results agree well with the experimental results. The internal flow characteristics of the ball valve are similar at the same opening during opening and closing process. At small opening, the spool and outlet channels easily form a back-step flow structure. The disappearance and generation of backflow vortices during opening and closing occur at 85% opening and 75% opening, respectively. With the decrease in opening degree, the difference in vortex core area in the flow channel of the ball valve spool in the opening and closing process gradually appears. The research results provide some reference value for the design and optimization of ball valves.