Weaving secondary battery electrodes with fibers and tying them like ropes for both durability and performance
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Apr-2026 12:16 ET (23-Apr-2026 16:16 GMT/UTC)
A joint research team led by Dr. Gyujin Song of the Korea Institute of Energy Research (President: Yi, Chang-Keun, hereafter “KIER”), Dr. Kwon-Hyung Lee of the University of Cambridge, and Professor Tae-Hee Kim of the University of Ulsan has successfully developed a new dry-process manufacturing technology for secondary battery electrodes that overcomes the limitations of conventional electrode fabrication processes.
A global collaboration including Sunwoda, Chery, Nobel laureate M. Stanley Whittingham, Semitronix, the University of Delaware, and Advance Power, has proposed the "Integrated Battery Large Model," the first AI-driven paradigm covering the entire lithium-ion battery lifecycle. Published in National Science Open, the work outlines a new paradigm for intelligent battery design, manufacturing optimization, defect diagnosis, and lifecycle management through multi-modal AI and simulation synergy.
High-resolution full-color quantum dot light-emitting diode (QLED) displays still face significant challenges, particularly limitations in restricted pixelation manufacturing process and the operational longevity of specific pixels. Researchers have developed a single-layer color-tunable QLEDs technology that achieves color-tunable emission via operating voltage adjustment, avoiding complex tandem structures while demonstrating record-breaking external quantum efficiency (EQE) and broad color gamut including standard white emission, highlighting significant potential for application in full-color display and lighting technologies.
Artificial intelligence is reshaping brain modeling. This review introduces a unified framework where AI functions as a surrogate brain by integrating dynamical modeling, inverse problem solving, and model evaluation. Trained on neural data, surrogate brains can accurately predict large-scale brain activity and support system analysis, virtual experiments, and model-guided neurostimulation.
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