On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst, the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively investigated. This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines. Results showed that the prevention and control of rockburst had made significant progress. However, with the increasing mining depth, several unresolved concerns remain challenging. From the in-depth research and analysis, it can be inferred that rockburst disasters involve three main problems, i.e., the induction factors are complicated, the mechanism is still unclear, and the accuracy of the monitoring equipment and multisource stereo monitoring technology is insufficient. The monitoring and warning standards of rockburst need to be further clarified and improved. Combined with the Internet of Things, cloud computing, and big data, a study of the trend of rockburst needs to be conducted. Furthermore, the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored. A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed. High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the development direction of rockburst in the future. This research will help experts and technicians adopt effective measures for controlling rockburst disasters.

Grain refinement can strengthen the mechanical properties of materials according to the classical Hall–Petch relationship but does not always result in better corrosion resistance. During the past few decades, various techniques have been dedicated to refining grain, along with relevant studies on corrosion behavior, including general corrosion, pitting corrosion, and stress corrosion cracking. However, the fundamental consensus on how grain size influences corrosion behavior has not been reached. This paper reviews existing literature on the beneficial and detrimental effects of grain refinement on corrosion behavior. Moreover, the effects of microstructural changes (i.e., grain boundary, dislocation, texture, residual stress, impurities, and second phase) resulting from grain refinement on corrosion behavior are discussed. The grain refinement not only has an impact on the corrosion performance, but also results in microstructural changes that have a non-negligible effect on corrosion behavior or even outweigh that of grain refinement. Grain size is not the only factor affecting the corrosion behavior of metallic materials; thus, the overall influence of microstructures on corrosion behavior should be understood.

The chemical binder is one of the critical factors affecting ore agglomeration behavior and leaching efficiency. In this study, we investigated the effect of the type of binder and mass fraction of the H₂SO₄ solution used on the curing, soaking, and leaching behavior of agglomerations. The results revealed that Portland cement (3CaO·SiO₂, 2CaO·SiO₂, and 3CaO·Al₂O₃) was the optimal binder for obtaining a well-shaped, stable agglomeration structure. A higher extraction rate was achieved when using Portland cement than that obtained using sodium silicate, gypsum, or acid-proof cement. An excessive geometric mean size is not conducive to obtaining well-shaped agglomerations and desirable porosity. Using computed tomography (CT) and MATLAB, the porosity of two-dimensional CT images in sample concentrations L1–L3 was observed to increase at least 4.5vol% after acid leaching. Ore agglomerations began to be heavily destroyed and even to disintegrate when the sulfuric acid solution concentration was higher than 30 g/L, which was caused by the excessive accumulation of reaction products and residuals.

Understanding bacterial adsorption and the evolution of biofilms on arsenopyrite with different surface structures is of great significance to clarifying the mechanism of microbe–mineral interfacial interactions and the production of acidic mine drainage impacting the environment. In this study, the attachment of Sulfobacillus thermosulfidooxidans cells and subsequent biofilm formation on arsenopyrite with different surface structures in the presence of dissolved As(Ⅲ) was studied. Arsenopyrite slices with a specific surface were obtained by electrochemical corrosion at 0.26 V. The scanning electronic microscopy-energy dispersion spectra analyses indicated that the arsenopyrite surface deficient in sulfur and iron obtained by electrochemical treatment was not favorable for the initial adsorption of bacteria, and the addition of As(Ⅲ) inhibited the adsorption of microbial cells. Epifluorescence microscopy showed that the number of cells attaching to the arsenopyrite surface increased with time; however, biofilm formation was delayed significantly when As(Ⅲ) was added.

In the ironmaking process, the addition of an organic binder to replace a portion of bentonite has the potential to improve the performance of pellets. The interaction between original bentonite (OB) and organic binder was investigated. Results indicated that the micromorphology of organic composite bentonite (OCB) became porous and the infrared difference spectrum exhibited a curved shape. In addition, the residual burning rates of OB and organic binder were determined to be 82.72% and 2.30%, respectively. Finally, the influence of OCB on the properties of pellets was investigated. The compressive strength of OCB-added green pellets (14.7 N per pellet) was better than that of OB-added pellets (10.3 N per pellet). Moreover, the range of melting temperature of OCB-added green pellets (173°C) was narrower than that of OB-added pellets (198°C). The compressive strength of OCB-added green pellets increased from 2156 to 3156 N per pellet with the increase in roasting temperature from 1200 to 1250°C.

