With the rapid development of laser weapon technology, predicting the damage behavior and failure process of laser protective coatings plays a key role in understanding the reliability of coatings. However, current models have not fully studied the thermal response process of multi-layer composite coatings and heavily rely on data samples such that their stability and applicability still require further consideration. To tackle these problems, in this work, a multidimensional prediction framework combining finite element simulation, SHAP quantitative analysis and deep learning was proposed. Firstly, through thermal-structural coupled finite element simulation and the SHAP quantitative method, the surface reflectivity was identified as the dominant factor in suppressing temperature rise, revealing its significant negative correlation with the peak temperature; when the reflectivity was increased from 87% to 97%, the peak temperature under 3000 W laser irradiation was decreased by approximately 73.1%. Subsequently, experiments on the Y₂O₃/8YSZ/NiCrAlY multilayer coating system further validated the finite element model. The results indicated that no obvious damage occurred on the coating surface under low-power laser irradiation. As the laser power increased, significant microstructural evolution, such as ablation rings and elemental enrichment from the bond coat, appeared on the coating surface, showing good agreement between the experimental phenomena and simulation results. Finally, the constructed deep learning framework achieved high-precision prediction of thermal damage, where the deep neural network demonstrated high prediction accuracy for transient temperature curves (R²>0.95) with a failure time prediction error of less than 10%. Furthermore, the Pix2PixHD network successfully realized high-fidelity inversion of the temperature field contour maps. This study provides a systematic reference for the structural design, performance evaluation and lifetime prediction of anti-laser coatings.

The promise of fusion energy is real. Major countries worldwide aim to achieve commercial grid-connected fusion power generation by around 2050, with magnetic confinement fusion—represented by tokamaks—leading the way among various fusion approaches. However, identifying suitable plasma-facing materials (PFMs) for the fusion core may be the greatest challenge on the road to commercial fusion, serving as a bottleneck that constrains the safety, steady-state operation, lifetime, and cost of fusion devices. PFMs are challenged by heat fluxes up to 20 MW·m⁻², plasma exposure with temperatures of hundreds of millions of K and neutron irradiations of 14.1 MeV. This places extremely stringent demands on the comprehensive properties of PFMs, including thermomechanical properties, corrosion resistance, radiation resistance. No single material has been able to simultaneously meet all the requirements for ideal PFMs. In this paper, an overview of the development history of PFMs in tokamaks is provided. Stainless steel was used as PFM in early fusion devices and was abandoned due to their low melting points and the contamination of the plasma by high-Z impurities generated by sputtering. Then, the PFM community shifted to low-Z materials such as carbon and beryllium that are compatible with plasma. These low-Z PFMs were phased out mainly due to their high erosion and high tritium retention later. The PFMs community revisited the high-Z materials of high melting points and high sputtering threshold, leading to tungsten as the reference material. The implementation of PFMs has undergone a transition from high-Z to low-Z and back to high-Z materials, reflecting the dialectical principle of negation of negation in epistemology. This evolution represents progress in comprehensive understanding of material properties, plasma control, and fusion device design of the fusion community, laying a solid foundation and instilling confidence in the realization of fusion energy’s promise. This paper also introduces potential candidate materials for PFMs in future fusion devices primarily including refractory metals and ultra-high temperature ceramics and discusses their advantages and disadvantages as PFMs. Challenges and perspectives on the future development of PFMs are presented at the final section.

