A CUHK-led team has developed an integrated all-optical signal processor (OSP) that corrects signal distortion directly in light form, reducing latency and energy use compared with conventional digital signal processors (DSP). Built on a silicon photonic chip, it can perform real-time signal equalization in the optical domain and achieve 1.6 Tb/s throughput with under 60 picoseconds latency and extremely low power consumption, while flexibly compensating various transmission impairments, including fiber dispersion, system bandwidth limitation, and nonlinearities. Published in Science, the breakthrough offers a high-bandwidth, low-latency, and energy-efficient solution for high-speed AI data centre interconnects and marks progress toward using light for both data transmission and processing.

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.