To investigate directional independence of multistage stress memory during progressive cyclic loading of granite under compression with a series of deflection angle, experiments were conducted on cyclic loading and unloading of granite with different deflection angles by using a self-made deflection device. The Kaiser effect (KE) and the incomplete erasion phenomenon (IEP) of the maximum stress in previous multistage cycles after progressive cyclic loading with deflection angles were explored in the experiments. Results show that both KE and IEP in granite exhibit directional independence. The directional independence of KE has a critical angle of 10° and the directional independence of IEP has a critical angle of 12°. With a deflection angle of 12°, the IEP will interfere with the memory of historical maximum stress by KE.

The process and mechanism of removing iron ions from manganese leaching solution by a combination of pyrite and air were explored. The results show that after iron removal by 1 hour of reaction at 25 ℃, with pH of solution at 2.5, addition of pyrite at an amount of 15 g/L, and air flow rate at 2.4 L/min, the left leaching solution has a mass concentration of residual iron ions less than 0.01 g/L, and the manganese recovery rate is higher than 99%. Pyrite as a reducing agent, in combination with air in the solution, creates an active reaction zone around pyrite with the coexistence of Fe³⁺/Fe²⁺ with oxygen, which contributes to the precipitation of iron ions in the form of goethite in the solution for removal.

The chemical composition, types and content of minerals, microregion quantitative energy spectrum analysis of titanium-bearing minerals, equilibrium estimate of TiO₂, occurrence state of titanium-bearing minerals, particle size and dissociation degree of ilmenite in a vanadium-titanium magnetite ore from Panxi region have been investigated. By these means, the reasons for difficulty in this ore dressing were ascertained. The technical index of ilmenite concentrate and the main mineralogical factors affecting the ilmenite dressing effect have been analyzed comprehensively, which may provide a detailed scientific basis for development and utilization of this vanadium-titanium magnetite ore in Panxi region.

Thermodynamic analysis was conducted with HSC Chemistry 9.0 software for removing arsenic by sulfuration from waste acidic solution left after copper electrolysis, and it is found that H₂S could effectively make asenous acid and arsenate in the high-concentrated sulfuric acid system precipitated by sulfuration. Based on the theoretical analysis results, an experiment on arsenic removal of waste acidic solution by sulfuration was carried out to investigate the effects of sulfurizing agent dosage and reaction time on the arsenic precipitation effect by sufuration. Results show that by 30 min-sulfuration with an addition of H₂S at 0.87 times the theoretical amount, the arsenic content in waste acidic solution after precipitation process falls down to 10.68 mg/L from 6 777.52 mg/L, and the removal rates of arsenic, copper and antimony are 99.84%, 99.76% and 99.33%, respectively. The iron and nickel therein are hardly precipitated, and the mass fraction of arsenic and sulfur in the residue of the arsenic removal process are 43.21% and 44.68%, among which the arsenic in the form of arsenic sulfide is in a mass fraction of 42.33%, and S/As in the arsenic sulfide is in a ratio of 2.29. The finally obtained product is a mixture of As₂S₃ and As₂S₅. It is shown that the thermodynamic analysis results differ slightly from the experimental results, but are still of guiding reference for experiments and practice.

A FeCoCrNiMn high-entropy alloy (HEA) coating was prepared on the 201 stainless steel surface by adopting high-speed laser cladding technology, and then the microstructure, phase distribution, microhardness of FeCoCrNiMn coating, as well as its wear properties in dry sliding condition were all investigated. It is found that such laser cladded FeCoCrNiMn HEA coating consists of a single FCC structure, with no obvious cracks observed. It also forms a good metallurgical bond with the substrate. The microhardness of the coating is around (439±2.1) HV, nearly two times that of 201 stainless steel substrate, and the strengthening mechanisms mainly include strengthening by grain refinement and solid solution strengthening. Also, the FeCoCrNiMn coating presents an obviously better wear resistance than 201 stainless steel, with an average friction factor of 0.246 and a specific wear rate of about 2.59×10^-6 mm³/(N·m). The wear mechanisms for it include adhesive and abrasive wear. It is concluded that such FeCoCrNiMn HEA coating prepared by high-speed laser cladding technology can significantly improve the surface hardness, wear resistance and service life of machine components.

