New biochar breakthrough offers hope for cleaner, safer farmland soils
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Sep-2025 07:11 ET (21-Sep-2025 11:11 GMT/UTC)
In a pioneering study that explores the hidden carbon reservoirs of coastal ecosystems, researchers are quantifying the carbon stocks of macroalgal beds in the southwestern Atlantic Ocean. The study, titled "Carbon Stocks of Coastal Macroalgal Beds in the SW Atlantic," is led by Prof. Angelo Fraga Bernardino from the Departamento de Oceanografia at Universidade Federal Do Espírito Santo (UFES) in Vitória, Brazil. This research offers valuable insights into the role of macroalgal beds in carbon sequestration, highlighting their importance in marine protected areas.
This study focuses on V2O3-x nanoparticles and systematically analyzes them as plasmonic solar-driven catalysts for the first time. It reveals that they exhibit the localized surface plasmon resonance (LSPR) absorption characteristics in the near-infrared regions. By integrating in-situ characterization and theoretical calculation results, the mechanism of in-situ generation of oxygen vacancies (Vo) in V2O3 under irradiation and subsequently transformed into catalytically active V2O3-x is elucidated. Furthermore, the process in which V2O3-x generates hot electrons and holes through plasmon damping is analyzed, as well as its excellent effects in increasing the local temperature, providing active sites, and enhancing the light absorption capacity. V2O3-x demonstrates excellent performance in the reverse water-gas shift reaction (RWGS), with a CO conversion rate of 668.48 mmol g-1 h-1, with a CO selectivity exceeding 99.9%, and long-term stability for 90 h, highlighting the great potential of metal oxide plasmas in solar-driven catalysis. This research provides crucial insights into enhancing the solar-chemical energy conversion efficiency by utilizing the synergistic effect of LSPR and intrinsic interband transitions..
A team of AI scientists and seismologists has developed a pioneering self-supervised framework, DASFormer, for high-resolution earthquake monitoring. Built on a two-stage, coarse-to-fine architecture, DASFormer is pre-trained on vast amounts of unlabeled Distributed Acoustic Sensing (DAS) data collected from existing fiber-optic cables (e.g., Internet cables). Acting like a “self-taught seismologist”, the model first learns the predictable patterns of background noise and then flags earthquake signals as anomalies that defy its forecasts. This novel approach demonstrates superior performance, outperforming other state-of-the-art models. Its versatility extends to challenging environments such as the seafloor, underscoring its potential for scalable, automated seismic intelligence.
Ultraviolet (UV) phototherapy is a widely used and effective dermatological treatment, yet its application has been limited by UV toxicity and challenges in targeted delivery. Upconversion nanoparticles (UCNPs), a novel photoluminescent nanomaterial capable of converting near-infrared (NIR) light into shorter-wavelength visible or UV light, hold promise for enabling NIR-driven skin phototherapy.
Tomatoes, one of the world's most important horticultural crops, often struggle to grow in saline soils that limit yields and quality.
Water behaves very differently when confined at the nanoscale, and understanding these anomalies is crucial for advancing catalysis, environmental technologies, and energy systems. A new study has investigated the mechanisms and scale-dependent behavior of confined water between Al2O3 layers, and identified a threshold range of 10 to 20 nm that marks the transition between confined and bulk water behaviors, offering guidance for the design of next-generation nanoreactors and interfaces.
The civilian GPS signals are vulnerable to spoofing attacks in UAV system. A new on-board algorithm named MSSTP-OAD enables low-cost drones to detect counterfeit GPS positions in real time using only their existing GPS receiver and inertial unit—no extra radios, antennas or ground stations required. Compared to existing LSTM-based algorithms, the proposed method can achieve 98.4 % accuracy, 24 % faster detection and 26 % shorter recovery distance.
Flexible composites-based piezoelectric nanogenerator (PENG) with low cost, stable properties and sensitivity to mechanical deformation is highly suitable to construct self-powered sensing layer for distributed electrical transmission power lines, and this innovation can help reduce manual maintenance costs. However, the lower output performance of the PENG hinders its integration with energy management circuits and signal recognition systems. In this study, a high-performance PENG was achieved by designing branch-heterostructure piezoelectric ceramic fibers, which can enhance the charge transport mechanisms and induced polarization. Moreover, an intelligent Power Internet of Things system through the synergistic integration of this high-performance PENG and learning-assisted data analytics has been constructed, which enables accurate self-powered real-time monitoring of abnormal vibration states in transmission power lines with approximately 96% identification accuracy. This work not only provides an effective strategy to enhance PENG performance, but also offers a solution to improve the reliability of power grid operations and optimize maintenance efficiency. Recently, a team of material scientists led by Haowei Lu from Henan University, China, prepared high-performance PENG based on a new piezoelectric ceramic fiber, which is beneficial to the improvement of electrical output performance by enhanced induced polarization and directed charge transport mechanism. Moreover, based on this PENG, a power grid transmission line vibration determination system with high identification accuracy can be constructed in this study.