Ever wondered how nature’s waterproof leaves and self-cleaning surfaces could inspire new materials? A recent study in Engineering explores how starch, a common kitchen ingredient, can be used to create advanced superwettable systems for packaging, water treatment, and even food taste enhancement. Discover how this eco-friendly solution is shaping the future of material science!

Looking to improve zinc production? Scientists have developed a new model that can quickly and accurately predict temperatures in industrial roasters using minimal data. This innovation could enhance efficiency and product quality in zinc smelting. Find out how it works and its potential impact in our latest report!

Lithium-rich oxides are widely regarded as one of the most promising cathode materials for next-generation lithium-ion batteries, but their potential has been hampered by rapid performance degradation. Now, researchers have developed a protective LiF@spinel dual shell that dramatically improves their stability. The spinel layer acts as a fast highway for lithium ions, while the outer LiF layer serves as a shield against corrosive electrolytes. Working in tandem, the two layers prevent structural collapse and suppress damaging side reactions. With this innovation, the modified cathode demonstrates outstanding cycle life and capacity retention, opening a new path toward reliable high-energy batteries.

Unlocking deep oil reservoirs just got easier! Scientists have developed a groundbreaking nanographite system that boosts oil recovery in extreme conditions. Read on to discover how this innovative solution overcomes high-temperature and high-salinity challenges, offering a game-changing approach for enhanced oil extraction.

Cornelia de Lange syndrome (CdLS) is a developmental genetic disorder. The characteristics of CdLS remain unexplored in the Chinese population. Now, a group of researchers from the National Center for Children’s Health, China, have examined the clinical presentations, mutational profiles, and hormonal therapy responses of Chinese children with CdLS. Mutations in three genes, correlation between mutations in a development-related gene and clinical presentations, and differential responses to hormone therapy were identified in Chinese patients.

Embodied intelligence applications, such as autonomous robotics and smart transportation systems, require efficient coordination of multiple agents in dynamic environments. A critical challenge in this domain is the multi-agent pathfinding (MAPF) problem, which ensures that agents can navigate conflict-free while optimizing their paths. Conflict-based search (CBS) is a well-established two-level solver for the MAPF problem. However, as the scale of the problem expands, the computation time becomes a significant challenge for the implementation of CBS. Previous optimizations have mainly focused on reducing the number of nodes explored by the high-level or low-level solver. This paper takes a different perspective by proposing a parallel version of CBS, namely GPU-accelerated conflict-based search (GACBS), which significantly exploits the parallel computing capabilities of GPU. GACBS employs a task coordination framework to enable collaboration between the high-level and low-level solvers with lightweight synchronous operations. Moreover, GACBS leverages a parallel low-level solver, called GATSA, to efficiently find the shortest path for a single agent under constraints. Experimental results show that the proposed GACBS significantly outperforms CPU-based CBS, with the maximum speedup ratio reaching over 46.