As global water resources face increasing pressure from industrial and agricultural activities, scientists are looking for innovative ways to clean and reuse wastewater sustainably. Researchers from Dalhousie University have now developed a simple and eco-friendly method to turn agricultural and forestry waste into powerful magnetic materials that can effectively remove toxic chemicals from water.

A new study has revealed that the lasting effects of biochar depend strongly on the material it is made from, with straw-derived biochar offering clear advantages for maize productivity under limited-water conditions. The research, published in Biochar, shows that combining wheat-straw biochar with an alternate partial root-zone drying irrigation system can boost crop yield and resource efficiency for at least two growing seasons after a single biochar application.

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.

Silicon carbide (SiC) and silicon nitride (Si₃N₄) powders are critical raw materials for advanced ceramics. However, traditional synthesis methods face four major challenges: difficulty in achieving SiC nanosizing, difficulty in realizing Si₃N₄ high purification, the need for external energy input for the weakly exothermic Si-C reaction, and the requirement of adding large amounts of diluents to enable the combustion synthesis of the strongly exothermic Si-N₂ reaction. Recently, a research team utilized the difference in heat release between the Si-N₂ and Si-C reactions. By means of chemical furnace encapsulation, the strong heat release from the Si-N₂ reaction was used to induce the combustion synthesis of the weakly exothermic Si-C reaction system. Through the regulation of the combustion reaction temperature field and the partial pressure of CO reducing gas, β-SiC powders with an average particle size of only 30 nm and high-purity pink β-Si₃N₄ powders with an oxygen content as low as 0.46 wt% were successfully synthesized. Their work is published in the journal Industrial Chemistry & Materials on 10 October.

Researchers at Seoul National University have compiled the latest technologies in the field of fabricating stretchable synaptic transistors, a neuromorphic device capable of learning even under deformation. This review introduces materials, manufacturing processes (photopatterning, printing, lamination-and-transfer), and structures (vertical, wave-like, textile) that maintain low-voltage stable operation even under deformation. By clearly identifying remaining technical challenges, such as n-type/bipolar semiconductors, CMOS-compatible patterning, and biocompatibility, it provides a roadmap for developing scalable wearable and neuroprosthetic systems.

Orbital angular momentum (OAM) of light offers transformative potential for optical technologies, yet current efforts largely focus on spatial-only control within a single pulse, leaving dynamic space-time manipulation limited. Toward this goal, researchers in China proposed a novel concept of a spatiotemporal vortex comb with time-varying photon features, including transverse OAM density and chirality, realized through a spatiotemporal multiplexing technique. This technique may facilitate applications in ultrafast light-matter interactions, quantum information, spatiotemporal topology and metrology.