With funding from the Federal Ministry of Research, Technology and Space (BMFTR), the new project SIBAF (Supraleitender Ionenbeschleuniger als BAsistechnologie für die Fusionsforschung) will establish a unique accelerator-based infrastructure for the rapid qualification of advanced materials for future fusion power plants. As part of the funding program “Basistechnologien für die Fusion – auf dem Weg zu einem Fusionskraftwerk” (Basic technologies for fusion – on the path to a fusion power plant), SIBAF will receive €9.7 million over three years, of which €8.1 million will support activities at the GSI Helmholtzzentrum für Schwerionenforschung and the international accelerator center FAIR, currently under construction. Alongside GSI, which coordinates the project, Goethe University Frankfurt is the project partner.

Decorative wood veneer bends much more easily when its rough “loose side” faces outward during shaping. By simply choosing the right bending direction—loose side as the tension surface—the reduced cracking and a minimum wrapping angle of 90° for beech veneer have achieved, making it suitable for right-angle curved furniture without costly reinforcements.

Researchers from Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) recently observed a species of armored searobin, Scalicus engyceros, walking sideways and backward on the sea floor in the South China Sea. This is the first time a species of fish has been observed walking backward.

Researchers have developed a stretchable passive cooling interface that spontaneously self-stratifies into a sunlight-reflecting upper region and a liquid-metal heat-spreading lower region, reducing the temperature of wearable electronics by up to 12 °C outdoors while preserving the quality of physiological signals.

A large-scale international study led by The Hong Kong University of Science and Technology (HKUST) has revealed that inter-city collaboration on emission reduction can improve overall sustainability performance by more than 10%. This comprehensive analysis covers 4,116 cities and spans 11 years of data, shedding new light on regional and global strategies towards achieving the United Nations Sustainable Development Goals (SDGs).

Researchers from Zhejiang University and Zhejiang Advanced CNC Machine Tool Technology Innovation Center, China, have developed a Symmetry-Imbued Hamiltonian Neural Operator (SIHNO) for predicting stress fields in porous metamaterials. The proposed architecture combines rotation-equivariant geometric representations with a Hamiltonian-inspired energy structure to improve prediction accuracy and robustness under different structural orientations.

The framework integrates a Rotation-Steerable Lattice Projector (RSLP), a Hamiltonian-Fueled Propagator (HFP), and a slice-aware convolutional decoder to address two challenges in stress field prediction: orientation bias caused by fixed coordinate representations and non-physical stress leakage near void-solid interfaces.

In comprehensive numerical experiments based on finite-element-generated stress fields, SIHNO outperformed several established neural operator and physics-informed models across multiple evaluation metrics. The model also maintained millisecond-level inference speed, highlighting its potential for rapid stress prediction in additive manufacturing applications.