As affordable alternatives to lithium-ion batteries, potassium-ion batteries (PIBs) face problems such as safety issues, limited lifespan, and electrolyte incompatibility with high-capacity electrodes. A non-flammable electrolyte using fluorinated triethyl phosphate (FTEP) as a weakly solvating solvent to create an anion-rich solvation sheath around potassium ions was developed. This innovation facilitates stable potassium plating, efficient K⁺ insertion into graphite, and prevents aluminum corrosion, paving the way for safer and more durable PIBs.

A computational framework integrates electrochemical lithium-ion intercalation dynamics with mechanical stress evolution in battery materials, addressing a critical gap in solid-state battery design. The specific aspect of coating material for silicon particles in anode layer is investigated, and the key parameters, including coating thickness and strength are systematically analyzed. 

Rechargeable aqueous batteries (RABs) have attracted considerable attention for large-scale energy storage applications due to their inherent safety. Manganese dioxide (MnO₂), based on two-electron-transfer deposition/dissolution chemistry, offers an ultrahigh theoretical capacity and high redox potential, paving the way for high-energy RABs.

A 20-hectare plot at the Paint Rock ForestGEO site in north Alabama (29,282 trees mapped) reveals how landscape features shape tree species distribution and biomass. While overall biomass did not correlate with landform or topographic indices, the biomass of individual species did. The dominant species appeared to partition the site with American beech and yellow-poplar dominating the valleys, and white oak, southern shagbark hickory, and white ash predominantly on slopes and benches Average biomass was 211 Mg/ha., The species distribution demonstrates how topographic niche partitioning maximizes ecosystem carbon storage, as published in Forest Ecosystems.

Unmanned Swarm Systems (USS) have transformed key fields like disaster rescue, transportation, and military operations via distributed coordination, yet trajectory prediction accuracy and interaction mechanism interpretability remain major bottlenecks—issues that existing methods fail to address by either ignoring physical constraints or lacking explainability. A recent breakthrough from Northwestern Polytechnical University solves this: Dr. Shuheng Yang and Prof. Dong Zhang developed the Swarm Relational Inference (SRI) model, an unsupervised end-to-end framework integrating swarm dynamics with dynamic graph neural networks. This model not only enhances interpretability and physical consistency but also drastically reduces long-term prediction errors, marking a critical step toward reliable autonomous collaboration for real-world USS applications.

Molten calcium–magnesium–alumina–silicate (CMAS) is easy to wet and penetrate into thermal barrier coatings (TBCs), causing the coating corrosion and premature failure. Applying a protective layer on the TBC surface is considered a useful method to alleviate CMAS attack. In this study, a bilayer-structured apatite layer was constructed by pre-reacting GdPO₄ with CMAS powders. It consists of an acicular upper layer and a compact lower layer, which remained microstructure integrity after heat treatment at 1250 °C for 50 h, and did not crack after 100 thermal cycles. At 1250 °C for 30 min, the CMAS contact angle on the bilayer-structured apatite layer was 17.4 °, exhibiting excellent low-wettability to CMAS. In addition, the layer provides outstanding resistance to the penetration of molten CMAS. Hence, the bilayer-structured apatite layer can be used as a protective layer for TBCs to fundamentally address the CMAS corrosion issue.

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.

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.