Photocatalytic seawater splitting is an attractive way for producing green hydrogen. Significant progresses have been made recently in catalytic efficiencies, but the activity of catalysts can only maintain stable for about 10 h. Here, we develop a vacancy-engineered Ag₃PO₄/CdS porous microreactor chip photocatalyst, operating in seawater with a performance stability exceeding 300 h. This is achieved by the establishment of both catalytic selectivity for impurity ions and tailored interactions between vacancies and sulfur species. Efficient transport of carriers with strong redox ability is ensured by forming a heterojunction within a space charge region, where the visualization of potential distribution confirms the key design concept of our chip. Moreover, the separation of oxidation and reduction reactions in space inhibits the reverse recombination, making the chip capable of working at atmospheric pressure. Consequently, in the presence of Pt co-catalysts, a high solar-to-hydrogen efficiency of 0.81% can be achieved in the whole durability test. When using a fully solar-driven 256 cm² hydrogen production prototype, a H₂ evolution rate of 68.01 mmol h⁻¹ m⁻² can be achieved under outdoor insolation. Our findings provide a novel approach to achieve high selectivity, and demonstrate an efficient and scalable prototype suitable for practical solar H₂ production.

With the development of the Internet and intelligent education systems, the significance of cognitive diagnosis has become increasingly acknowledged. Cognitive diagnosis models (CDMs) aim to characterize learners’ cognitive states based on their responses to a series of exercises. However, conventional CDMs often struggle with less frequently observed learners and items, primarily due to limited prior knowledge. Recent advancements in large language models (LLMs) offer a promising avenue for infusing rich domain information into CDMs. However, integrating LLMs directly into CDMs poses significant challenges. While LLMs excel in semantic comprehension, they are less adept at capturing the fine-grained and interactive behaviours central to cognitive diagnosis. Moreover, the inherent difference between LLMs’ semantic representations and CDMs’ behavioural feature spaces hinders their seamless integration. To address these issues, this research proposes a model-agnostic framework to enhance the knowledge of CDMs through LLMs extensive knowledge. It enhances various CDM architectures by leveraging LLM-derived domain knowledge and the structure of observed learning outcomes taxonomy. It operates in two stages: first, LLM diagnosis, which simultaneously assesses learners via educational techniques to establish a richer and a more comprehensive knowledge representation; second, cognitive level alignment, which reconciles the LLM’s semantic space with the CDM’s behavioural domain through contrastive learning and mask-reconstruction learning. Empirical evaluations on multiple real-world datasets demonstrate that the proposed framework significantly improves diagnostic accuracy and underscoring the value of integrating LLM-driven semantic knowledge into traditional cognitive diagnosis paradigms. 

Researchers at Texas A&M University model extreme conditions using 3D bioprinting, revealing insights that could make flight and space travel protocols safer while driving new breakthroughs in respiratory disease research and drug discoveries.

As the number of wireless applications and devices grows, higher standards for the quality of service and navigation performance of mobile networks are required. Numerous critical applications, including unmanned aerial vehicles, internet of things, digital twin, and military systems, require reliable communication and accurate navigation services. To meet these requirements, the development of the sixth generation (6G) network is necessary. 6G networks provide seamless 3-dimensional coverage in space–air–ground–sea area, as well as deep coupling of communication, sensing, and computation. 6G networks will be combined with low Earth orbit (LEO) satellites to construct a universal and intelligent integrated system of communication, sensing, and computing by utilizing the benefits of LEO satellites, such as miniaturization, modularity, large bandwidth, low latency, and wide area coverage. One of the critical construction tasks in this system is the integration of communication and navigation (ICAN), which can break the limitations of the global navigation satellite system, provide high-precision, robust navigation capability, and enable high- quality communication services.

Space manipulators play an important role in the on-orbit services and planetary surface operation whose reliability is a key issue. In the extreme environment of space, space manipulators are susceptible to a variety of unknown disturbances. Since it is difficult for the manipulator to be repaired immediately, once it fails, it will mean that it cannot complete the mission as expected, which may cause serious losses and dangers. How to have a resilient guarantee, i.e., the manipulator’s ability to resiliently recover and continue to complete tasks, in failure or disturbance is the core capability of its future development. The motion planning unit is used as the computing terminal of the manipulator’s joint motion trajectory. Compared with traditional motion planning, learning-based motion planning has gradually become a hot spot in current research. However, no matter what kind of research ideas, the single robotic manipulator is studied as an independent agent, making it unable to provide sufficient flexibility under conditions such as external force disturbance, observation noise, and mechanical failure.

With the advancement of Internet applications, the global demand for broadband satellite communication services is incessantly escalating. Furthermore, there exists an exponential surge in the requisition for the capacity of satellite communication systems. In response to this evolving demand, the domain of satellite communication technology is progressively evolving toward the realm of high-throughput satellite (HTS) communication systems. The typical technical characteristics of HTS are: (a) the satellite adopts multibeam technology for beam overlapping coverage of the service area, which improves the quality of the wireless link while realizing the spatial dimension segmentation; (b) based on this, the system adopts multiple frequency multiplexing to improve the communication capacity of a single satellite; (c) gateway stations are tightly coupled with user beam clusters to complete two-hop communication, which makes multiple gateway stations share the communication resources of the same satellite, forming a spatial isolation of the gateway stations, and once again realizing the frequency multiplexing of the gateway station links. A key requirement for future multibeam broadband satellite communication systems is the ability to flexibly adjust beam capacity according to changes in business distribution, in order to meet time-varying business requirements. Beam hopping technology provides an efficient solution to achieve the efficient use of frequency resources and power resources. At the same time, the use of beam hopping makes the beam hopping of satellite payload need to match the business signals of ground signal stations, bringing about the need for synchronization of beam hopping between satellite and ground.

The advent of the fifth-generation (5G) technology has revolutionized the way we think about communication networks, enabling a plethora of new use cases and scenarios that were not possible with previous generations of wireless technology. The existing 5G communication networks predominantly rely on terrestrial communication infrastructure, which, however, exhibits several notable limitations such as capacity constraints, latency issues, and energy inefficiencies, necessitating this next-generation leap. The 6G aims to provide a comprehensive solution for a hyperconnected, intelligent, and immersive digital ecosystem, seamlessly integrating terrestrial, airborne, and spaceborne networks which is referred to as the space-air-ground-sea integrated network (SAGSIN). A traditional SAGSIN scenario mainly includes 3 segments: spaceborne network, airborne network, and terrestrial network. The classical SAGSIN architecture has shown remarkable capabilities in providing massive connectivity by integrating spaceborne, airborne, and terrestrial cellular networks, which, however, encounters inherent technical challenges against their respective practical implementation. On the other hand, the philosophy of near-space communications (NS-COM) is gradually emerging. The distinctive location of near space which is 20 ~ 100 km above Earth’s surface positiones at the core of the SAGSIN, thus allowing the NS-COM network to address the shortcomings of traditional spaceborne, terrestrial, and airborne networks. NS-COM present a promising addition to SAGSIN, making them the final piece of the SAGSIN puzzle.