Molecular nanostructures can be activated using ultrasound
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Oct-2026 07:16 ET (27-Oct-2026 11:16 GMT/UTC)
The stability of zinc metal anodes is a critical bottleneck hindering the practical application of aqueous zinc-ion batteries. The team of Zhaoling Ma and Hongqiang Wang from Guangxi Normal University has developed a ZnV2O4 ion-sieve interface layer featuring a three-dimensional tunnel structure. By leveraging the synergistic effect of moderate oxygen vacancies and tunnel geometry, the material achieves ultra-fast and selective Zn²⁺ transport. This design enables symmetric cells to deliver stable cycling for over 3,700 hours at 4 mA cm⁻², and full cells to maintain a capacity retention of 52.5% after 1,000 cycles, offering a promising strategy for long-life aqueous zinc-ion batteries.
Viscosity is a fundamental property that determines how easily a material flows, affecting systems from industrial materials to the Earth's deep interior. Yet, scientists have rarely considered whether viscosity has an upper limit because high-viscosity materials are usually rock-forming minerals outside fluid dynamics studies. Now, a Japanese researcher has combined Earth observations, laboratory experiments, and numerical simulations to estimate a physically meaningful upper viscosity bound of 1030±2 Pa s, with implications for geophysics and materials.
Researchers at the University of Osaka have used machine learning to develop a systematic framework for structural descriptors in supercooled water. A neural network model was used to quantitatively assess the performance of 16 structural descriptors in differentiating between two states of water, a high-density liquid and a low-density liquid. The framework could be used to further our understanding of the anomalous behavior of water.
As artificial intelligence drives demand for faster and more energy-efficient hardware, ferroelectric memristors are attracting growing attention. A new review outlines how these devices combine memory, computation, and learning capabilities in a single platform, offering new opportunities for intelligent computing beyond the traditional von Neumann architecture.