Researchers uncover the origin of activation in high-capacity lithium-ion anodes
Peer-Reviewed Publication
Updates every hour. Last Updated: 26-Oct-2026 23:16 ET (27-Oct-2026 03:16 GMT/UTC)
High-capacity lithium-ion anodes often undergo an “activation” process in which capacity initially decreases and then gradually recovers during cycling, delaying full battery performance. Researchers have now shown that this behavior is strongly dependent on particle size. Using a Sn-based model system, the team found that large particles exhibit pronounced activation, whereas small particles show little to no activation. Their results reveal that the difference arises from a stress-induced kinetic retardation during lithiation, providing new guidance for the design of advanced battery materials.
A research team led by Prof. Jin Ge reports a strategy to markedly enhance iontronic mechanical sensors by tuning two previously underexplored electrical parameters—ionic conductivity and excitation frequency. Through a droplet-based model system combined with impedance spectroscopy and equivalent circuit analysis, the study establishes a quantitative framework linking these parameters to device impedance and capacitance variation. The results reveal that reducing ionic conductivity while increasing excitation frequency significantly boosts sensitivity, achieving up to 8772% improvement without altering device structure. The approach is further validated in hydrogel-based solid-state systems, demonstrating broad applicability. Prototype devices enable real-time pressure sensing, material differentiation in robotic systems, and 2D pressure mapping, offering a new pathway for the rational design and optimization of iontronic sensors.
The integration of liquid metals into conductive hydrogels has long been hindered by particle instability and coalescence. Researchers from Fuzhou University have developed a novel stabilization strategy using gelatin to create a highly uniform, conductive, and stretchable hydrogel. This "electronic skin" not only monitors human motion with high sensitivity but also utilizes deep learning for real-time handwriting recognition and harvests solar energy via photothermal conversion.
Lignin is a sustainable "gold mine" for green chemicals, yet its complex structure remains difficult to crack. Researchers have now developed an ultra-efficient Ru nanocluster catalyst supported on CeO2 to convert lignin-derived compounds into high-value 1,4-cyclohexanediol in pure water. By leveraging the Strong Metal-Support Interaction (SMSI) to create active interfaces, this green process achieves a record 96.7% yield, paving the way for sustainable plastic and resin production.
The high cost and limited availability of platinum-based catalysts remain major barriers to the widespread adoption of green hydrogen production via water electrolysis. A research team has developed a groundbreaking solution: a novel RuP₂-Ni₂P heterojunction catalyst embedded within N,P-codoped hollow carbon spheres (RuP₂-Ni₂P/NPC), engineered through an innovative "heterojunction-hollow confinement" synergistic strategy. This material demonstrates record-low overpotentials and exceptional long-term stability for the hydrogen evolution reaction (HER) across both alkaline and acidic electrolytes. This achievement not only provides a cost-effective alternative to platinum but also establishes a new design paradigm for developing next-generation electrocatalysts, bringing large-scale green hydrogen production closer to reality.
Conventional vision systems suffer from severe power and latency bottlenecks due to the physical separation of sensing and processing, which are challenges that in sensor computing seeks to resolve. However, existing neuromorphic hardware remains hindered by high programming energy and unidirectional photocurrent polarity. This work presents an energy efficient reconfigurable photodiode based on ferroelectric HfxZr1-xO2 (HZO) and ambipolar semiconductor WSe2, achieving energy-efficient in-sensor computing.
The U.S. Department of Energy has named North Carolina State University to lead three Genesis Mission projects aimed at using artificial intelligence (AI) to expedite discovery in the fields of high-performance computing, cybersecurity and astrophysics.
Researchers from Xinjiang University and East China University of Science and Technology have developed a novel iron-based single-atom catalyst (ZnS@Fe-NSC) that overcomes the long-standing trade-off between high activity and long-term stability in electrochemical CO2 reduction. By integrating sulfur doping and zinc sulfide (ZnS) nanoparticles within the catalyst architecture, the team achieved exceptional CO production efficiency with over 98% selectivity and maintained stable operation for 30 hours, paving the way for more durable and efficient energy conversion technologies.
Microwave-assisted catalytic reactors can convert biomass into useful gases such as hydrogen much faster than conventionally heated ones, and researchers from Kyushu University, Japan have captured evidence of why. Using advanced X-ray techniques to observe the catalyst in real time, the team showed that microwaves create tiny, localized hot spots on nickel catalyst particles, accelerating the catalytic reaction. The team hopes to establish an electrified, high-efficiency pathway for carbon-neutral biomass conversion.