This paper explores the application and development trends of artificial intelligence (AI) technology, particularly machine learning and natural language processing in the field of failure analysis. Failure analysis is a crucial method for ensuring the reliability and safety of equipment, and is widely used in aerospace, automotive manufacturing, electronic devices, and other fields. Traditional failure analysis methods often rely on expert experience, which is time-consuming and laborious. By integrating AI’s powerful data processing capabilities with traditional methods, the accuracy and efficiency of analysis have been significantly enhanced. In terms of failure mode diagnosis, AI can rapidly and accurately identify various fault modes and provide precise diagnostic results. In failure cause diagnosis, AI integrates data from multiple sources to uncover complex failure factors and potential causal relationships, improving diagnostic reliability. In failure prediction, machine learning can accurately forecast material lifespan and strength, reducing experimental time and costs. In failure prevention, AI offers new approaches to effectively reduce the risk of failure and lower product maintenance costs. The paper also looks forward the future development prospects of AI in failure analysis and highlights challenges and recommendations in the areas, such as data quality improvement, model optimization, interdisciplinary collaboration, and ethical and safety issues.

The manufacturing process of composites is crucial for ensuring structural efficiency and application reliability of their products. Computer-based process simulation plays a significant role in improving the manufacturing quality of composite components and reducing the manufacturing cost. Traditional process simulation relies on physical and chemical mechanisms in manufacturing of composites with the mathematical equations solved by numerical methods such as finite element/finite volume analysis and computer-aided design methods e.g. computer graphics. At present, it has been widely used in simulations of the lay-up of reinforcements/prepregs, the infiltration flows of resin, the curing behaviours of thermosetting resin, the heat transmission and exchange, and the nonlinear mechanics including residual stress and curing deformation predictions. Recently, artificial intelligence（AI）technologies have rapidly developed, its technical basis machine learning（ML）, in combination with artificial neural networks（ANN）, has been used in the field of lay-up process of fiber reinforcements, liquid molding processes, and autoclave processes, which aimed for data mining and developing reduced-order models. The former can establish relationships between process conditions and the curing quality or mechanical properties of the composite parts, while the latter can improve computational efficiency of the process simulation. However, due to the complexity, immeasurability, and high cost of manufacturing fiber-reinforced resin matrix composites, at the beginning of the AI age, it is difficult to meet the requirements of ML only by relying on the amount of data obtained by experiments. Also, data-driven AI technology faces uncertain issues regarding the representativeness, generalisability, and interpretability of the models. Therefore, traditional process simulation based on physicochemical mechanisms can provide a large amount of reliable data for data-driven ML simulation, and then through AI, more quantitative models describing the composite process can be established to expand the computable scope of process simulation. At the same time, as AI technology enhances the computational efficiency, the process simulation that meets real-time requirements can evolve into digital twins（DT）of the composite manufacturing process, which can provide new technical support for reducing the composite costs and improving the scientific whole-life cycle management.

Rare earth permanent magnet materials are widely applied in critical fields such as aerospace, energy technology, and transportation, serving as critical materials in modern technology. The 1∶12-type（ThMn₁₂）SmFe permanent magnet material exhibits magnetic properties comparable to Nd₂Fe₁₄B and possesses a higher Curie temperature. It exhibits the highest theoretical magnetic energy product among permanent magnets. Moreover, it consists of abundant elements, showing significant potential for application. However, this material faces challenges in thermal stability, leading to low coercivity, thus hindering its potential. This paper first analyzed the reasons for the poor thermal stability of the 1∶12 phase, concluding the influence of elements occupying different crystallographic sites on phase stability and intrinsic magnetic properties. Subsequently, we analyzed the key factors affecting the coercivity, elucidating the inherent relationship between preparation processes and coercivity. Finally, we proposed strategies for achieving high magnetic energy products in 1∶12 type SmFe permanent magnets, such as multi-site element Co-doping, control of cooling rate, and grain boundary encapsulation, providing important references for developing rare earth permanent magnets.

