KAIST-KIMM-Korea University collaboration succeeds in transferring precision nano-circuits to plant leaves, lotus leaves, and curved lenses without any damage.

The method floats thin metal films on water to transfer them directly and completely eliminating the need for heat, pressure, adhesives, or toxic solvents.

Expected to serve as a next-generation sensor platform for smart agriculture, wearable healthcare, and bioelectronics.

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features from an AI model trained on atomic structural data and optical absorption spectra, and then groups materials with similar structural and spectral characteristics. This approach can be extended to reveal how atomic arrangements influence other material properties, paving the way for more efficient materials design.

A team led by Professor Yanhao Yu at Southern University of Science and Technology (SUSTech) designed a high‑barrier viscoplastic encapsulation interlayer composed of polyisobutylene (PIB) and maleic anhydride‑grafted polypropylene (MAPP). Leveraging chain slippage and permanent disentanglement mechanisms, the interlayer achieves intimate conformal adhesion and hermetic encapsulation for various non‑planar electrodes (e.g., microwires, micropillars, and serpentine electrodes). It extends the in vivo signal fidelity of stretchable bioelectronic devices to 45 weeks.

A recent study published in National Science Review reveals that the spring Southern Annular Mode (SAM) underwent a marked spatial shift around 1998. Since then, its wave-like features have strengthened, enhancing its delayed impact on Antarctic summer sea ice. The 2022 and 2023 record-low events both followed strong spring positive SAM anomalies. The study further suggests that ENSO, through more frequent positive SAM-La Niña co-occurrence, may amplify SAM’s influence on Antarctic sea ice.

A team led by the Beijing Institute of Technology presents a unified framework in National Science Review for personalized healthcare termed self-powered intelligence. It describes how on-device AI, flexible electronics, and body-based energy harvesting can be co-designed into wearable patches and implantable sensors, enabling them to analyze physiological signals in real time, predict health risks, for continuous and personalized healthcare.

A research paper just published in Science China Life Sciences reports single-nucleus RNA sequencing (snRNA-seq) as a powerful technology that, for the first time at single-cell resolution, reveals the spatiotemporal pattern of hydrogen sulfide (H₂S) signaling in Chinese cabbage (Brassica rapa L. ssp. pekinensis) leaves, which mediates precise control of the intracellular transcriptional reprogramming and drought tolerance mechanisms.