Space-based distributed array telescope formations, through multi-telescope collaborative observation and long-baseline optical interferometry, can significantly enhance deep space exploration capabilities, providing key technological support for missions such as asteroid monitoring and the search for extraterrestrial life. However, the measurement and control performance of such formations is highly dependent on the precision of intertelescope baseline measurements. Frequency-sweeping interferometry (FSI) technology, with its significant advantages—including freedom from the ambiguity range limitation, capability for non-cooperative target measurement, strong anti-interference ability in complex space environments, and high maturity of core components—has emerged as the most promising technical approach for baseline measurement in space-based distributed array telescope formations. Nevertheless, advancing this technology toward aerospace engineering applications still faces two major challenges: suppressing optical frequency-sweep nonlinearity and eliminating dynamic ranging errors. Currently, using electro-optic modulation to generate highly linear, synchronized, symmetrically sweeping positive and negative sidebands—establishing a frequency-sweeping interferometry system based on electro-optic sideband modulation—represents an effective method to address the issues of sweep nonlinearity and Doppler dynamic error. However, frequency-sweeping interferometry systems based on electro-optic sideband modulation lack a traceable on-orbit optical frequency-sweep reference, making it difficult to ensure long-term stable measurement and accuracy maintenance on orbit. Therefore, further research into high-precision electro-optic sideband modulation-based frequency-sweeping interferometry methods with traceable sweep references is of great significance for advancing the development of baseline measurement technology for space-based distributed array telescope formations.

Spaceborne gravitational wave detectors achieve long-baseline inter-satellite laser interferometry through satellite constellations, overcoming the limitations imposed by seismic noise and interferometer arm lengths on ground-based detectors, and providing a new observational means for detecting medium- and low-frequency gravitational waves and revealing the origin and evolution of the universe. The TianQin project aims to build a high‑precision spaceborne gravitational wave detection array. The test mass within its core component, the gravitational reference sensor, must transition smoothly from a high-load locked state to an ultra‑quiet and ultra‑stable geodesic state after launch and orbit injection, and this release process is a critical link for mission success. However, the plunger of the grabbing, positioning, and release mechanism (GPRM), under prolonged high-load operation, induces adhesion effects such as cold welding on the test mass, and the available electrostatic capture force is insufficient to overcome the interfacial adhesion, making it difficult for conventional release strategies to meet the strict constraint of residual velocity below 5 μm/s. Therefore, establishing a theoretical model that can accurately describe the dynamic behavior of the release mechanism and the interfacial adhesion effect is of great significance for evaluating release performance, revealing the mechanism of residual velocity generation, and guiding the optimization of mechanism parameters.

Ionic thermoelectrics (i-TEs) convert temperature differences into electricity, taking forms from liquids and gels to polyelectrolytes and porous solids. A new review in National Science Review takes a bird's-eye view—from the physics and chemistry of a single electrolyte to the engineering of commercial products—and lays out a material–device–system design framework. The authors conclude that reaching commercial products demands concerted, cross-disciplinary efforts in standardization, scalable manufacturing, reliability, and sustainability—not merely ever-higher performance metrics.

Near‑Earth asteroid impacts pose a major threat that could lead to the destruction of human civilization, having already caused catastrophic environmental changes and mass extinctions multiple times in history. In recent years, asteroids with diameters ranging from tens to hundreds of meters have frequently made close flybys of Earth, and a large number of large‑sized asteroids remain undiscovered, with warning times often only a few days to weeks. For large‑sized asteroids exceeding 100 meters in diameter, or even kilometer‑scale ones, traditional kinetic impact or long‑term force deflection methods offer limited energy and cannot achieve effective deflection within short timeframes. Using the enormous energy generated by nuclear detonation to directly destroy or rapidly deflect the asteroid's orbit is the most effective, and in extreme cases the only feasible, approach for dealing with large asteroids or those with short warning times. However, existing research on detonation defense has mostly focused on the direct rendezvous impact mode, in which the impact and detonation positions cannot be autonomously selected and energy coupling is relatively weak. Moreover, there is a lack of systematic analysis of the capability coverage and overall effectiveness of different defense modes, severely constraining the optimization of engineering designs.

Research, experimentation, training, as well as market access remain all too often disconnected in the building envelope sector, slowing the development and adoption of innovative, sustainable, and circular solutions. For companies, designers, and industry professionals, identifying the right expertise, infrastructure, and services throughout the innovation process is often complex, fragmented, and difficult to access.

The Building Envelope Alliance (BEA) was created to address this need. The new European network brings together research institutions, universities, and innovation accelerators. With complementary expertise and infrastructure, the Alliance aims to provide an integrated point of access to consulting services, testing, performance validation, specialized training, and technology transfer while supporting the development of building envelope solutions from the initial stages of research and concept validation through to market entry.

Researchers have built the first photonic computing chip that simultaneously exploits 32 wavelengths, 3 spatial modes, and 2 polarizations—192 parallel channels in total. The chip supports dynamically reconfigurable convolution kernels up to 13×13, enabling multi‑scale feature extraction and structured noise suppression. It achieves an experimental throughput of 15.36 TOPS, paving the way for high‑precision optical AI in computer vision and biomedical imaging.

As humanity enters the era of long‑term crewed deep‑space exploration, understanding the brain’s adaptive mechanisms to extreme environments such as microgravity and radiation has become a critical issue in space medicine. Previous studies using magnetic resonance imaging have revealed structural brain plasticity after spaceflight, including ventricular expansion and changes in grey matter volume. However, knowledge of dynamic changes at the neurophysiological level remains limited, and most existing evidence comes from group‑level analyses of long‑duration missions (e.g., six months), leaving the specific neurofunctional impact of short‑duration missions on individuals unclear. Conventional neuroimaging equipment is bulky and cannot be used in orbit. In contrast, electroencephalography (EEG) is portable, low‑cost, and repeatable, and has shown sensitivity in neurological conditions such as concussion, but its application in the extreme spaceflight environment has not been reported. Therefore, validating the feasibility of portable EEG technology for monitoring individual brain function before and after short‑duration spaceflight holds significant practical value for building future in‑orbit brain health assessment systems in deep‑space exploration.

The AI-based program AlphaFold predicts a protein’s 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant conformation, or shape, and overlooks experimental conditions that can alter local structure. Researchers at the Institute of Science and Technology Austria (ISTA) and international collaborators have now developed a way to guide AlphaFold with experimental data. Their approach, published in Nature Biotechnology, paves the way for improved future predictive models.