The rapid development of artificial intelligence (AI) is reshaping the research landscape of structural design. Based upon the long-established theoretical framework of mechanics, emerging AI technologies, particularly large language models (LLMs), are providing new cognitive tools and methodological perspectives for structural design. As the structural morphology space continues to expand and multi-scale, multi-physics coupling problems become increasingly prevalent, traditional design approaches relying on accumulated experience and local trial-and-error methods are approaching their limits in handling growing complexity. In this context, AI not only opens new possibilities for exploring high-dimensional design spaces, representing knowledge, and facilitating interdisciplinary integration, but also extends the way humans understand and analyze complex systems. Looking ahead, AI may enable new development pathways for structural design, including closed-loop frameworks integrating design, manufacturing, and testing, unified paradigms for multi-physics structural design, and the emergence of intelligent structural systems. These developments offer important opportunities for structural science to further expand its cognitive boundaries in an era increasingly shaped by intelligent technologies.

To optimize an efficient biomimetic microfluidic chip for the highefficiency, highthroughput separation of micronsized particles such as microplastics, a computational fluid dynamic (CFD) coupled with discrete element method (DEM) numerical approach was employed to systematically investigate the internal flow field and particle separation mechanisms of a biomimetic microfluidic filtration structure. The 4 interesting particle separation mechanisms were summarized: at low Reynolds numbers, particles are separated through inertial focusing effects; at high Reynolds numbers, particles rely on the capture effect of vortices at the leading edge of the valve and the backflow effect between valves at the channel end to form 3 separation mechanisms. Finally, based on the mechanism analysis, the chip structure was optimized by increasing the crosssectional length of the auxiliary channel, to achieve a maximum improvement of 7.9% in particle separation efficiency, an average reduction of 7.2% in the main channel flow rate, and a maximum increase of 9.4% in the production of clean filtrate. These findings provide a theoretical support for the optimized design of efficient bionic filtration membranes.

The fracture behaviors of electrically semipermeable regular npolygon nanoholes with surface effects under farfield antiplane mechanical loading and inplane electric loading, were investigated. Based on the GurtinMurdoch surface model theory, the conformal mapping technique was adopted to analytically solve the stress and electric displacement fields, to obtain the analytical solutions for the stress intensity factor (SIF) and the electric displacement intensity factor (EDIF) at the crack tip. A new conformal mapping was constructed, from the exterior of s nanocracks emanating from the regular npolygon nanohole to the interior of the circular nanohole. The results indicate that, both the SIF and the EDIF are influenced by the coupling of farfield mechanical and electric loadings. Additionally, the smaller the side length of the regular npolygon is, the more prominent the surface effect will be.