In order to promote the leaching of Ca and Mg elements in anorthite, a strain hzt-1′ with good adaptability to anorthite was screened from the soil of Jialiangshan, Fangshan County, Lvliang City, Shanxi Province. It was identified as Phyllobacterium myrsinacearum. The optimum growth conditions of the strain and the optimum leaching conditions of anorthite in Czapek Medium were investigated. The optimum growth conditions of strain hzt-1′ are as follows: pH of 6, liquid volume of 80 mL, inoculation volume of 7%, glucose as the best carbon source (20 g/L), and NaNO₃ as the best nitrogen source (1 g/L). The optimum leaching conditions of strain hzt-1′ are as follows: pH of 6, inoculation volume of 3%, pulp mass concentration of 20 g/L, and liquid volume of 100 mL. Under these conditions, the leaching rates of Ca²⁺ and Mg²⁺ in anorthite are 50.3% and 39.91%, respectively. The strain promotes the dissolution of anorthite through proton exchange and complexation, accelerates the leaching of Ca²⁺ and Mg²⁺, and thus improves the utilization rate of anorthite and other mineral resources. This study can provide a new strain for efficient leaching of silicate minerals.

In order to better monitor the filling morphology effect of goaf, a study on the characterization of grouting filling morphology effect with polarizability as the target was carried out based on resistivity parameters. Seven different kinds of cement were selected and prepared with five different contents of graphite powder. The variation of resistivity and polarizability of cement-based grouting filling materials was analyzed. The electrical characteristics and compressive strength of grouting filling materials under different cement types and ratios were studied, and the application test was carried out. The indoor test results indicate that with the increase of graphite powder conten, the compressive strength decreases, and the polarizability increases. When the ratio of cement to graphite is less than 10:1, the polarizability increases rapidly. In addition to sulphoaluminate cement, the content of graphite powder has little effect on the resistivity of cement-based grouting filling materials. Under the condition that the resistivity difference before and after grouting filling in goaf is not obvious, the visual characterization of filling morphology effect can be realized by polarizability (when the polarizability value of filling material is more than 3 times that of surrounding rock, the characterization effect is obvious). The research finding which is of great significance for broadening the field of grouting geophysical monitoring and improving the monitoring effect.

In order to investigate the microscopic structural characteristics and uniaxial damage evolution law of loess-slag-based cemented filling materials with different water-cement ratios, scanning electron microscopy and acoustic emission tests were conducted on the loess-slag-based cemented filling materials. Furthermore, PFC2D was used to investigate the crack evolution and particle damage characteristics of cemented filling materials with different water-cement ratios under uniaxial compression. The results show that when the water-cement ratio is small, the cemented filling material can generate more hydration products and the structure of the specimen is denser. The acoustic emission ringing count curves of cemented filling materials can be divided into compaction stage, linear-elastic deformation stage, crack constant-velocity expansion stage, crack sudden increase stage, and post-peak stage, and the ringing count characteristics are correlated with the strength characteristics. As the water-cement ratio increases, the cracking stress and damage stress during the compression process of the specimen gradually decrease, and the ratio of cracking stress to peak stress and damage stress to peak stress are not affected by the water-cement ratio. When the cemented filling material is damaged, shear cracks are the main type. As the water-cement ratio decreases, the number of cracks increases and the maximum value of the force chain increases. Changing the water-cement ratio has little effect on the spatial distribution of internal cracks and force chains in the specimens.

To reveal the energy consumption patterns of irregular ore particles under impact crushing, impact crushing tests were conducted on six types of iron ore with different properties, and the fractal characteristics of irregular iron ore fragmentation were analyzed, as well as the size effect on average particle size of fragments, fractal dimension, and unit absorption energy. Then, the energy consumption model of irregular single particle crushing was established. The results show that the average particle size of fragments, fractal dimension, unit absorption energy all exhibit a power function relationship with initial isosphere diameter under the same impact conditions. As the isosphere diameter of the particles increases, the average particle size of the fragments gradually increases, and the fractal dimension and unit absorption energy gradually decrease. There is an increasing relationship with power function between unit absorption energy and average particle size of fragments. The relationship between the logarithm of unit absorption energy and fractal dimension shows a linear increase. Through the method of ore crushing tests of irregular single ore particle, relationship models of unit crushing energy consumption of irregular iron ore particles changing with the initial size, average particle size of fragments, and fractal dimension were established, with an average correlation coefficient of 0.789, which effectively describes the energy consumption pattern of ore crushing.

In view of the limitations of existing technologies in the field of hydrometallurgy regarding green environmental protection, the application value and development potential of the glycine leaching system as a new type of green hydrometallurgical leaching technology were explored. By analyzing the unique physicochemical properties of glycine and its application advantages in the hydrometallurgy industry, the development history of the glycine hydrometallurgical leaching technology was reviewed, the research status and commercial dynamics of this technology in treating different types of mineral resources were sorted out, and the main existing problems of the technology were systematically summarized. The research results show that the glycine green hydrometallurgical leaching technology can expand the existing technologies in the metallurgical industry, and has the potential to replace the traditional cyanide gold extraction technology, especially in the field of rare and precious metals. Meanwhile, from aspects such as applicable fields, leaching efficiency of target metals, universality for secondary resources, and the mechanism of synergistic leaching systems, the development direction of the technology is clarified. The glycine green hydrometallurgical leaching technology has significant application value in the field of green hydrometallurgy, and can provide references for metal resource utilization, recovery of rare and precious resources, and secondary resource processing.

