The Fermi level pinning effect at the interface between two-dimensional transition metal dichalcogenides（TMDs） and metals severely limits carrier transport efficiency.Phase transition engineering in 2D TMDs offers a breakthrough strategy for improving metal-semiconductor contacts. This work elucidates the physical mechanisms of phase transitions, revealing that lattice symmetry breaking（2H→1T/1T） synergistically optimizes three critical functionalities by reconfiguring interfacial electronic states and atomic arrangements:（1） suppression of metal-induced gap states（MIGS）,（2） modulation of band alignment, and（3） construction of atomically smooth interfaces. Systematic strategies for phase transition control are explored, including charge doping, external field stimuli, and thermodynamic regulation. Atomic intercalation stabilizes metallic phases by tailoring orbital electron filling, while external fields（optical, electrical, or strain） trigger lattice reconstruction through energy-momentum coupling. Alloying and thermodynamic synthesis enable spatially controlled growth of heterophases via energy barrier engineering. These approaches establish multiscale correlations among electronic states, lattice ordering, and interfacial transport, providing theoretical foundations for high-efficiency contacts in lowdimensional devices. Future challenges lie in achieving atomic-scale resolution of dynamic phase transitions, enhancing heterophase interfacial stability, and developing cross-scale integration processes. Addressing these issues will require multidisciplinary efforts to advance 2D electronic devices from fundamental innovation toward high-density integrated circuits.

Regarding M2 high-speed steel continuous-cast billets,the carbide’s size,distribution,and morphology not only directly influence subsequent processes like rolling,but also exert a significant impact on the performance and quality of the final product.A thermal simulation test machine is utilized in this study for dendritic growth in continuous cast billets to explore the effect of pulse magneto-oscillation （PMO） solidification refinement technology on the carbide precipitation and growth process in M2 high-speed steel billets.The possibility and conditions for using PMO technology to improve the carbides in continuous cast M2 high-speed steel are also discussed.The thermal simulation results indicate that PMO can refine the solidification microstructure.Under peak current conditions of0,120,240,and 360 K_IA,the secondary dendrite arm spacing at the solidification end decreased by 3.08,3.83,and 6.91μm,respectively.At the same time,the macro-distribution of C,W,and Cr elements became more uniform.The thermal simulation quenching tests show that PMO technology can effectively reduce the area fraction of carbides and decrease the size of carbide network intersections.The lowest carbide area fraction was observed at360 K_IA,while the smallest carbide network intersection size was found at 240 K_IA.Thermodynamic calculations indicate that without PMO treatment,the solid-phase fraction of Mo₂C and W₂C precipitated at the solid-liquid interface was 0.921 and 0.972,respectively.With PMO treatment,the precipitated solid phase fractions of Mo₂C and W₂C at the solid-liquid interface reach 0.931 and 0.988 respectively,while the morphology of M₂C（M=Mo/W） transitions from lamellar to fibrous-like structure.On the one hand,PMO treatment refines the solidification microstructure and weakens element enrichment,and on the other hand,it lowers the carbide precipitation temperature.These two effects result in smaller carbides.

This study employed electrostatic spinning technology combined with solidphase separation to regulate the microstructure of a polyacrylonitrile（PAN） nanofiber basal membrane. Polymethylmethacrylate（PMMA） was added as a porogen. After amidoximation, a hierarchically porous nanofiber adsorption（PM-PAO-F） membrane was obtained for uranium（U） extraction from seawater. The adsorption kinetics, thermodynamics, and underlying mechanisms were subsequently investigated through a series of characterizations and experiments. The results showed that using PMMA as a porogen successfully generated secondary pores on the nanofiber surface. Consequently, the specific surface area of the PAN-based membrane increased from 8.87 to 22.94 m2/g, and the U（VI） adsorption capacity of the PAO adsorption membrane increased from 25.0 to 51.2 m~2/g under identical conditions. The adsorption kinetics and thermodynamic analyses revealed that the U（VI） adsorption by PM-PAO-F was endothermic. Fitting the experimental data to the Langmuir adsorption isotherm and the pseudo-second-order kinetic model indicated that the adsorption proceeds was uniform monolayer chemisorption. Moreover, the PM-PAO-F membrane retained 88% of its initial adsorption capacity after 12 cycles, highlighting its practical potential.

