With the continuous improvement of global technological levels and the increasing demand for high-performance alloy materials in national economic construction, the traditional single principal component alloy is increasingly unable to meet people’s increasing service needs. High-entropy alloys play an important role in aerospace, mechanical manufacturing, biomedicine, energy development and other engineering fields because of their unique physical, chemical and mechanical properties. Based on the concept of high-entropy alloys, the high-entropy effect, lattice distortion effect, sluggish diffusion effect and cocktail effect of high-entropy alloys are represented in this paper. The common preparation methods of high-entropy alloys are summarized according to the classification of melting-casting method, mechanical alloying method and coating method. The strength and toughness, wear resistance, corrosion resistance, high temperature resistance, fatigue resistance, radiation resistance and magnetic properties of the high-entropy alloys are discussed. The application prospect of high-entropy alloys is summarized, and the future research and development direction of high-entropy alloys are prospected on this basis.

With the constant progress in industrial technology, titanium alloy has been widely applied in fields such as aerospace, medical equipment, automotive manufacturing and ocean engineering because of its excellent performance due to its light weight and high strength. However, the shortcomings of titanium alloy, such as low hardness, poor wear resistance, and easy oxidation at high temperatures, limit its application range. Laser cladding technology, as an effective means of surface modification, greatly improves the surface properties of titanium alloy by preparing coatings with specific functions on the surface. In this paper, the research progress of laser cladding technology on the titanium alloy surface is reviewed, including the basic principle of laser cladding, process methods, selection of cladding materials, factors affecting the quality of the laser cladding layer and the development and application of functional coatings. Special attention is paid to the research status of wear-resistant coating, corrosion-resistant coating, high-temperature and oxidation-resistant coating and coating for biological applications, and the development trend and future research direction of laser cladding technology are discussed, in order to provide theoretical basis and technical support for the preparation of high-performance titanium alloy coating.

As a new type of alloy system composed of five or more principal components, high-entropy alloys demonstrate outstanding comprehensive performance in the field of friction and wear through the synergistic effects of the high-entropy effect, lattice distortion effect, hysteresis diffusion effect and cocktail effect. This paper systematically reviews the research progress on the friction and wear properties of high-entropy alloys. The mechanisms of metal elements such as Al, Ti, Cu and Nb through solid solution strengthening, second-phase precipitation and oxide film formation were analyzed emphatically. And non-metallic elements such as C, Si, and B form and strengthen the regulation laws of their tribological properties. The influence of working conditions, such as high temperature, ocean, and hydrogen peroxide on the friction and wear behavior of high-entropy alloys by altering the wear mechanism, was discussed. The influence of test conditions such as load, sliding velocity and friction pair matching on its friction coefficient and wear rate was expounded. It is pointed out that high-entropy alloys have significant application potential in key friction components, providing reference and guidance for the further development and application of high-entropy alloys.

Marine engineering equipment operates under extreme conditions such as high salinity, humidity, and flow velocity during marine resource exploration. These harsh environments impose strict requirements on surface performance, especially in terms of wear and corrosion resistance. Wear-resistant coatings are increasingly regarded as a crucial surface engineering approach to mitigate multi-mechanism degradation and improve the long-term reliability of marine equipment. In this review, the typical wear mechanisms in marine environments are systematically analyzed. Corresponding to different service scenarios, the main categories of coating materials, such as metal matrix composite coatings, cermet coatings, functionally graded coatings, and nanolayered coatings are summarized in terms of their structure and performance characteristics. Furthermore, mainstream fabrication techniques, including high-velocity oxy-fuel (HVOF), high-velocity air-fuel (HVAF), laser cladding, cold spray, and physical/chemical vapor deposition (PVD/CVD), are reviewed with respect to their influence on coating micro-structure and properties. Standardized evaluation methods for coating performance are also discussed. Finally, the current research challenges are identified, and future development trends are outlined, with an emphasis on multifunctional, intelligent, and environmentally friendly coating systems. This work aims to provide a systematic reference and theoretical basis for the design and application of wear-resistant coatings in marine environments.

With the advancement of industrial technology toward high speed, heavy load, precision, and automation, traditional sliding bearing materials have been unable to meet modern industrial demands. Surface coating technology, as an efficient surface modification method, has become a key means to enhance the tribological properties, wear resistance, corrosion resistance, and fatigue resistance of sliding bearings, thus extending their service life. This paper systematically reviews the research progress of coating technology for sliding bearings in the past, aiming to fill the gap in comprehensive summaries of multi-material systems and multi-process technologies in existing reviews. In terms of materials, it focuses on the performance characteristics and application scenarios of three major coating types—metal-based, ceramic-based, and polymer-based—clarifying their advantages and limitations. In terms of processes, it analyzes the technical characteristics of mainstream methods including electroplating, magnetron sputtering, and laser cladding, as well as their innovative applications in replacing traditional processes. Furthermore, this review summarizes the latest research results in coating performance evaluation, such as tribological testing via pin-on-disk testers and corrosion resistance analysis via salt spray tests. Finally, it discusses future development trends in new materials, new process applications, and environmental sustainability. This work is expected to provide a valuable reference for related research and engineering applications in the field of sliding bearing coatings.

Continuous casting is a key core link in steel production with characteristics of strong nonlinearity, multi-parameter coupling and dynamic fluctuations under working conditions. Traditional experience-dependent or mechanism-driven models are no longer suitable for the high-quality and high-efficiency production demands of modern steel industries. Machine learning provides an effective technical path for solving the complex control problems in the continuous casting process through its powerful data mining and pattern recognition capabilities. This paper systematically reviews the research progress of machine learning applications in the field of continuous casting, focusing on three core scenarios: abnormal prediction, quality defect detection and process parameter optimization. It sorts out the evolution from single models to feature optimization and integration, deep learning hybrid models, and mechanism-data dual-driven models. It summarizes the significant achievements of this technology in reducing production risks and improving the stability of cast billet quality, and it analyzes the prominent challenges currently faced such as data distortion and distribution imbalance, insufficient model interpretability and limited cross-scenario generalization ability. Finally, it looks forward to future technological innovation and application expansion directions, providing theoretical support and technical references for the digital and intelligent transformation of the steel industry.