The development of electromagnetic (EM) wave-absorbing materials is crucial for applications spanning information communication, equipment protection, and advanced defense systems. As operational environments extend toward high-speed and high-temperature regimes, a distinct class of high-temperature wave-absorbing materials has emerged, where EM response is no longer governed solely by intrinsic material properties but is strongly coupled with thermal activation effects and phase instability. The purpose of this review is to establish a comprehensive understanding of the key factors that govern high-temperature wave absorption and to identify design principles that can bridge intrinsic EM optimization with practical service reliability. First, this review clarifies the temperature-dependent evolution of intrinsic EM parameters, especially the loss of magnetic response above the Curie temperature, the drift of complex permittivity, and the resulting conflict between impedance matching and dielectric attenuation. Strategies for temperature-insensitive and broadband absorption are then discussed, including interfacial-polarization regulation, positive/negative temperature coefficient compensation of conductivity, frequency dispersion regulation, macrostructural resonance, and multiscale collaborative design. Second, the effect of oxidation, phase transformation, and decomposition, thereby introducing performance instability beyond idealized material assumptions, on the intrinsic EM responses are discussed. Then, the multi-physics coupling regime (thermal-mechanical-oxygen fields) encountered under near-service conditions is highlighted, where structural integrity degradation and EM attenuation failure become intrinsically intertwined, representing a system-level challenge that cannot be addressed by single-factor optimization. The oxidation-resistant design strategies for integrated load-bearing and wave-absorbing ceramic matrix composites, as well as design methods and recent progress related to high-temperature wave-absorbing coatings, are reviewed. Finally, remaining challenges and future development directions for high-temperature wave-absorbing materials are discussed.

Carbon/carbon-silicon carbide (C/C-SiC) composites are critical thermostructural materials for extreme aerospace environments, where flexural strength governs structural reliability. However, reliable prediction of flexural strength remains difficult because flexural strength is governed by complex nonlinear process-structure-property relationships, while experimental evaluation is time-consuming and costly. Traditional ML models often struggle to capture the complex structure-property relationships embedded in unstructured textual descriptions. Despite large language models (LLMs) excelling in natural language, their direct application to small-sample numerical regression remains challenging. This study introduces a semantics-guided multimodal machine learning (SGMML) framework using a LoRA-fine-tuned LLM text encoder with structured numerical features. The SGMML model based on a dataset of 142 cases achieved an MAE of 25.96 MPa and an R² of 0.81 outperforming traditional ML models by 20.9% and fine-tuned LLMs by 92.9% in terms of R². Experimental validation on two C/C-SiC composites manufactured via different processes yielded prediction residuals of 2.1 and 1.5 MPa. Furthermore, independent validation on external literature samples yielded an MAE of 18.08 MPa, demonstrating the framework's transferability beyond the training data. These results show that combining structured descriptors with domain-specific textual encoding enables accurate and scalable property prediction for advanced composites under data-limited conditions.

Bulk phase stability does not determine the service life of high entropy carbides in rocket applications; oxidation and recession of the surface oxide scale do. A screening methodology combining a regular solution stability model, equilibrium thermochemistry, and recession kinetics is applied to (Hf,Zr,Ti,Ta,Nb)C. No compositional spinodal is predicted, so selection falls to the oxide scale; every candidate oxide is molten at a throat, so volatility, not melting temperature, controls recession. Loss is bracketed between dissociative vaporization (floor) and a steam hydroxide channel (ceiling), second order in water vapor, which raises throat recession over two orders of magnitude at a hydrogen engine. The wall temperature controls recession exponentially, and a 55 flight life needs it below about 1870 K. At fixed wall temperature the dominant lever is the water vapor pressure; exchanging the steam loadings of hydrogen and kerosene engines changes recession 22 fold, against 1.4 fold for their 105 K gas temperature difference. Hafnium enrichment is worth 8.8 fold on the dissociation channel but only 1.06 fold with hydroxides. Against an adopted 100 μm/h criterion, five of seven candidates clear a leading edge and none clears a hydrogen engine throat; the hafnium and zirconium rich carbide ranks first in both.

The Moon has long inspired humanity’s imagination of the unknown. For thousands of years, it has remained a distant world that humans could gaze up but could not reach. Since the beginning of the 21st century, new lunar exploration programs have greatly expanded the understanding of the Moon, while a return of humans to the lunar surface is becoming a reality. The Moon is expected to become an important platform for future deep-space exploration. The lunar surface is characterized by extreme environments, including vacuum and low gravity, large temperature gradients, intense radiation, micrometeoroid impact, lunar dust, and energy limitations, which pose significant challenges to the long-term reliability and environmental adaptability of materials for lunar exploration. This perspective argues that the future of materials for lunar exploration lies not in discovering a single superior material, but in designing environment-adaptive material systems through the integration of materials, structures, and manufacturing strategies.