Ultra-high-molecular-weight polyethylene（UHMWPE） fibers have very low intermolecular forces, resulting in poor anti-creep performance and limiting their applications.Trimethylolpropane triacrylate（TMPTA） and a photo-initiator（Irgacure500） were introduced into UHMWPE fibers using solvent extraction modification. After a three-stage hot drawing, the fibers were irradiated with ultraviolet light to produce a cross-linking structure within the fibers, thereby improving the anti-creep performance of UHMWPE fibers.The results showed that the gel content of the UHMWPE fibers increased significantly after ultraviolet irradiation. With an increase in the mass fraction of TMPTA in the modified extracting solution, the gel content, melting point, anti-creep performance, and residual strength of the fibers after high-temperature treatment first increased and subsequently decreased; the crystallinity, degree of orientation, and mechanical properties decreased;and the thermal shrinkage resistance improved. Comprehensively, considering the mechanical properties, thermal performance, and anti-creep performance of cross-linking modified fibers, the optimal quality mass fraction of TMPTA in the modified extracting solution was2%, the anti-creep performance of resultant fibers was improved by 27.75% and 52.99%,respectively, after room temperature creep for 20 min under 30% breaking stress and 90 ℃creep for 20 min under 0.25 cN/dtex, and the strength remained at 90.3% after being treated at 150 ℃ for 30 minutes.

Dual-emission gel spheres（lanthanides（Ln）@carbon dots（CDs）@alginate（Alg）,Ln = Eu, Tb） were successfully prepared using a simple injection method, with Alg as the matrix and Ln and CDs as emission centers. Furthermore, their structures and luminescent properties were characterized. The results revealed that the Ln@CDs@Alg gel spheres emitted red and green fluorescence under ultraviolet（UV） excitation at 254 nm, and blue fluorescence under UV excitation at 365 nm. Based on this property, an array was developed that displayed blue fluorescence under UV excitation at 365 nm for information protection and revealed the encoded information “MY” in red and green fluorescence under UV excitation at 254 nm. The unique features demonstrated by the gel sphere array presented significant potential for applications in the field of anti-counterfeiting.

In this study, the effects of alloy composition, heat treatment temperature, and external loading on the α → γ phase transformation behavior in Fe-Cu-Mn-Ni alloys were systematically investigated. Using a phase-field modeling approach, the composition and structural distributions of both α and γ phases were examined and analyzed, represented by two sets of order parameters. The results indicate that a lower Cu concentration promotes the formation of α precipitates with Cu enrichment at the particle center, maintaining the same crystal structure as the parent α phase（i.e., the bcc structure）. In contrast, a higher Cu concentration favors the formation of γ precipitates, characterized by Cu enrichment at the particle edge and an fcc crystal structure. Moreover, the addition of small amounts of Mn and Ni to Fe-Cu alloys leads to the formation of precipitate phases with Mn/Ni compositional ring enrichment. Increasing the Mn and Ni content accelerates the phase transformation process, with Mn exhibiting a more pronounced effect than Ni. Furthermore, the α + γ dual-phase microstructure of Fe-based alloys can be regulated by adjusting the thermomechanical parameters and external loading. A lower aging temperature or a faster cooling rate results in earlier initiation of the phase transformation, as well as earlier Cu enrichment at the particle edges during precipitate growth. Additionally, increasing external loading promotes the formation of Cu-enriched γ phases. These findings provide theoretical support for optimizing the performance of Fe-Cu-Mn-Ni alloys and offer a reference for phase-field modeling studies on other multicomponent alloy systems.

A novel data-shifting method is proposed to address the shift-efficiency problem of the variable-length modified signed digit（MSD） adder used in a ternary optical computer（TOC）. Using this method, a corresponding distance-configurable shift register is designed. The new shifting method sets bypass paths for each register’s input and output lines, connecting them to different bit lines of the data bus. A 1-bit latch controls the electronic switch of each bypass, and the shifting distance can be adjusted by setting the latch, thereby enabling rapid shifting over specified positions. This method resolves the problem of low efficiency caused by the bit-by-bit shifting limitation of the current shift register, which uses a series of D flip-flops（DFFs）. This paper discusses the principles of the new shifting technology and implementation of the proposed shift register, providing six distance-configurable shift register examples. The shift registers in the examples are compared with traditional shift registers in an experimental analysis. The results demonstrate that the novel shifting technology significantly outperforms the traditional shifting technology in terms of clock frequency, shift latency, hardware resource utilization, and power consumption, markedly enhancing the performance of the MSD adder in TOC.