The acid leaching solution of cathode materials from spent lithium iron phosphate batteries was taken as raw material, and iron, phosphorus and lithium elements therein were recovered by adopting an oxidation-precipitation process. The effects of factors, including endpoint pH value of reaction system, reaction temperature, concentration of sodium hydroxide, dripping rate of sodium hydroxide, and the volume ratio of hydrogen peroxide to acid leaching solution, on the precipitation rates of iron and phosphorus and the loss of lithium during the precipitation process were all investigated. Results show that with the endpoint pH value of 2.5, temperature of 75 ℃, sodium hydroxide with concentration of 1.5 mol/L, sodium hydroxide solution at a dripping rate of 7.7 mL/min, and hydrogen peroxide and acid leaching solution in a volume ratio of 1∶60, the average precipitation rates of iron and phosphorus are 99.86% and 98.23%, respectively, and the average loss of lithium is just 1.23%. Under the above-mentioned conditions, iron and phosphorus in the solution can be effectively removed and recycled in the form of iron phosphate, presenting a lower loss rate of lithium. After 5 h-heat treatment at 700 ℃, it is shown that the chemical composition of iron phosphate can meet the industrial standard.

According to the mineral properties of a kind of flake graphite ore in Heilongjiang Province, a new efficient flotation reagent was developed and then adopted in a flotation experiment. Results show that with the new reagent of CYM-11 as a collector, CYQ-01 as a foaming agent, an experiment with a closed-circuit flowsheet consisting of eight-stage regrinding and nine-stage cleaning can yield an graphite concentrate with fixed carbon content of 96.63% at 95.69% recovery, among which the graphite concentrate at a size of +0.15 mm can be produced with a yield of 11.38% and fixed carbon content of 96.04% in mass fraction. It is shown that the large flake graphite can be well protected during the course of mineral processing.

In order to effectively predict blast-induced rock fragmentation, a distribution of normalized rock fragmentation under different conditions was obtained by performing a designed experiment on drilling and blasting of a concrete specimen, and then the rock fragmentation exceeding 40 mm was selected for study. The correlation among variables under different testing conditions was analyzed by using Spearman correlation statistics, and the initial weights and thresholds of the BP neural network were optimized by using the ant colony optimization (ACO) to construct an ACO-BP model. The model was then trained with rock fragmentation by on-site blasting, and tested. Based on the comparison of such prediction mode with BP neural network model, random forest (RF) model and extreme gradient boosting (XGboost) model, it is found that the ACO-BP model is highly reliable in predicting blast-induced rock fragmentation, presenting a root mean square error of 0.13, an average absolute error of 0.11, and a coefficient of determination of 0.92. It is concluded that this model, with higher accuracy in prediction and applicability, can accurately predict blast-induced rock fragmentation.

In order to analyze mechanical properties of conveying hose during deep-sea mining operation, a mechanical model was established with Abaqus software for the buffer, flexible hose, and mining vehicle under different working conditions to analyze effects of buoyant ball position, buoyant force, ocean current velocity and volume fraction of conveyed mineral ores on hose configuration, as well as effect of forces that flexible hose exerts on the mining vehicle. When buoyant balls are put on the position far away from a mining vehicle, the hose is prone to be dragged on the seafloor；while being closer to a mining vehicle, the hose is prone to be entangled. It is shown that the closer to a mining vehicle, the greater the buoyant force and the greater the forces that the hose exerts on the mining vehicle. Furthermore, slower current velocity is more likely to bring greater impact to the hose configuration. The velocity of ocean current will influence the direction, magnitude and variation of the forces exerted on the mining vehicle. It is suggested that with ocean current at a velocity of 0.2 m/s, buoyant balls should be put on the position 12 m away from the buffer, with buoyant force selected at 1 500 N. In this case, the maximum horizontal and vertical tensile forces of the hose on the mining vehicle are 941 N and 1 258 N, respectively.

Copper ore sorting by dual-energy X-ray technique basded on traditional algorithms by curve fitting of T-value always results in great deviation. In view of this problem, a curve fitting of T-value by segmented straight lines was proposed. This method divides thickness into several segments, and performs a T-value curve fitting in each segment for copper ore sorting, which can more accurately reflect the changing trend of T-value with different thicknesses and also reduce impact of thickness on sorting. High-energy and low-energy rays are adopted to fit the T-value curve, and then the residual between the T-value and the curve-fitting mapping value is calculated in each segment, showing different residuals for different substances, which can be used to achieve copper ore sorting. In a verification experiment, two types of copper ores with different grades were sorted by this method. The ore images fitted with T-value curves by segmented straight lines were put into ResNet18 neural network for training, and the trained model was then used for testing. The test results show that an accuracy rate can reach 88.67%.