The aircraft engine is considered the “heart” of the aircraft. The development of advanced aircraft engines focuses on achieving a high thrust-to-weight ratio, high efficiency, low fuel consumption, and extended operational life. High-temperature functional coatings, such as thermal barrier coatings（TBCs）, thermal/environmental barrier composite coatings（T/EBCs）, and high-temperature stealth coatings, are applied to critical hot-end components of aircraft engines. These coatings play a significant role in enhancing the service performance, operational life, safety and reliability of the engine. Taking TBCs, T/EBCs, and high-temperature stealth coatings as examples, this paper provides a systematic overview of recent research progress in the design of high-temperature functional coating materials, coating preparation science and technology, and coating performance evaluation and characterization, both domestically and internationally, with a specific focus on the advancements made at Beihang University. Furthermore, challenges and development trends faced by new high-temperature functional coatings of advanced aircraft engines in the future are also discussed. In the future, the research focus of advanced high-temperature functional coatings will shift toward multifunctional composite coatings, enhanced adaptability to extreme environments, and improved process compatibility.

As the turbine inlet temperatures of aero engines continue to rise, there is an urgent need to develop a new generation of single-crystal superalloys and their thermal protective coatings for turbine blades. In order to meet the stringent requirements for the comprehensive performance of high-temperature structural materials in the complex service environments of aero engines, the intelligent design research of single crystal superalloys and thermal protection coatings has been gradually carried out at home and abroad in recent years under the promotion of material integrated computational engineering and material informatics. This paper reviews the latest research progress in the design of novel single-crystal superalloys and thermal protective coatings by utilizing multi-scale computational simulations and machine learning methods. The findings confirm that multi-scale computational simulations offer robust theoretical support for understanding the strengthening and toughening mechanisms of single-crystal superalloys, as well as the oxidation resistance and diffusion protective mechanisms of thermal protective coatings. Additionally, the study highlights the reliability and significant potential of machine learning in constructing intrinsic "composition-structure-property" relationship for high-temperature structural materials. This approach paves an intelligent and efficient new pathway for the rapid development of next-generation high-temperature single-crystal superalloys and thermal protective coatings.

With the global energy transition and increasing environmental requirements, hydrogen-mixed gas turbines as a high-efficiency and low-emission energy conversion equipment has been widely concerned. This paper reviews the development status of hydrogen-mixed gas turbines domestically and internationally, analyzes the characteristics of hydrogen combustion in gas turbines, explores the impact of hydrogen combustion on complex components and the application of high-temperature materials, and analyzes the performance requirements for hot-end component materials operating under high temperature, high pressure, and corrosive conditions, as well as the main challenges and potential solutions in current material development. The effects of water vapor and hydrogen embrittlement during hydrogen combustion on gas turbine alloys and thermal barrier coatings are discussed in detail.Water vapor accelerates the oxidation and corrosion of alloys, leading to a decline in mechanical properties. Furthermore, hydrogen embrittlement significantly affects the toughness and durability of alloys, increasing the risk of crack propagation and fracture. In terms of the problems, future research should focus on multi-field coupling simulations and accelerated corrosion tests, considering the factors such as temperature, pressure, and different atmospheres to establish realistic environment simulators to evaluate alloy and coating performances. Additionally, the combined effects of hydrogen and water vapor on high-temperature alloys and thermal barrier coatings should be emphasized. This includes investigating the diffusion mechanisms of hydrogen in alloys, interactions with lattice defects, and the microscopic processes leading to hydrogen embrittlement. Building oxidation models in high-temperature water vapor environments, clarifying the dissociation and adsorption mechanisms of water vapor at high temperatures, the hydroxylation of protective oxide films Al₂O₃ and Cr₂O₃, and the growth behavior of non-protective oxides（e.g., spinel） are also essential.

