Opto-Electronic Advances (光电进展)•2026•DOI: 10.29026/oea.2026.250263
The convergence of artificial intelligence (AI) and metaphotonics is creating a new paradigm for controlling light-matter interactions. The synergy of AI's ability to learn complex relationships in multidimensional data and provide ultra-fast inference with the capacity of metaphotonics to engineer optical properties not found in nature is unlocking a new era in computational design, real-time control, and fully automated optical systems. This review provides a comprehensive overview of state-of-the-art AI-driven approaches for metaphotonic systems. We focus on the solutions to real-world problems in accelerating metaphotonic simulations and inverse design, optical data characterization, and the development of fully integrated end-to-end AI-assisted metaphotonic systems. Finally, we provide our perspectives on the future research directions and emerging opportunities at the rapidly evolving intersection of metaphotonics and AI.
China Foundry (中国铸造 - 英文版)•2026•DOI: 10.1007/s41230-026-5020-x
Automation and intelligence have become the primary trends in the design of investment casting processes. However, the design of gating and riser systems still lacks precise quantitative evaluation criteria. Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements, but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions, making real-time adjustments to gating and riser designs challenging. In this study, an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed, which enhances the flexibility and usability of evaluating the casting process by simulation. Firstly, geometric feature extraction technology is employed to obtain the geometric information of the target casting. Based on this information, an automated design framework for gating and riser systems is established, incorporating multiple structural parameters for real-time process control. Subsequently, the simulation results for various structural parameters are analyzed, and the influence of these parameters on casting formation is thoroughly investigated. Finally, the optimal design scheme is generated and validated through experimental verification. Simulation analysis and experimental results show that using a larger gate neck (24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state, effectively eliminating shrinkage cavities and enhancing process yield by 15%.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01753-w
Joint health is critical for musculoskeletal (MSK) conditions that are affecting approximately one-third of the global population. Monitoring of joint torque can offer an important pathway for the evaluation of joint health and guided intervention. However, there is no technology that can provide the precision, effectiveness, low-resource setting, and long-term wearability to simultaneously achieve both rapid and accurate joint torque measurement to enable risk assessment of joint injury and long-term monitoring of joint rehabilitation in wider environments. Herein, we propose a piezoelectric boron nitride nanotubes (BNNTs)-based, AI-enabled wearable device for regular monitoring of joint torque. We first adopted an iterative inverse design to fabricate the wearable materials with a Poisson’s ratio precisely matched to knee biomechanics. A highly sensitive piezoelectric film was constructed based on BNNTs and polydimethylsiloxane and applied to precisely capture the knee motion, while concurrently realizing self-sufficient energy harvesting. With the help of a lightweight on-device artificial neural network, the proposed wearable device was capable of accurately extracting targeted signals from the complex piezoelectric outputs and then effectively mapping these signals to their corresponding physical characteristics, including torque, angle, and loading. A real-time platform was constructed to demonstrate the capability of fine real-time torque estimation. This work offers a relatively low-cost wearable solution for effective, regular joint torque monitoring that can be made accessible to diverse populations in countries and regions with heterogeneous development levels, potentially producing wide-reaching global implications for joint health, MSK conditions, ageing, rehabilitation, personal health, and beyond.
China Foundry•2025•DOI: 10.1007/s41230-025-4054-9
Alumina fibers, with an aspect ratio ranging from 9 to 27, were utilized as the reinforcing materials for silica-sol ceramic shell molds, and the impact of different alumina fiber additions on the green bending strength, room- and high-temperature bending strength, and self-weight deformation of ceramic shell molds was investigated. The green bending strength of shell molds is the maximum at an alumina fiber addition amount of 0.2wt.%, reaching 6.20 MPa. Further increases in alumina fiber content do not significantly affect the green bending strength. As the alumina fiber addition amount increases from 0.2wt.% to 1.0wt.%, the bending strength and the resistance to self-weight deformation of the ceramic shell molds at high-temperatures show a pattern of first increase and then decrease. The shell molds after sintering exhibit the highest room-temperature strength of 17.33 MPa and the highest high-temperature strength (18.97 MPa at 1,100 °C; 17.78 MPa at 1,200 °C; and 15.3 MPa at 1,300 °C), and the smallest self-weight deformation of 0.022% at 1,000 °C when the alumina fiber addition is 0.6wt.%. The appropriate amount of fibers in the shell mold matrix consume the energy required for crack growth through mechanisms such as bridging and pulling-out, thereby improving the strength of shell molds. In summary, the comprehensive performance of the shell molds is the best when the fiber addition amount is 0.6wt.%.
