Tuning the chiral asymmetry factor: A new dimension for lithium–sulfur battery catalysts
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Updates every hour. Last Updated: 25-Oct-2026 07:16 ET (25-Oct-2026 11:16 GMT/UTC)
It has long been recognized that chiral materials can selectively transport electron spins, yet their role in electrochemical energy storage remained unclear. Now, writing in National Science Review, researchers led by Prof. Hongsen Li at Qingdao University demonstrate that regulating the chiral asymmetry factor enhances spin polarization at catalytic sites, accelerates sulfur redox reactions, and significantly improves the electrochemical performance of lithium–sulfur batteries.
Researchers identified functional noncoding variants in an enhancer of TBX1 that may contribute to tetralogy of Fallot, the most common cyanotic congenital heart defect. Using whole-genome sequencing in 428 patients and blood vessel organoids, the study shows that disruption of this enhancer reduces TBX1 expression and impairs vascular development linked to the cardiac outflow tract.
In a paper published in SCIENCE CHINA Earth Sciences, a research team led by Professor Chengbang An reconstructed 4,000 years of dietary evolution in the central-eastern Eurasian Steppe from the Bronze Age to the Tang Dynasty, revealing synchronized dietary shifts across multiple regions: increased millet and meat consumption from the Early Iron Age to the Han Dynasty, followed by a return to wheat- and barley-based C₃ diets during the Jin-Tang periods. The study further demonstrates that these transitions were jointly driven by climate change, intensified interregional interaction among pastoralist groups, and innovations in grain processing technology. This work provides a critical reference for understanding human-environment interactions in the Eurasian Steppe.
Halide cathode materials are reshaping all-solid-state lithium batteries (ASSLBs) by enabling multi-electron reactions that dramatically boost energy density. A new review traces their evolution from liquid to solid-state systems, spotlighting single-phase electrode designs that eliminate inactive components and the rational design of multi-electron cathode materials. Looking ahead, it highlights AI-driven material discovery and integrated architectures to overcome energy challenges, charting a course toward cheaper, higher-energy ASSLBs.
Shaping electromagnetic waves at will is a long-standing goal in modern science and engineering. Programmable metasurfaces offer a promising route, but existing schemes are often too simple and fixed for real-time, task-oriented, and diverse control. A team from Zhejiang University has now developed a deep-learning-enabled temporal sequencing framework that maps target illusion patterns to modulation sequences, enabling rewritable and customizable electromagnetic illusions in experiments. This work is published in National Science Review.
A team led by Academician Ge Junbo and Professor Sun Aijun at Fudan University reveals that environmental eustress attenuates doxorubicin-induced cardiotoxicity while enhancing antitumor effects via a hypothalamus-heart-tumor axis. Eustress upregulates hypothalamic BDNF, which activates TrkB receptors on cardiac resident macrophages to inhibit CCL2 secretion, thereby reducing pro-inflammatory Ly6Chigh monocyte/macrophage infiltration into heart tissue. In hepatocellular carcinoma models, eustress also downregulates tumor microenvironment CCL2, decreasing immunosuppressive G-MDSCs and M2 macrophages while increasing cytotoxic CD8+ T cells and M1 macrophages. CCL2 is identified as a core dual target for cardio-oncology intervention, providing a safe and accessible non-pharmacological strategy for preventing chemotherapy-related cardiac toxicity in cancer patients.
Eye AI is moving fast, but will it work for people living at high altitude? In a study accepted by Science Bulletin, Dr. Wu Yuan’s team found that leading ophthalmic foundation models can lose accuracy across high-altitude retinal image cohorts. The team developed MIXFound, a lightweight way to combine several models and make AI diagnosis more robust in underrepresented settings.