Reconstructing three-dimensional（3D） faces from monocular RGB images is a challenging computer-vision task. Owing to the dearth of datasets with facial-expression labels, most 3D facial reconstruction schemes lack the supervision of facial expressions,thus resulting in the inaccurate reconstruction of input facial expressions. Therefore, this study proposes a 3D facial reconstruction method based on emotional consistency. In this method, a loss of emotional perception consistency is introduced during training to selfsupervise facial emotions, thus enabling the reconstructed face to exhibit the same facial expression as the input face. Additionally, this study proposes a lightweight framework that uses MobileNetV2 to replace the deep network ResNet50 to regress face parameters and improve the inference speed of the model on the CPU side. Experimental results show that the proposed method can reconstruct a high-quality 3D face model based on a single-face image. The proposed method is superior to some mainstream face-reconstruction methods in terms of facial-expression capture and 3D face-reconstruction accuracies. Additionally,the lightweight face-reconstruction framework adopted in this study significantly improves the inference speed on the CPU side and expands the application prospects of the model in computing-resource-constrained scenarios.

The Yungang Grottoes, carved into sandstone strata, are culturally significant heritage sites. However, prolonged exposure to natural elements has led to considerable weathering. Focusing on the north wall of the Chanting Corridor in Cave 9,nondestructive testing was performed using a combination of microwave moisture measurement, microscopy, and X-ray fluorescence techniques. This study examines the spatiotemporal distribution of moisture, chemical properties of aqueous solutions, and characteristics of sandstone weathering on the walls. Considering environmental conditions,the study also discusses the deterioration mechanisms of sandstone resulting from waterrock interactions. The results showed that the moisture distribution on the wall exhibited spatial heterogeneity, with the lower regions being consistently more humid than the upper regions. Rainfall-induced fluctuations in the ambient relative humidity significantly affected the moisture content of the shallow sandstone layers, resulting in the formation of continuous water films and droplets on the surface. The weathered sandstone contained a high concentration of soluble salts, and the aqueous solution on the wall exhibited an alkaline nature. The primary chemical elements in the solution were Mg, S, Na, Ca, Cl,and K, with Mg and S concentrations being substantially higher than those of the other elements. Weathering pathologies were predominantly observed in powdery and flaky forms,characterized by porous and fractured microstructures, with color variations due to differences in material composition. Wetting-drying cycles and chemical dissolution emerged as key factors contributing to the weathering of the walls in the Chanting Corridor. These findings provide valuable data and a theoretical basis for both scientific understanding and preventive conservation efforts in similar stone cultural heritage sites.

A precast lap beam-column joint with a corbel and tenon configuration is proposed. A short beam equipped with a small corbel in the lower section was placed on the column surface to create a lap connection with the beam. Accordingly, the beam was designed with a section-reduced tenon in the upper section at the end of the lap connection. Mechanical sleeves were used to connect the reinforcement rebar between the beam and joint. To verify the bearing capacity and seismic performance of the proposed frame joint, quasi-static tests were performed on two 1/2-scaled frame joint specimens that were produced with a normal reinforcement concrete（RC） frame configuration and a special corbel-tenon configuration. The results showed that the failure of the corbeltenon specimen mainly occurred in the connection region and that its bearing capacity and energy dissipation capacity were better than those of the RC specimen, whereas its ductility was lower. Based on the experimental results, a finite element analysis was performed,and it achieved good agreement with the experimental results. Finally, a finite element parameter analysis of the lap beam-column joint with corbel and tenon configurations was performed. The analysis results show that the corbel size, corbel stirrup diameter, and column longitudinal reinforcement diameter have no significant effect on the hysteresis or skeleton curves of the joint. The bearing capacity of the joint decreases with a decrease in the diameter of the longitudinal reinforcement of the corbel, and the bearing capacity and initial stiffness of the joint increase significantly with an increase in the diameter of the beam longitudinal reinforcement.