CaO-containing carbon pellets (CCCP) were successfully prepared from well-mixed coking coal (CC) and calcium oxide (CaO) and roasted at different pyrolysis temperatures. The effects of temperature, pore distribution, and carbon structure on the compressive strength of CCCP was investigated in a pyrolysis furnace (350–750°C). The results showed that as the roasting temperature increased, the compressive strength also increased and furthermore, structural defects and imperfections in the carbon crystallites were gradually eliminated to form more organized char structures, thus forming high-ordered CC. Notably, the CCCP preheated at 750°C exhibited the highest compressive strength. A positive relationship between the compressive strength and pore-size homogeneity was established. A linear relationship between the compressive strength of the CCCP and the average stack height of CC was observed. Additionally, a four-stage caking mechanism was developed.

Semi-solid isothermal heat treatment was proposed to directly process cold-rolled ZL104 aluminum alloys and obtain semi-solid billets. The effects of two process parameters, namely, temperature and processing time, on the microstructure and hardness of the resulting billets were also experimentally examined. Average grain size (AGS) increased and the shape factor (SF) of the grain improved as the process temperature increased. The SF of the grain also increased with increasing processing time, and the AGS was augmented when the processing time was prolonged from 5 to 20 min at 570°C. The hardness of the aluminum alloy decreased because of the increase in AGS with increasing temperature and processing time. The optimal temperature and time for the preparation of semi-solid ZL104 aluminum alloys were 570°C and 5 min, respectively. Under optimal process parameters, the AGS, SF, and hardness of the resulting alloy were 35.88 µm, 0.81, and 55.24 MPa, respectively. The Lifshitz–Slyozov–Wagner relationship was analyzed to determine the coarsening rate constant at 570°C, and a rate constant of 1357.2 μm³/s was obtained.

A near eutectic Al−12.6Si alloy was developed with 0.0wt%, 2.0wt%, 4.0wt%, and 6.0wt% Al−5Ti−1B master alloy. The microstructural morphology, hardness, tensile strength, elongation, and fracture behaviour of the alloys were studied. The unmodified Al−12.6Si alloy has an irregular needle and plate-like eutectic silicon (E_Si) and coarse polygonal primary silicon (P_Si) particles in the matrix-like α-Al phase. The P_Si, E_Si, and α-Al morphology and volume fraction were changed due to the addition of the Al−5Ti−1B master alloy. The hardness, UTS, and elongation improved due to the microstructural modification. Nano-sized in-situ Al₃Ti particles and ex-situ TiB₂ particles caused the microstructural modification. The fracture images of the developed alloys exhibit a ductile and brittle mode of fracture at the same time. The Al−5Ti−1B modified alloys have a more ductile mode of fracture and more dimples compared to the unmodified alloy.

Thermal barrier coatings are widely used as surface modifications to enhance the surface properties of the material and protect from surface degradations such as erosion and corrosion. Ceramic-based coatings are highly recommended to increase wear resistance in the industrial sector. In this paper, an alumina–titania ceramic powder was deposited on an aluminum alloy using an atmospheric plasma spray technique. Experimental investigations were performed to study the behavior and erosion rate of the material. Solid particle erosion studies were performed by varying the particle velocity and particle flow rate. The angle impingement and stand-off distance were constant for comparison. The base metal has a clinging effect and the mass change was negative at a maximum particle flow rate of 4 g·min⁻¹. Under the same process conditions, the coated sample had a reduced lifetime and reached a maximum erosion rate of 0.052 (Δg/g). The solid particle erosion studies confirmed that the base metal aluminum alloy had severe surface damage with erodent reinforcement when compared to the coated samples. The influence of the particle velocity, particle flow rate, and input process parameters were also identified.

A facile one-step strategy involving the reaction of antimony chloride with thioacetamide at room temperature is successfully developed for the synthesis of strongly coupled amorphous Sb₂S₃ spheres and carbon nanotubes (CNTs). Benefiting from the unique amorphous structure and its strongly coupled effect with the conductive network of CNTs, this hybrid electrode (Sb₂S₃@CNTs) exhibits remarkable sodium and lithium storage properties with high capacity, good cyclability, and prominent rate capability. For sodium storage, a high capacity of 814 mAh·g⁻¹ at 50 mA·g⁻¹ is delivered by the electrode, and a capacity of 732 mAh·g⁻¹ can still be obtained after 110 cycles. Even up to 2000 mA·g⁻¹, a specific capacity of 584 mAh·g⁻¹ can be achieved. For lithium storage, the electrode exhibits high capacities of 1136 and 704 mAh·g⁻¹ at 100 and 2000 mA·g⁻¹, respectively. Moreover, the cell holds a capacity of 1104 mAh·g⁻¹ under 100 mA·g⁻¹ over 110 cycles. Simple preparation and remarkable electrochemical properties make the Sb₂S₃@CNTs electrode a promising anode for both sodium-ion (SIBs) and lithium-ion batteries (LIBs).

