This review presents a comprehensive analysis of the electromagnetic shielding mechanisms, advanced synthesis techniques, and material optimization strategies for ceramic-based electromagnetic shielding materials. Meanwhile, this review discusses the research progress of traditional ceramics (such as oxides, carbides, borides, nitrides and ferrites) and emerging ceramics (such as polymer-derived ceramics, MAX phase ceramics and high-entropy ceramics). Furthermore, the review outlines future research directions in four key areas: microstructure engineering for high-efficiency electromagnetic shielding ceramics, advanced manufacturing technologies, multifunctional integration of shielding properties, and the development of artificial intelligence-driven design approaches for ceramic materials.

Carbon fibers (CFs) are advanced materials that benefit various applications, including light-weight components for aircraft, automobiles and wind turbine blades. At present, the predominant feedstock is expensive polyacrylonitrile. A team of scientists used cheap coal and waste plastics to produce liquefied coals, which were subsequently fabricated into general-purpose and high-performance carbon fibers. This process has the potential to decrease the price of CFs and contribute to environmental and economic sustainability. Their work is published in Industrial Chemistry & Materials on October 3, 2025.

Researchers from the South China University of Technology, Jihua Laboratory, and Jilin University have developed a new way to make deep-blue OLED (organic light-emitting diode) devices more efficient without compromising on color quality.

A study in Forest Ecosystems found that combining bedding plows with pre-plant herbicide application, rather than double bedding, delivers the largest and most sustained gains in pine volume. This two-pass system effectively controls woody shrubs, the main long-term competitor, allowing pines to thrive for decades.

A Forest Ecosystems study highlights how forest landscape restoration (FLR) can play a critical role in improving water availability and ecosystem health across tropical regions. Drawing on decades of field studies, modeling, and global research, the study emphasizes that healthy soils and reliable water supplies are essential for both people and ecosystems to thrive.

Power systems are among the most complex man-made systems. However, complexity is not inherently an advantage. In fact, complex dynamics are often the underlying cause of complicated stability issues. In the future 100% renewable power system, converter-interfaced generation (CIG) becomes the main form of power generation, the dynamic of which are dominated by control processes and can be reduced with proper control strategies. Following this idea, researchers at Tsinghua University propose a frequency-fixed grid-forming control (FF-GFM) that controls CIGs as constant voltage sources within their capability limitations. FF-GFM can reduce frequency dynamics and synchronization dynamics, greatly enhancing the stability and safety of the system.

A multicenter study published in hLife has developed a novel risk prediction model for postoperative infections in kidney and liver transplant recipients. The research, involving 615 patients from six Chinese hospitals, identified previously overlooked predictors such as tea-drinking habits, psychological guilt scores, and dietary rhythms. The model achieved an area under the Receiver Operating Characteristic (ROC) curve of 0.78 in the training set, demonstrating strong predictive performance. These findings highlight the importance of integrating behavioral and psychological factors into clinical risk assessment, paving the way for more holistic post-transplant care strategies.

The exploration-exploitation dilemma is a long-standing topic in deep reinforcement learning. In recent research, a noise-driven enhancement for exploration algorithm has proposed for UAV autonomous navigation. This algorithm introduces a differentiated exploration noise control strategy based on the global navigation training hit rate and the specific situations encountered by the UAV in each episode. Furthermore, it designs a noise dual experience replay buffer to amplify the distinct effects of noisy and deterministic experiences. This approach reduces the computational cost associated with excessive exploration and mitigates the problem of the navigation policy converging to a local optimum.