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Mercury is a metal with special physical and chemical properties. High pressure can significantly alter its crystal structures and interatomic interactions. However, vibration-related experimental data of mercury under high pressure have been scarce for a long time, which limits the in-depth understanding of its high-pressure phase transition mechanisms. To fill this research gap, this study systematically investigate the structural transformations and evolution of vibrational mode of mercury under high pressure. This was achieved by integrating low-wavenumber high-pressure confocal Raman spectroscopy,
MoSe2 is a promising candidate for tunable near-infrared photodetectors owing to its band gap alignment with optical fiber communication windows. We combine diamond anvil cell techniques with density functional theory calculations to investigate pressure-induced structural evolution and optoelectronic modulation in MoSe2. X-ray diffraction and Raman spectroscopy confirm that the hexagonal 2H phase remains stable up to 10 GPa, exhibiting pronounced anisotropic compression. The
The strontium tantalate Sr2Ta2O7 is a ceramic with an orthogonal
Lawsonite is a key hydrous mineral in subducting oceanic crust, with an H2O mass fraction of up to 11.5% and volume fractions that can reach 50%, and is stable over a wide pressure-temperature range. Constraining the high-pressure elastic properties of lawsonite is therefore essential for understanding seismic velocity structures in subduction zones and the deep-water cycle. In this study, dense polycrystalline lawsonite was synthesized by hot-pressing natural lawsonite powder at 7 GPa and 1 073 K for 2 h. Ultrasonic interferometry was then used to measure P- and S-wave velocities of lawsonite up to 8 GPa at room temperature, from which the elastic moduli and their pressure derivatives were determined. The results show that both elastic wave velocities and moduli increase with pressure, the adiabatic bulk modulus and shear modulus are 120(1) and 51(1) GPa at room temperature and ambient pressure, and their derivatives with respect to pressure are 5.7(1) and 0.9(1), respectively. Using these elastic properties, together with previous mineral-physics results, we constructed a lawsonite-bearing eclogite model, which indicates that the presence of lawsonite can provide a plausible explanation for the seismic velocity anomalies observed at depths of about 60–90 km within intermediate-temperature subducting slabs such as Nicaragua.
The geometric configuration of the corrugated Whipple protective structure significantly influences their protective capability against hypervelocity impact. To optimize the performance of the corrugated Whipple protective structures under hypervelocity impact, an integrated optimization method combining the finite element method-smoothed particle hydrodynamics (FEM-SPH) coupled algorithm with orthogonal experimental design was proposed. A reliable numerical simulation model was constructed, and the
The utilization of neural networks for the prediction of alloy properties and the inverse design of alloy microstructures has emerged as a novel approach in the industry for understanding material performance and developing new alloys. Texture acts as a critical factor influencing microstructural evolution during alloy deformation. It is typically characterized by spatially uncorrelated discrete grain orientation Euler angles, spatial-orientation coupled Euler angles within a representative volume element (RVE), or pole figures/inverse pole figures. However, identifying which texture representation method serves as the optimal input to maximize the performance of neural network models requires further investigation. Consequently, employing a modified U-Net model as the backbone architecture, this study evaluates and compares the impact of three texture representation methods, including discrete Euler angles, spatial Euler angles, and pole figures, as model inputs on the overall performance of the neural network. The three trained neural network models were individually deployed to predict samples within the test set. The results demonstrate that employing pole figures as the texture representation method yields the optimal performance. Furthermore, the trained neural network models were utilized to predict the macroscopic stress-strain curves of the alloys by incorporating a one-dimensional (1D) convolutional layer at the output stage. Compared to traditional methods relying solely on fully connected layers, this modification significantly enhances the prediction accuracy of the stress-strain curves.
In order to ensure the efficient recovery of copper resources, the copper-bearing albite rock samples were taken as the research object, and the impact loads with different strengths were applied by the split Hopkinson pressure bar (SHPB). The crack propagation process was recorded by a high-speed camera system, and the energy dissipation law of the samples under different impact pressures was analyzed by combining the one-dimensional stress wave propagation theory and the law of conservation of energy. At the same time, a numerical model of the impact process of copper-bearing albite is established based on the finite-discrete element coupling algorithm. The results show that the incident energy and the peak stress increase with the increase of the impact gas pressure, and the degree of sample breakage also increases. When the incident energy is less than 140 J, the energy dissipation rate increases with the increase of the incident energy. When the incident energy is greater than 140 J, the energy dissipation rate decreases with the increase of the incident energy, and the energy dissipation rate reaches the maximum when the impact gas pressure is 0.35 MPa. In the process of impact, tensile failure plays a dominant role and forms the main dominant area in the horizontal direction. The new crack area and the total impact energy increase with the increase of impact load. When the impact gas pressure is 0.30 MPa, the strain energy ratio is the smallest. Under this pressure, the proportion of shear cracks is the smallest, indicating that the rock breaking efficiency of 0.30 MPa impact gas pressure is the highest. The numerical model based on finite-discrete element method can effectively predict the damage and fracture process of copper-bearing albite under different impact loads.
To enhance the safety of the non-lethal kinetic energy ammunition used in the current 38 mm riot control guns, the finite element-discrete element method was employed to simulate the impact process of the 38 mm spherical kinetic energy projectile filled with lead sand on a human body-like target. The modeling method and parameter selection were indirectly verified through a rigid-wall experiment, and data on the deformation process, kinetic energy, velocity, displacement, and energy transfer rate during the projectile impacting on the target were obtained. Based on this, comparative analysis was conducted on different projectile velocities and wall thicknesses, and safety related shooting suggestions were proposed. The results show that the projectile undergoes significant deformation upon impact with the target, transforming into a disc like shape, while the target exhibits a circular indentation, with both deformations being partially recoverable to some extent. The wounding power of the projectile increases with velocity and decreases with wall thickness. The minimum safe shooting distances without causing abdominal skin penetration injuries for projectile wall thicknesses of 5, 7, and 9 mm are 122.40, 64.62, and 31.26 m, respectively.