This study investigated the effects of adding graphene nanoplates (GNPs) and carbon nanotubes (CNTs) into the Al7075 matrix via the stir casting method on the microstructure and mechanical properties of the fabricated composites. By increasing the volume fraction of reinforcements, the fraction of porosity increased. The X-ray diffraction results showed that the addition of reinforcements into the Al7075 changed the dominant crystal orientation from (002) to (111). Field emission scanning electron microscopy images also showed the distribution of clustered reinforcements in the matrix. Between the two reinforcements, the addition of CNTs generated a lower fraction of porosities. Through the addition of 0.52vol% GNPs into the matrix, the hardness, ultimate tensile strength and uniform elongation increased by 44%, 32%, and 180%, respectively. Meanwhile, the presence of 0.71vol% CNTs in the matrix increased the hardness, tensile strength and uniform elongation by 108%, 129%, and 260%, respectively.

A series of novel steel–Ti(C,N) composites was fabricated by spark plasma sintering (SPS) and subsequent heat treatment. The hardness, indentation fracture resistance, and wear behaviour of the steel–Ti(C,N) composites were compared with those of the unreinforced samples, and their potentials were assessed by comparison with traditional cermet/hardmetal systems. The results showed that with the addition of 20wt% Ti(C,N), the wear rates of the newly examined composites reduced by a factor of about 2 to 4 and were comparable to those of cermets and hardmetals. The martensitic transformation of the steel matrix and the formation of in situ carbides induced by heat treatment enhanced the wear resistance. Although the presence of excessive in situ carbides improved the hardness, the low indentation fracture resistance (IFR) value resulted in brittle fracture, which in turn resulted in poor wear property. Moreover, the operative wear mechanisms were investigated. This study provides a practical and cost-effective approach to prepare steel–Ti(C,N) composites as potential wear-resistant materials.

Pt/CeO₂–C catalysts with CeO₂ pre-calcined at 300–600°C were synthesized by combining hydrothermal calcination and wet impregnation. The effects of the pre-calcined CeO₂ on the performance of Pt/CeO₂–C catalysts in methanol oxidation were investigated. The Pt/CeO₂–C catalysts with pre-calcined CeO₂ at 300–600°C showed an average particle size of 2.6–2.9 nm and exhibited better methanol electro-oxidation catalytic activity than the commercial Pt/C catalyst. In specific, the Pt/CeO₂–C catalysts with pre-calcined CeO₂ at 400°C displayed the highest electrochemical surface area value of 68.14 m²·g⁻¹ and I_f/I_b ratio (the ratio of the forward scanning peak current density (I_f) and the backward scanning peak current density (I_b)) of 1.26, which are considerably larger than those (53.23 m²·g⁻¹ and 0.79, respectively) of the commercial Pt/C catalyst, implying greatly enhanced CO tolerance.

To discuss the potential role of iridium (Ir) nanoparticles loaded under atmospheric and high pressures, we prepared a series of catalysts with the same active phase but different contents of 10wt%, 20wt%, and 30wt% on gamma-alumina for decomposition of hydrazine. Under atmospheric pressure, the performance of the catalyst was better when 30wt% of the Ir nanoparticles was used with chelating agent that had greater selectivity of approximately 27%. The increase in the reaction rate from 175 to 220 h⁻¹ at higher Ir loading (30wt%) was due to a good dispersion of high-number active phases rather than an agglomeration surface. As a satisfactory result of this investigation at high pressure, Ir catalysts with different weight percentages showed the same stability against crushing and activity with a characteristic velocity of approximately 1300 m/s.

Based on the characteristics of nonlinearity, multi-case, and multi-disturbance, it is difficult to establish an accurate parameter model on the hydraulic turbine system which is limited by the degree of fitting between parametric model and actual model, and the design of control algorithm has a certain degree of limitation. Aiming at the modeling and control problems of hydraulic turbine system, this paper proposes hydraulic turbine system identification and predictive control based on genetic algorithm-simulate anneal and back propagation neural network (GASA–BPNN), and the output value predicted by GASA–BPNN model is fed back to the nonlinear optimizer to output the control quantity. The results show that the output speed of the traditional control system increases greatly and the speed of regulation is slow, while the speed of GASA–BPNN predictive control system increases little and the regulation speed is obviously faster than that of the traditional control system. Compared with the output response of the traditional control of the hydraulic turbine governing system, the neural network predictive controller used in this paper has better effect and stronger robustness, solves the problem of poor generalization ability and identification accuracy of the turbine system under variable conditions, and achieves better control effect.