As a critical technology in the aerospace field, estimating the relative position and attitude of satellite solar panels is crucial for successfully executing on-orbit satellite maintenance missions. However, under complex lighting conditions in space, nonuniform illumination and interference from repetitive edge textures complicate the accurate extraction of solar panel feature points, thereby impacting the precision of relative position and attitude estimation. Therefore, a method for estimating the relative positions and attitudes of satellite solar panels under complex lighting conditions through robust feature-point extraction was proposed. This method began by accurately segmenting the solar panel areas using a lightweight, multiscale edge-guided network. After preprocessing the segmentation results, the edges were fitted to straight lines, and the intersection points of these lines were calculated to efficiently extract the feature points of the solar panels.Based on this information, the relative position and attitude parameters of the solar panels were determined by matching point pairs based on adjacent frame data. Experimental results demonstrate that, under complex lighting conditions, as the camera dynamically approaches from a distance of 60 to 15 m, the proposed method effectively maintained the relative attitude error within 2° and reduced the relative position error from 0.38 to 0.04 m,highlighting its high precision and robustness.

To fully exploit the inherent correlation between light field epipolar plane images（EPI） and strengthen the effective capture of spatial information, this study proposed a dense light field decoupling reconstruction method based on multiscale EPI information fusion. This method utilized the spatial and epipolar plane dimensions to enable a better capture of the angular correlations between subaperture views. By decoupling and fusing multiple types of information, the accuracy and effectiveness of light field reconstruction could be enhanced. First, based on four-dimensional light field data, additional dense spatial dimensions were introduced to improve the generalization capability of the network and enhanced its understanding of local structures and texture details in images. Second, to better complement and enhance the mutual information among epipolar planes, an epipolar plane fusion module was designed along with a novel multiscale convolutional attention mechanism to integrate feature information. This attention mechanism effectively captured angular correlations through multiscale feature extraction and a global attention mechanism, thereby enhancing the expression of critical features while suppressing redundant content. Finally, experiments conducted on light field datasets, such as HCInew, HCIold,and Stanford, demonstrated that the proposed method outperformed existing state-of-theart（SOTA） approaches in terms of evaluation metrics including the peak signal-to-noise ratio（PSNR） and structural similarity（SSIM）. The proposed method achieved superior reconstruction performance in most test scenarios.

A deep feature fusion method was proposed for low-light images rain streak removal in digital twin applications. First, the dynamic line convolution（DLConv） was created to learn the prior knowledge of rain streaks, enhancing the ability to extract rain streak features to address the artifact problem. Second, by combining prior knowledge with the coordinate attention（CA） mechanism, the U-shaped model was improved to generate deep features of rain streaks, thereby addressing the issue of detail loss. Finally, the brightness information of the images was utilized to further refine and enhance the deep features and obtain rain-free images at the current stage, where the features of the rainfree images were fused between the stages, and multiscale features were transferred through cross-stage feature fusion, achieving rain streak removal for low-light images. Experimental results on the latest low-light rainy image dataset showed that the proposed method achieved peak signal-to-noise ratio（PSNR）、structural similarity（SSIM）、learned perceptual image patch similarity（LPIPS） and natural image quality evaluator（NIQE） values of 38.522 9 dB, 0.974 5, 0.061 9 and 4.207 2, respectively, outperforming existing mainstream methods. This demonstrated the effectiveness of the proposed approach in alleviating artifacts and detail loss, thereby significantly improving the usability of low-light images.

Although high-efficiency video coding（HEVC） can reduce bit rates by approximately 50% over its predecessor H.264, 35 prediction modes have been proposed to improve intra-prediction accuracy, resulting in a significant increase in computational complexity and a challenge for both software and hardware implementation. To address this issue, this study proposes a fast algorithm based on HEVC to determine the intra-prediction mode based on the image’s texture direction and correlation between the prediction modes. Experimental results show that this algorithm can save over 46% encoding time when the BD-rate loss is only 5.79% compared to the HEVC reference software HM16.20, which significantly reduces the complexity of the intra prediction mode decision and makes it easy to implement the algorithm landing on the end side with limited hardware resources such as embedded systems.