With the continuous growth of global communication demands, fiber-optic networks are undergoing rapid expansion, and the most widely used silica-based optical fibers are now approaching their intrinsic loss limits. Heavy-metal fluoride ZBLAN fibers theoretically exhibit losses in the mid-infrared band that can be approximately 20 times lower than those of silica fibers. However, this theoretical advantage has long been constrained by the inevitable crystallization problem during ground-based fabrication—ZBLAN glass possesses a critical cooling rate far higher than that of silica, rendering it highly susceptible to crystallization during the fiber drawing process on Earth, which leads to a significant increase in scattering loss. Although microgravity environments may reduce crystallization rates by suppressing buoyancy-driven convection, and theoretical models support this mechanism, the lack of space-qualified automated fiber drawing equipment has previously prevented the acquisition of fiber samples of sufficient length for systematic characterization. Therefore, validating the practical feasibility and performance enhancement effects of ZBLAN fiber drawing under microgravity conditions has become a key scientific issue in overcoming the bottleneck to realizing the ultra-low-loss potential of this material.

Over nearly five decades, biomolecular simulation techniques have become indispensable tools for uncovering fundamental principles governing life at molecular scale. These computational approaches enable quantitative characterization of complex biomolecular events including protein folding, conformational dynamics and protein‑protein interactions, and have greatly advanced both fundamental and applied biological research. In recent years, the integration of machine learning, especially deep‑learning algorithms, has sparked substantial innovation within this field.

Solid electrolytes are promising materials for safer, more compact all-solid-state batteries, but producing smooth thin films with high ionic conductivity remains challenging. In a recent study, researchers from Shibaura Institute of Technology, Japan, developed a multilayer method using lithium borohydride and lithium iodide to create high-iodine thin films. Their approach improved iodine incorporation, maintained relatively smooth surfaces, and produced good room-temperature ionic conductivity, opening new possibilities for thin-film solid electrolytes.

Lithium cobalt oxide (LiCoO₂, LCO) stands as one of the most representative cathode materials in lithium-ion batteries. The improvement in energy density of LiCoO₂ is essentially achieved by increasing the charge cut-off voltage. However, under high-voltage conditions, the electrolyte solvent molecules undergo severe oxidative decomposition at the cathode interface. Moreover, a series of issues including transition metal dissolution, oxygen release, and deteriorated thermal stability, have become bottlenecks that severely restrict its practical application.

To address this challenge, Prof. Yang Sun (Sun Yat-sen University), Associate Researcher Maolin Yang (Xiamen University), Professors Qiaobao Zhang (Xiamen University), Yu Qiao (Xiamen University), and Academician Shi-gang Sun (Xiamen University) have proposed a novel strategy to stabilize high-voltage LiCoO₂ cathodes by coating them with a conformal zeolite layer using a scalable high-speed solid-phase mechanofusion technique. The sub-nano channels of zeolite enable complete Li⁺ desolvation, creating a locally supersaturated electrolyte that suppresses solvent decomposition. The Zeolite@LCO cathode achieves ~83% capacity retention after 300 cycles at 4.8 V and stable operation at 5.0 V, with significantly enhanced thermal safety. This work provides a translatable paradigm for high-energy-density lithium-ion batteries. This work was recently published online in Science Bulletin.