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.

The development of efficient, durable, and cost-effective oxygen evolution reaction (OER) electrocatalysts is essential for advancing renewable energy technologies. Herein, a novel strategy is reported that spatially confines a nanoscale localized high-entropy oxide (LHEO) consisting of Fe, Co, Ni, Zn, and Mn within α-Fe2O3, forming a unique α-Fe2O3@LHEO nanoarchitecture. The catalyst exhibits outstanding OER performance for alkaline water splitting, achieving a current density of 10 mA/cm2 at a low overpotential of 229 mV with a small Tafel slope of 34.4 mV/dec, significantly outperforming commercial RuO2 (326 mV, 118.8 mV/dec). It also shows excellent long-term stability over 1000 h at 100 mA/cm2 without notable activity degradation. Applied in rechargeable zinc–air batteries with natural seawater, the α-Fe2O3@LHEO cathode delivers a high power density of 88.3 mW/cm2 and stable operation over 600 cycles, substantially surpassing the benchmark Ru-Pt electrocatalyst (74.7 mW/cm2, 170 cycles). Combined experimental and theoretical studies reveal that LHEO induces lattice strain in α-Fe2O3, modulates its electronic structure, and lowers the crystal field splitting energy to stabilize high-spin Fe3+. These effects enhance metallic character for efficient charge transfer and optimize the adsorption/desorption of key oxygen reaction intermediates, thus shifting the OER pathway from the conventional adsorbate evolution mechanism (AEM) to the more energetically favorable lattice oxygen mechanism (LOM) with the energy barrier reduced from 1.85 to 1.71 eV. Overall, this work proposes a novel localized high-entropy engineering approach that overcomes key bottlenecks in designing efficient and durable OER electrocatalysts based on earth-abundant materials.

No-code biological modeling: BSC researchers developed open-access tools (MCP servers) that connect AI agents with specialized computational biology software, allowing complex multicellular models to be built through simple conversation.

From months to 10 minutes: The framework enables experimental biologists to generate initial 3D tumor digital twin prototypes in under 10 minutes without writing a single line of code or mastering complex software.

Accelerating cancer research: Published in npj Systems Biology and Applications, the study demonstrates how targeted, iterative AI interactions ensure reproducibility, paving the way for AI-assisted modeling of complex diseases.

A research team at the Faculty of Engineering of The University of Hong Kong (HKU), led by Professor Ruibang Luo from the School of Computing and Data Science and Professor Can Li from the Department of Electrical and Computer Engineering, has developed Gungnir, a novel blockchain-inspired DNA data storage codec. The breakthrough framework significantly improves digital information recovery from severely damaged DNA sequences, extending the practical lifespan of DNA data archives from under a decade to centuries.

In shale reservoirs, total oil content does not necessarily show where oil is stored or how mobile it may be. Researchers led by Bo Liu at Northeast Petroleum University developed a multiscale workflow that combines swelling-extraction experiments, SEM/AFM pore characterization and molecular dynamics simulations. The study separates shale oil into five occurrence types: kerogen-swelling oil, adsorbed oil in organic pores, free oil in organic pores, adsorbed oil in inorganic pores and free oil in inorganic pores. The framework offers a tool with strong applicability across study areas for understanding oil-rock interactions and evaluating shale-oil mobility in continental shale systems.

Researchers at the Max Planck Institute for Intelligent Systems and Carnegie Mellon University have unveiled a breakthrough technology that allows for highly accurate 3D motion capture using only standard video cameras, eliminating the need for expensive, specialized hardware and the iconic skin-tight motion capture suits covered in reflective markers. They named their system MAMMA – Markerless Accurate Multi-person Motion Acquisition. This system is capable of accurately capturing human motion without the need for markers, making it easy and cheap for everyone to create high-end animations and virtual avatars.