The thin-wall effect of single crystal superalloys refers to the phenomenon that when the thickness of the sample and the part is less than 1 mm, the lasting life is reduced, the creep rate is increased and other mechanical properties are significantly attenuated. With the development of the internal cooling structure of advanced aero-engine single crystal blade parts, the structural thickness of some areas decreases, making it a typical thin-walled structure. Thus, it is of great engineering significance to consider the thin-wall effect in the thin-wall region during the design and manufacture of blades. Creep performance is one of the most important properties of superalloys for turbine blade application. This paper summarizes the thin-wall effect in creep performance of the superalloys as well as some advanced experimental equipment in the study of thin-wall effect. Research on thin-wall debit effect of superalloys can be divided into two categories, one is the cause of thin-wall debit, including the relative enhancement of oxidation, more significance in anisotropy, changes in microstructure and the initiation or growth of defects, and the factors that influence the thin-wall debit effect including experimental conditions（temperature, stress, etc.）, the processing methods（casting, machining）, geometric shape （rectangular cross-section, ring cross-section, film cooling holes）. Research on thin-wall debit effect is within the scope of engineering application, as a part of “component level/analog component level” in “building block” verification and evaluation technology, thin-wall debit effect research under service environment or near-service environment conditions is more valuable for application. For this purpose, a variety of advanced experimental equipment platforms have been developed to simulate one or several coupled service conditions（high temperature, high pressure, corrosion/erosion, centrifugal loading） of the blade in the engine. Future research on thin-wall effects should be carried out under conditions closer to actual service conditions by preparing specimens according to the actual blade manufacturing process and conducting experiments on the equipment that simulates the service environment.

Thermoelectric materials can efficiently and cleanly convert between electrical and thermal energy, offering significant prospects in waste heat recovery and electronic cooling applications. Lead telluride（PbTe）materials were used in thermoelectric power sources for deep space exploration. Lead selenide（PbSe）, a homologue of PbTe, shows potential as a more abundant and cost-effective alternative for mid-temperature thermoelectric power generation. Recently, research in PbSe thermoelectric has shifted from mid-temperature power generation to near-room-temperature cooling, driven by the growing demand for Te-free thermoelectric cooling materials and devices. This paper reviewed the typical optimization strategies used in the research of p-type PbSe, summarized the key research progress in thermoelectric devices based on this material, and highlighted its significant development prospects. Finally, we provide a personal outlook on developing the near-room-temperature thermoelectric performance of p-type PbSe materials and manufacturing high-performance cooling devices, which includes integrating various optimization strategies, optimizing device assembly techniques, identifying suitable contact materials, and developing Te-free thermoelectric devices based on PbSe, with the goal of advancing their application in critical fields such as deep space exploration and laser cooling.

Main-shaft bearings are vital safety components in aeroengines made of bearing steels with outstanding combinational properties. The material is supposed to exhibit high surface hardness, high fracture toughness, high temperature resistance, fatigue resistance and corrosion resistance. However, under harsh operation conditions bearing steels are prone to rolling contact fatigue（RCF）that leads to bearing failure, severely endangering flight. Therefore, accurately predicting the RCF lives of bearing steels is key to the reliability of aeroengine. This manuscript reviews important results and progress in the RCF and life prediction of aeroengine bearing steels and suggests future research directions. Firstly, special stress state as a result of the Hertzian contact between rolling element and raceway is introduced, where shear stress components peak at the subsurface.This explains the origin of complexsubsurface-originated RCF mechanisms in bearing steels and indicates subsurface-originated RCF to be an important failure mode of bearing steels under ideal conditions. Meanwhile, with increasing contact pressure, the response of material evolves from elastic mode to plastic mode. Besides, due to the harsh service environment of aero-engine bearings, surface-originated also takes place and hence the competition between these two mechanisms is present. Next, three methodologies for RCF life prediction are summarized, being probabilistic models, mechanistic models and numerical models, with their advantages and limitations analyzed. Probabilistic models are well developed and widely employed by industry, but they are in nature a kind of statistical models without accounting for RCF mechanisms and are hence lacking scientificity; Deterministic models predict RCF life via describing physical processes, which are rich in science but poor in accuracy due to their simplification; numerical models balancing both engineering practice and scientific characteristic is a powerful tool to tackle the problem of RCF life prediction, although their accuracy requires further improvement. Finally, it is suggested that future research may focus on solving key scientific problems in RCF, modifying life prediction models via inserting RCF mechanisms and applying artificial intelligence in RCF life prediction.