China Foundry•2025•DOI: 10.1007/s41230-025-4041-1
The effect of melt superheating treatment on the solidification microstructure and mechanical properties of the γ' phase precipitation-strengthened K424 superalloy was investigated. Differential scanning calorimetry (DSC) experiments were conducted to explore the influence of melt treatment temperature on the undercooling of the superalloy. Additionally, pouring experiments were carried out to assess how alterations in both the temperature and duration of melt treatment impacted the grain size, secondary dendrite arm spacing (SDAS), elemental segregation, and mechanical properties of the alloy. Metallographic analysis, scanning electron microscopy, energy dispersive spectroscopy (EDS) and Thermo-Calc software were employed for microstructure characterization. The test specimens were subjected to tensile testing at room temperature and stress rupture testing at 975 °C under 196 MPa. The findings reveal that appropriate melt treatment conditions result in decreased grain size, refined SDAS, minimized elemental segregation, and significant improvements in mechanical properties. Specifically, the study demonstrates that a melt treatment at 1,650 °C for 5 min results in the smallest average grain size of 949 μm and the smallest SDAS of 25.38 μm. Furthermore, the room temperature tensile properties and creep resistance are notably affected by the melt treatment parameters. It is shown that specific melt treatment conditions, such as holding at 1,650 °C for 5 min, result in superior room temperature strength and extended stress rupture life of the K424 superalloy, while a balance between strength and stability is achieved at 1,600 °C with a holding time of 10 min. These findings offer guidance for optimizing the melt treatment parameters for the K424 superalloy, laying a foundation for further investigations.
Journal of Central South University•2025•DOI: 10.1007/s11771-025-6100-6
In this study, AZ31 Mg alloy sheets were processed by a severe plastic deformation (SPD) technique called forging-bending repeated deformation (FBRD). The effect on the microstructure and microhardness of AZ31 Mg alloy through FBRD was investigated with increasing temperature treatment and a 90° cross route. The results reveal that the effective strain increases with the number of passes. The flow uniformity is effectively enhanced due to alterations in shear deformation direction. After four passes of deformation, the average grain size is refined by 79.3% compared to the initial specimen. The grain refinement mechanism predominantly originates from the synergistic effects of discontinuous dynamic recrystallization (DDRX), continuous dynamic recrystallization (CDRX), and twinning-induced recrystallization (TDRX). The formation of {1012} extension twins (ET) significantly contributes to coarse grain subdivision and plastic deformation coordinated. Furthermore, pyramidal <c+a> slip activation effectively enhances the plasticity of Mg alloys. By post four-pass processing, the alloy exhibits a microhardness of 81.9HV, primarily governed by fine grain strengthening and dislocation strengthening mechanisms.
Journal of Central South University•2025•DOI: 10.1007/s11771-025-6095-z
In this paper, the multi cross-rolling and cryogenic treatment were adopted to process the AZ31 Mg alloy to study the influence of passes and cryogenic treatment on cross-rolled AZ31 Mg alloy. The tensile properties and hardness were tested. The microstructure was characterized using electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) in order to elucidate the influencing mechanism. The results indicate that the treatment method can significantly improve the mechanical properties of AZ31 Mg alloy. The 3-pass sample processed by cryogenic treatment shows the highest strength (351 MPa) and has the highest hardness (76.1HV) and best hardness uniformity (standard deviation=0.9HV). The 2-pass sample has the highest ductility among all the samples but poor hardness evenness. The strengthening mechanism of 3-pass sample can be attributed to the fine grains, bimodal structure, high dislocation density, and precipitation strengthening. Due to repeated heat preservation of 4-pass and 5-pass, their comprehensive performances decrease.