Precision nutrient management in high-density orchards is critical for yield and fruit quality, yet accurately gauging the nitrogen status of individual trees remains a challenge. 

With the exponential increase in the number of objects in low Earth orbit (LEO), collision risks have risen correspondingly, making high-precision orbit prediction a core requirement for ensuring satellite safety and space environment management. Two-Line Elements (TLEs) are the only publicly available orbital data source and are widely used in conjunction with the Simplified General Perturbations 4 (SGP4) model for LEO object orbit prediction. However, LEO objects are significantly affected by complex time-varying perturbations such as atmospheric drag, causing model prediction errors to grow rapidly over time—short-term errors can reach hundreds to thousands of meters, while medium- and long-term prediction errors may exceed 10 km. Although traditional dynamical models can achieve relatively high accuracy through numerical integration, they incur substantial computational costs and suffer from limited atmospheric density modeling accuracy (only about 5%–15%). Analytical methods, while computationally efficient, struggle to handle complex perturbations. In recent years, bidirectional long short-term memory (BiLSTM) networks have demonstrated strong capabilities in time-series prediction; nevertheless, an effective approach for systematically modeling and compensating for TLE-based prediction errors using solely publicly available TLE data has remained lacking.

A review published in SCIENCE CHINA Earth Sciences synthesizes current knowledge of nitrous oxide (N₂O) production by marine planktonic ammonia-oxidizing archaea (AOA), an important microbial group involved in ocean nitrification. The authors summarize the potential metabolic pathways of AOA-derived N₂O and examine how environmental factors including oxygen, temperature, pH, substrate availability, and organic carbon regulate this process. The review highlights the need to understand multifactorial effects of ocean warming, acidification, and deoxygenation to better predict marine N₂O emissions under future climate change.

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.