High-strength aluminum alloys have been widely used in aviation, aerospace and other industries because of their high specific strength and good machining property. Corrosion is an important factor affecting the safety and stability of high-strength aluminum alloys in service. Based on the preparation process of high-strength aluminum alloys, this paper focuses on the effect of structural evolution caused by heat treatment on the corrosion property of high-strength aluminum alloys. The corresponding relationship between the microstructure and corrosion behavior of high-strength aluminum alloys is analyzed. Research directions for improving the corrosion property of high-strength aluminum alloys are proposed. The segregation of elements and phases in high-strength aluminum alloys can easily lead to electrochemical inhomogeneity of microstructure, causing corrosion of substrate. Therefore, based on the optimization of composition, the melt casting process, deformation process and heat treatment process of high-strength aluminum alloys should be regulated to prepare the microstructure with uniform distribution of elements and second phases, and uniform electrochemical property, which is crucial for improving the corrosion property of high-strength aluminum alloys. In addition, the corrosion sensitivity of alloys is affected by the width of the precipitate free zone and the distance and distribution of the grain boundary precipitation phases of alloy. Thoroughly studying and clarifying the effect of various structures such as precipitate free zone on the corrosion behavior of alloys is the prerequisite for the preparation of high-strength aluminum alloys with high corrosion property. To balance the mechanical property and corrosion property of high-strength aluminum alloys, heat treatment methods such as aging and thermomechanical treatment should be optimized, and new composite heat treatment methods should be developed. Meanwhile, the test methods and evaluation methods for the corrosion property of high-strength aluminum alloys are discussed. In order to more efficiently and accurately evaluate the corrosion property and service safety of high-strength aluminum alloys, further research work should be carried out in the combined use of traditional evaluation methods with modern data processing technologies such as digital twin, virtual simulation and machine learning.

High-entropy alloys（HEAs）have attracted considerable attention from the research community as a pioneering alloy design paradigm over the past two decades. They have fundamentally challenged traditional design paradigms and exhibited exceptional mechanical properties and functional characteristics, thereby positioning themselves as promising candidates for significant engineering applications in the future. Recent advancements have unveiled several alloy systems that demonstrate exceptional performance across diverse metrics, including low-temperature fracture toughness, high-temperature strength, impact resistance, radiation tolerance, and fatigue resistance. These qualities render HEAs highly attractive materials for research with substantial application potential in critical domains such as deep space exploration, deep-sea investigations, low-temperature superconductivity, and advanced nuclear energy technologies. This paper will briefly introduce the concept and classification of HEAs, and review the experimental progress of HEAs under various extreme conditions such as extremely low temperatures, high-speed impacts, and high nuclear radiation. We also summarize the strategies for enhancing the strength and toughness of HEAs, and extract the deformation mechanisms and physical and chemical properties of HEAs under different extreme loads. It is foreseeable that the main development direction of HEAs will be to form microscopic fluctuations in chemical composition and construct multi-scalestructural ordering efficiently through fine adjustment of the selection and proportion of alloying elements and optimization of heat treatment processes. For comprehensive studies on HEAs subjected to extreme loads, it is essential to explore their microscopic deformation mechanisms further while proposing innovative strategies designed to address inherent trade-offs between strength and toughness. The integration of state-of-the-art simulation techniques combined with advanced characterization methods will be crucial for improving research efficiency while providing insights into microstructural behavior. Additionally, tailored optimization approaches should be implemented for distinct advantageous systems and phase structures, particularly those capable of activating dislocation movements, twinning, phase transformations and incorporating novel processing methodologies such as additive manufacturing. Finally, conducting more realistic simulation experiments that closely replicate extreme environments along with generating relevant engineering data are vital steps toward accelerating the practical application of HEAs in challenging settings.

