Researchers have developed a multimodal artificial intelligence framework that predicts the research octane number (RON) of both pure fuel components and complex mixtures with high accuracy. For pure components, the model achieved an R² of 0.9373 and a mean absolute error (MAE) of 4.04. For mixtures, the latent-space model achieved an R² of 0.9736 and an MAE of 1.46—reducing prediction error by 69.8 % compared with conventional linear blending rules. The model also enables inverse fuel formulation design, allowing researchers to search for feasible component proportions that meet target RON constraints.

 Researchers have systematically reviewed the application of electromagnetic induction heating in energy chemical engineering, focusing on three susceptor categories: carbon‑based materials, macroscopic metals, and magnetic nanoparticles. Carbon‑based susceptors enable reactant‑heat source integration for high‑temperature endothermic reactions such as calcium carbide synthesis, achieving solid‑phase synthesis with reaction temperatures reduced by 400‑500 °C compared to the electric arc process. Macroscopic metal susceptors combine heat generation and catalytic functions, with iron‑based induction heating reducing ammonia decomposition activation energy by more than half and maintaining high conversion at ultra‑high space velocities. Magnetic nanoparticles generate heat precisely at catalytic sites, enabling nanoscale hot spots under mild macroscopic temperatures for reactions such as reverse water‑gas shift and dry reforming.

Scientists from Trinity College Dublin have developed a powerful way to unravel the changing weather patterns on distant worlds. Using this approach, they discovered that the weather on a well-studied brown dwarf, “SIMP 0136”, previously linked with Northern Lights-like phenomena, is largely shaped by just two dominant processes: changes in temperature and the vertical structure of its clouds.

Scientists have long speculated why Venus, with a similar size, mass, and structure to Earth, doesn’t have a moon. New UC Riverside research shows it’s because our hungry twin likely swallowed it.

With the rapid development of 6G space–air–ground integrated communication networks, low Earth orbit (LEO) satellite constellations, leveraging their advantages of wide-area coverage and freedom from geographic constraints, have become key infrastructure for achieving global seamless connectivity. However, due to the relative motion among satellites in different orbits, inter-satellite links (ISLs) exhibit periodic dynamic on–off characteristics, among which a portion of the interruptions are predictable topological changes. Conventional Open Shortest Path First (OSPF) protocols compute shortest paths solely based on link distance, without considering link effective duration or bandwidth constraints, rendering them inadequate for adapting to the dynamic topological characteristics of satellite networks. Although fast reroute strategies can address sudden link failures, they consume substantial bandwidth resources and cannot provide protection for all nodes across the entire network. Therefore, how to proactively switch service paths before predictable link interruptions occur, so as to minimize service disruption and resource overhead, has become a core issue in ensuring service continuity in LEO satellite networks.