China's iron ore resources are increasingly depleted, and they have difficult to select characteristics such as poor, fine and miscellaneous. The traditional anionic collector has large dosage, complex reagent system and poor activity. In order to solve this problem, the surfactant processed by industrial waste amine (YTDB) was used as cationic collector to study the single mineral flotation test and mineral adsorption mechanism of quartz and hematite. The results show that when dodecylamine (DDA) is used as collector, under the conditions of pH=7 and collector dosage of 20 mg/L, the recovery rate of quartz is 78.36%, and the recovery rate of hematite is 12.57%. At this time, the flotation difference is the largest. When YTDB is used as collector, under the condition of pH=7 and collector dosage of 15 mg/L, the recovery rate of quartz is 91.27%, and the recovery rate of hematite is 12.67%. At this time, the flotation difference is the largest. YTDB is obviously better than DDA in flotation index, and saves the dosage of reagent to a certain extent. By testing the infrared spectrum, surface tension and Zeta potential before and after the interaction of the agent and the mineral, it is found that YTDB adsorbed on the surface of quartz.

Fiber-reinforced wet-mix shotcrete has excellent properties such as deformation resistance and crack resistance. To evaluate the support performance of fiber-reinforced wet-mix shotcrete, a series of tests were conducted, including uniaxial compressive tests, notched beam flexural toughness tests, and disk flexural tests. The test results indicate that, although the addition of fibers slightly reduces the compressive strength of wet-mix shotcrete, the flexural strength and energy absorption capacity have been significantly enhanced. The roadway support test results shows that the compressive strength of the steel fiber wet-mix shotcrete can reach 25 MPa, the thickness of the spray layer is maintained at 100−150 mm, with a minimal rebound and notable support effectiveness.

Aiming at the engineering problems such as insufficient crack detection accuracy and limited real-time performance in the complex geological environment of underground mine tunnels, an underground mine tunnel crack-segmentation network (UMTC-net) integrating multi-scale feature perception and adaptive attention mechanism was proposed. This network can realize cross-scale feature extraction of crack images from local texture to global structure through hierarchical cascading of Swin Transformer module groups. Meanwhile, a scaling cosine attention mechanism encoded by relative positions in logarithmic space was introduced to effectively suppress the interference of abnormal pixels. In addition, a codec framework based on dynamic patch merging/expansion was constructed, which solved the problems of ambiguous boundary positioning of fine cracks and high false detection rate in complex backgrounds in traditional methods. The results show that the UMTC-net has an accuracy of 85.15%, an average intersection-union ratio of 85.78%, and an F₁ value of 83.27% in the Crack 500 dataset, and an accuracy of 87.51%, an average intersection-union ratio of 79.98%, and an F₁ value of 86.95% in the MineTunnelCrack-2000 dataset. It exhibits stronger robustness, especially in low light and high dust environments. This network achieves an inference speed of 38.9 ms on the RTX 3060 mobile graphics card, occupying only 5 230 MB of memory and reducing deployment costs by more than 40%. It meets the real-time and low-power requirements of portable detection devices, and has a higher cost-effectiveness for adaptation. In the field test, the detection efficiency of UMTC-net is 8 times higher than that of manual inspection, and the missed detection rate is reduced from 18% to 3.2%. The research results provide an efficient and accurate new scheme for crack detection in underground mine tunnels, which is helpful to find potential safety hazards in time and ensure the safety of mine production and stable operation of equipment.

The existing object detection algorithms for shaking table concentrate bands have problems such as inability to balance detection accuracy and speed, high computational costs, difficulty in compressing model size, and slow inference speed. To address these problems, a lightweight fusion network for shaking tables (YC-Lightweight Net) object detection algorithm was proposed. The YC-Lightweight Net model firstly used a repetitive visual transformation network to extract features from the images of shaking table sub-banding. Then, by introducing group space convolution, multi-scale efficient cross stage fusion modules, and using skip connections, an efficient and lightweight neck network was designed. Finally, a weight based layer adaptive pruning algorithm was used to compress the model size. The experimental results show that the accuracy, recall, mean average precision, and FPS indicators of the YC-Lightweight Net model are 98.4%, 97.9%, 98.8% and 333 frame/s, respectively. The detection accuracy and speed are significantly better than those of the compared models. The number of parameters, floating-point operations, and model size after pruning are 13.9%, 15.4% and 17.5% of the original model, respectively. The pruning operation greatly reduces the computational complexity and model size of the model. The YC-Lightweight Net model has good detection accuracy and real-time performance, meeting the requirements of industrial equipment for lightweight models in shaking table mineral processing plants. The study can provide a technical support for accurate identification of separation points in mineral bands and intelligent upgrading of the shaking table mineral processing plant equipment.

As an environmentally friendly material, gold-tailings-based concrete has a wide range of potential applications. However, the complexity of the material composition of gold-tailings-based concrete, traditional prediction methods of compressive strength are often difficult to capture the nonlinear correlation and multivariate coupling characteristics within the material, resulting in insufficient prediction accuracy. Thus, a strength prediction model for gold-tailings-based concrete was proposed based on a deep learning binary fusion model (DP), a fusion Convolutional Neural Network (CNN) and a Gated Recurrent Unit (GRU). Firstly, the mineral, chemical composition and particle size distribution of gold tailings were analyzed, and their leaching toxicity was tested according to relevant standards to ensure their safety and stability as concrete materials. Subsequently, the gold tailings concrete dataset was constructed through experiments and applied to the training and validation of the model. In order to further verify the predictive ability of the model, it was applied to real engineering cases. The results show that the proposed model exhibits high accuracy in both the training and testing process, and is capable of effectively predicting the compressive strength of the gold-tailings-based concrete. The actual engineering cases show that the error range between the predicted and measured compressive strength of concrete with 20%−40% gold tailings is −4.1%−5.7%, which further proves the potential of the model to be applied in engineering practice.