As a typical ceramic matrix composite （CMC）, SiC_f/SiC composite has enormous potential for application in the aerospace field because of the excellent properties such as high specific strength, high temperature resistance, oxidation resistance and good thermal shock resistance. The interphase between fiber and matrix plays a crucial role for protecting fibers, transmitting load and deflecting cracks, resulting in the pseudo-plastic fracture characteristics of SiC_f/SiC composites. The design scheme of interphase significantly affects its microstructural properties, thereby affecting the macroscopic mechanical properties and damage failure modes of SiC_f/SiC composites. In recent years, nano/micro fabrication techniques based on the focused ion beam （FIB）and nano/micro mechanical testing methods based on the nanoindentation are the effective methods to analyze and extract the interphase properties of SiC_f/SiC composites. The existing design schemes of interphase and the influence of interphase properties on toughening mechanism are reviewed. And also the application conditions, advantages and disadvantages of small-scale mechanical testing techniques including single fiber push-out/push-in and micropillar compression are summarized. Finally, the development trend for the research of CMC interphase properties are prospected: further standardizing the testing methods, building a high-temperature testing platform and modeling of testing data.

Carbon materials have high specific surface area, high dielectric constant, and excellent thermal and electrical conductivity characteristics, and BaTiO₃ has excellent dielectric properties. The combation of the two materials can effectively prevent and control electromagnetic pollution. In view of this, the BaTiO₃/PAN nanofiber film was prepared by electrospinning method, and then the BaTiO₃/carbon nanofiber mesh composite absorbing fabric was obtained by pre-oxidation and high temperature carbonization treatment. The nanofiber film prepared has the advantages of light, thin and wide bandwidth absorption. The results show that 2.0% BT/C has the best comprehensive performance, the carbon fiber arrangement is dense, the BaTiO₃ crystal form is complete and well dispersed, and the reflection loss at 2.3 mm reaches −61.72 dB, and the maximum absorption bandwidth reaches 8.5 GHz, which has excellent wave absorption.

The as-cast microstructure of 2024 high-strength aluminum alloy has an important effect on its thermal workability and end-use performance.The effects of Cu/Mg ratio and solidification rate on as-cast microstructure were investigated by regulating the Cu and Mg content and solidification rate of 2024 alloy. The results show that with the mass ratio of Cu/Mg increases from 2.1 to 4.1, the type of second phase in the alloy is not changed. However, the content of Al₂CuMg gradually decreases, while the content of Al₂Cu and Al₂₃Cu（Fe, Mn） ₄ gradually increases.When the solidification rate increases from 0.2 ℃/s to 2.4 ℃/s, the grain size is obviously refined, the average grain size decreases from 293.0 μm to 77.0 μm. Moreover, the dendrites become developed, and the dendrite arm spacing decreases, and the second phase becomes smaller and distributes more homogeneous in the matrix, and the content of Al₂₃Cu（Fe, Mn） ₄ insoluble phase obviously reduces. The formation of iron-rich insoluble phase can be reduced by reducing the Cu/Mg ratio and increasing the solidification rate, so as that the machining and mechanical properties of the alloy can be improved.

A titanium alloy collision friction ignition device was used to conduct collision and continuous friction between TC4 titanium alloy rotating rod and TA7 and other titanium alloy collision samples.Combined with SEM and other microscopic analysis, the anti-ignition performance and products of TA7 and TC11 titanium alloys were studied, and the experimental results under this special friction condition were obtained. The research results show that the friction contact pressure P_f and the combustion chamber pressure P can be effective test parameters to evaluate the titanium alloy impact ignition process. The critical ignition curves of the three titanium alloys drawn based on P_f-P are all linear laws, and the anti-ignition performance is: TC11 > TA11 > TA7. Microscopic analysis of the titanium alloy after impact ignition shows that the combustion reaction zone of the titanium alloy consists of four regions: the combustion product zone （CPZ）, the oxide zone （OZ）, the heat-affected zone （HAZ）, and the friction product zone （FPZ） in total. The multi-layer structure of Al₂O₃ formed by TC11 after ignition is conducive to blocking the mutual diffusion of Ti, O and other elements, which is the main reason for its superior anti-impact ignition performance.