Soft, shape-changing materials are attracting growing interest in applications ranging from robotics to wearable devices, but conventional 3D printing methods are limited to a single actuation mode in each printed component. A new study demonstrates the first 3D-printable smectic liquid crystal elastomer ink that can switch molecular alignment during printing, allowing the same filament to either elongate or contract when heated. The advance could enable more versatile soft robots, adaptive surfaces, and minimally invasive biomedical devices.

Sodium-ion batteries (SIBs) are promising, safer, and lower-cost alternatives to lithium-ion batteries. Recently, scandium (Sc) has been shown to be a promising dopant material for sodium-based cathodes, aimed at improving durability of SIBs. In a new study, researchers investigated how Sc doping and coating improves cycling performance of sodium-based electrodes. The study uncovers the underlying mechanisms and offers practical design guidelines for developing next-generation, long-lasting SIBs. 

Halide cathode materials are reshaping all-solid-state lithium batteries (ASSLBs) by enabling multi-electron reactions that dramatically boost energy density. A new review traces their evolution from liquid to solid-state systems, spotlighting single-phase electrode designs that eliminate inactive components and the rational design of multi-electron cathode materials. Looking ahead, it highlights AI-driven material discovery and integrated architectures to overcome energy challenges, charting a course toward cheaper, higher-energy ASSLBs.

Shaping electromagnetic waves at will is a long-standing goal in modern science and engineering. Programmable metasurfaces offer a promising route, but existing schemes are often too simple and fixed for real-time, task-oriented, and diverse control. A team from Zhejiang University has now developed a deep-learning-enabled temporal sequencing framework that maps target illusion patterns to modulation sequences, enabling rewritable and customizable electromagnetic illusions in experiments. This work is published in National Science Review.

Three-dimensional (3D) vision is undergoing a profound transformation. Recently, Zhoujie Wu and Qican Zhang from Sichuan University, together with Gunther Notni from the Fraunhofer Institute for Applied Optics and Precision Engineering IOF, published a review paper in Light: Advanced Manufacturing to systematically summarize over four decades of development in fringe projection profilometry (FPP) and reveal a paradigm shift from traditional geometric triangulation toward computational 3D imaging.

Researchers at Aalto University in Finland, together with international partners, have developed the most accurate model yet of how humans read. The new model uses reinforcement learning, a type of AI used in robotics, to explain—and recreate—the choices readers make as they move through text.

Eye AI is moving fast, but will it work for people living at high altitude? In a study accepted by Science Bulletin, Dr. Wu Yuan’s team found that leading ophthalmic foundation models can lose accuracy across high-altitude retinal image cohorts. The team developed MIXFound, a lightweight way to combine several models and make AI diagnosis more robust in underrepresented settings.