At present, the trans-media weapon is one of research hotspot in the military field. Based on the Reynolds time-averaged Navier-Stokes (N-S) equation, volume of fluid (VOF) multiphase flow model and modified Realizable
To investigate the influence of cottonseed oil mass fraction on the rheological properties and anti-vibration performance of site-mixed emulsion explosive matrix, samples of site-mixed emulsion explosive matrix with different cottonseed oil mass fractions were prepared. A rotational rheometer, HY-5A rotary speed-regulating vibrator, and water dissolution method were used to study the rheological properties and anti-vibration performance of the site-mixed emulsion matrix. The results show that when the mass fraction of cottonseed oil is not more than 2.5%, the viscosity of the site-mixed emulsion matrix increases gradually. In terms of the temperature environment of the pipeline of on-site mixing trucks, the viscosity of the emulsion matrix can meet the pumping requirements. The elastic modulus and cohesion increase gradually and then remain nearly stable. The anti-vibration performance first increases and then decreases, and when the cottonseed oil mass fraction is 2.0%, the anti-vibration performance is the best.
To enhance the prediction accuracy of data-driven models in slope stability classification, this study proposes a hybrid intelligent model (WMA-SVM) that integrates a novel whale migration algorithm (WMA) with a support vector machine (SVM). First, a heterogeneous dataset of slope cases from diverse engineering backgrounds was constructed. To address its significant class imbalance, a combined strategy using the synthetic minority over-sampling technique (SMOTE) and the local outlier factor (LOF) algorithm was adopted to generate a high-quality balanced dataset. Subsequently, the WMA algorithm, which demonstrated superior optimization performance on eight benchmark test functions, was employed to optimize the hyperparameters of the SVM adaptively. Evaluation results show that the proposed WMA-SVM model significantly outperforms all benchmark models across various performance metrics. Moreover, based on the permutation feature importance (PFI) method, the unit weight, slope angle, and internal friction angle were identified as the most critical features influencing the classification outcomes for this dataset. Finally, the model’s generalization capability was further validated through eight independent engineering case studies, revealing a high consistency between the predictions and the actual stability states. This research provides a modeling framework with considerable generalization potential for the intelligent analysis of slope stability.
In order to improve the blasting contour accuracy and surrounding rockprotection under complex geological conditions, comparative experiments of protective blasting and protective notched-coupling blasting were conducted using a digital laser dynamic caustic experimental system and polymethyl methacrylate specimens. The crack propagation mechanisms and mechanical response characteristics of the two blasting modes were systematically investigated. The results show that in the protective notched-coupling blasting, the main crack propagates stably along the preset notched direction, demonstrating effective directional control. Meanwhile, the secondary peak value of the crack-tip stress intensity factor is significantly higher than that of the single protective blasting, indicating a stronger dynamic stress concentration effect. The notched-coupling blasting not only achieves a higher overall crack propagation velocity with slower attenuation at later stages, but also exhibits greater persistence and stability. In addition, this blasting mode effectively reduces the length and number of cracks on the protected wall side, thereby providing better rock-mass protection. The study reveals that the protective notched-coupling blasting optimizes crack propagation behavior and improves the directionality and energy utilization efficiency of blasting through the combined mechanisms of notch guidance and energy re-concentration. These findings provide theoretical support and technical guidance for precision blasting design and engineering applications in deep rock masses.
To further enhance the wave-cutting efficiency of bubble curtain, a series of field tests were conducted. These tests involved the use of single-tube and multi-row bubble holes, as well as high-speed photography to observe the morphology of the bubble curtain. Additionally, a numerical calculation model for the equivalent thickness of the bubble curtain was constructed using AUTODYN software. The results indicate that the number of bubble hole rows is a critical factor affecting wave-cutting efficiency under the same air flow rate. At a detonation center distance of 12.0 m, the wave-cutting efficiencies for 1, 2, and 3 rows of holes are 89.92%, 97.25%, and 96.41%, respectively. At different distances from the detonation center, the two-row hole bubble curtain demonstrated the highest wave-cutting efficiency, consistently exceeding 95%. The thickness and density of the bubble curtain are maximized for two rows of holes, and the thickness of the bubble curtain is the key factor determining wave-cutting efficiency. The equivalent thickness fitting formula established by combining experiments and simulations has high reliability, and the numerical simulations also exhibit high accuracy. To achieve convenient, efficient and low-cost wave-cutting efficiency, it is recommended that the single-tube two-row hole bubble curtain is applied in similar projects.
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- 2025 Symposium on Engineering Structure Safety and Protection (First Announcement)
- The 22nd Chinese Conference on High Pressure Science (Third Announcement)
- Notification for the Selection of the Fifth High-Pressure Science Outstanding Young Scholars
- Results of the 2024 Excellent Reviewer Selection for the Journal of High Pressure Physics
- Call for Papers for the Special Issue on Machine Learning and High-Throughput Research of Material Properties under Dynamic Loading
- Notice for the 2024 Shanghai Synchrotron Radiation Large Pressure Machine Experimental Technology Training Course
- Chinese Journal of High Pressure Physics will change from a bimonthly journal to a monthly journal starting in January 2025



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