High-nitrogen stainless steels are widely used due to their excellent comprehensive performance. In this study, the effects of process parameters (laser power, scanning speed, and cavity pressure) on the formation of high-nitrogen stainless steels were studied by using conventional selective laser melting and high-pressure selective laser melting (HPSLM). The nitrogen content, nitrogen emission, phase composition, microstructure, and microhardness of the high-nitrogen stainless steel samples obtained through selective laser melting (SLM) were analysed by using an oxygen/nitrogen/hydrogen analyser, X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and electron backscatter diffraction. The results showed that the maximum nitrogen emission in the SLM sample was 0.175 wt.%, the emission rate reached up to 54.7%, and the maximum nitrogen content in the HPSLM sample was 1.07 wt.%. There was no significant difference between the phase peak positions of the SLM samples with different laser powers and the original powder. The main phase of the HPSLM sample changed at 0.3 MPa (from α-Fe to γ-Fe phase); the microstructure of the SLM sample was mainly composed of columnar and cellular crystals, and columnar crystal bands formed along the direction of heat flow. The HPSLM sample was mainly composed of equiaxed crystals with a grain size of 10–15 μm. At an energy density of 136 J/mm³, the microhardness and relative density reached their peak values of 409 HV and 98.85%, respectively.

The effects of powder formulation, including elemental mixed powder (EMP) and alloy mixed powder (AMP), and energy density on the nitrogen content and microstructural characteristics of high-nitrogen steel prepared by selective laser melting were investigated. The results reveal that the samples prepared with EMP had more nonfusion flaws and a relatively low density, with a maximum of only 92.36%, while samples prepared with AMP had fewer defects and a relative density of up to 97.21%. The nitrogen content and microstructural characteristics were significantly influenced by the laser energy density. The relative density of the EMP samples increased from 88.29% to 92.36% as the laser energy density increased from 83.3 J/mm³ to 125 J/mm³, while the relative density of the AMP samples rose from 93.31% to 97.21%, and the number of defects and the nitrogen content decreased. The mechanical properties of the AMP samples were superior to those of the EMP samples when the energy density rose, and the strength of the high-nitrogen steel first rose and then fell. The AMP samples showed the best mechanical properties when the energy density was 104.2 J/mm³, which corresponds to a laser power of 250 W, a scanning speed of 1000 mm/s, and a layer thickness of 30 μm. The corresponding values of yield strength, ultimate tensile strength, and elongation were 958.8 MPa, 1189.2 MPa, and 30.66%, respectively.

A water model was adopted to conduct an experimental study on the physical modeling of bubble behaviors and the effects of vessel pressure intensity, nozzle aperture diameter, bottom blowing location and bottom blowing flow rate on bubble properties were analyzed. Experimental results show that with the increase in vessel pressure intensity, the bubble breaking distance is shortened, the size is decreased, the number is increased, the degree of deformation in the rising process becomes smaller, and the fluctuation range of liquid level becomes small; in addition, the diameter of bubbles breaking away from the nozzle decreases. With the increase of bottom blowing aperture diameter, the average diameter of bubbles on the liquid level gets bigger and the number of bubbles decreases; moreover, the size of bubbles breaking away from the nozzle increases, their shape tends to be oval, and the time from bubble formation to bubble breaking is longer. With the increase of bottom blowing flow rate, the bubble breaking distance gets long, the size and number of bubbles increase, the bubble shape tends to be oval, and the impact force on the liquid level becomes larger. The greater the pressure intensity of the vessel, the closer the bottom blowing position is to the center, and the smaller the average diameter of bubbles.

The bandgap is a critical factor influencing the energy density of batteries and a key physical quantity that determines the semiconducting behavior of materials. To further improve the prediction accuracy of the bandgap in silicon oxide lithium-ion battery materials, a boosting machine learning model was established to predict the material’s bandgap. The optimal model, AdaBoost, was selected, and the SHapley Additive exPlanations (SHAP) method was used to quantitatively analyze the importance of different input features in relation to the model’s prediction accuracy. It was found that AdaBoost performed exceptionally well in terms of prediction accuracy, ranking as the best among five predictive models. Using the SHAP method to interpret the AdaBoost model, it was discovered that there is a significant positive correlation between the energy of the conduction band minimum (cbm) of silicon oxides and the bandgap, with the bandgap size showing an increasing trend as the cbm rises. Additionally, the study revealed a strong negative correlation between the Fermi level of silicon oxides and the bandgap, with the bandgap expanding as the Fermi level decreases. This research demonstrates that boosting-type machine learning models perform superiorly in predicting the bandgap of silicon oxide materials.

In the quest to produce high-strength steel, the preparation technology for vanadium–nitrogen alloy (VN) was refined through thermodynamic analysis, employing it as an additive to enhance the strength and hardness of microalloyed steel. Changes in the Gibbs free energies associated with the reactions between vanadium oxides and carbon in a nitrogen atmosphere were meticulously calculated and examined. This study explored the effects of the carbon to V₂O₅ ratio, the nitrogen to V₂O₅ ratio, and the pressure on the production of VN and CO at various temperatures. The results indicate that the productivity of VN is highest under conditions of approximately 1000 °C, a C:N₂:V₂O₅ ratio of 10:8:1, and a pressure of 1 bar. Under these conditions, VN constitutes approximately 70% of solid products, with a conversion rate of around 67.92%. CO accounts for approximately 38.17% of the exhaust gas, resulting in a yield of approximately 45.28%. The CO generated can be utilized as fuel in the production of iron in blast furnaces, providing an opportunity for secondary use of resources.

The paper is dedicated to analysis the inclusion behavior in steel using theoretical calculation and simulation of water. The aim is to establish collision and absorption model of inclusions on refractory. The article discusses the variation of critical stay speed and critical shear with the radius of inclusions in the process of colliding, rebounding and absorbing. The results show the critical stay speed and critical shear of alumina respectively surpasses 1 cm·s⁻¹and 1 N·m⁻², while titanium dioxide separately exceeds 4 cm·s⁻¹and 10 N·m⁻²for the inclusions that radius is less than 2.5 μm. If the inclusions occur rebound after colliding, the inclusions that radius is less than 7 μm will still be absorbed by the surface, while the inclusions that radius is more than 10 μm can easily reenter the steel. The model coincides with the water simulation results and it is of good adaptability.