Spin-state tuning in PrFeO3-δ perovskite boosts high-temperature oxygen evolution reaction
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Updates every hour. Last Updated: 22-Sep-2025 06:11 ET (22-Sep-2025 10:11 GMT/UTC)
The quest for high-performance energy storage solutions continues to drive innovation in materials science. A new study titled "Unlocking Colossal Storage Capacity and Energy Density of Two-Dimensional Biphenylene Oxide for Li-, Na-, and K-Ion Batteries" presents a groundbreaking advancement in the development of anode materials, offering a significant leap forward in battery technology.
Triterpenes, a diverse family of plant-derived molecules, are increasingly recognized for their potential in medicine, food, and sustainable industry.
Flowering in woody bamboos has long been considered one of botany's great mysteries, due to its rarity, unpredictability, and the eventual death of clumps after blooming.
Researchers at Nankai University have demonstrated a Surface Plasmon Driven Atomic Migration Mediated by Molecular Monolayern under room temperature and atmospheric conditions. By harnessing localized surface plasmons and molecular monolayers, the team achieved light-driven atomic manufacturing with high efficiency and controllability, paving the way for atomic-scale patterning and nanodevice fabrication.
This article examines the potential of Artificial Intelligence-driven Distributed Acoustic Sensing (AI+DAS) technology in engineering applications. Based on fiber optic monitoring, DAS enables real-time acoustic signal monitoring by detecting disturbances along the fiber, offering long measurement distances, high spatial resolution, and a large dynamic range. The article outlines the basic principles and demodulation methods of DAS using Φ-OTDR technology, highlighting AI's role in data processing and event recognition. By integrating AI algorithms, DAS systems enhance monitoring accuracy and reliability. Additionally, the article reviews AI+DAS applications across various fields, including engineering and geology, and discusses challenges such as model complexity and resource demands. Overall, it aims to foster interdisciplinary collaboration and support digital transformation in industrial scenarios.