As part of an international team, researchers from the Karlsruhe Institute of Technology (KIT) have synthesized an extraordinary aromatic cycle. Consisting of three metal atoms, it is the heaviest example of this type of molecule: A triangle made from three bismuth atoms is held between two metal complexes in a structure known as “inverse‑sandwich” complex. This discovery contributes to a better understanding of aromaticity in heavy elements. In addition, the study might pave the way for new functional materials. The results have been published in Nature Chemistry.  (DOI: 10.1038/s41557-026-02123-8)

Scientists from the Dalian Institute of Chemical Physics of the Chinese Academy of Sciences have explained themicrostructure formation mechanism of nonsolvent-induced phase separation (NIPS) by separating the formation processesof different pore structure. Based on the findings, the team developed a free-standing ultrathin porous polymeric membrane with a thickness of only 2.7 μm that simultaneously offers high selectivity and high conductivity. When applied in a vanadium flow battery, the membrane demonstrated outstanding electrochemical performance.

Could wound healing dressings adhere better, and drug delivery patches become more sophisticated? A KAIST research team has developed a technology that leverages natural ingredients derived from plants to increase the strength of seaweed-based hydrogel (a gel material that contains a large amount of water while maintaining its shape) by more than fivefold, while also controlling its adhesiveness and degradation rate.

Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This systematic review comprehensively surveys ML applications across pipeline reliability design, integrity assessment, inspection, and maintenance; identifies key bottlenecks including data scarcity, poor interpretability, and limited field validation; and proposes a research roadmap toward tractable, trustworthy ML for full-lifecycle pipeline safety.

Researchers from the University of Oxford have demonstrated a new family of quantum superpositions – Schrödinger’s cat- like quantum states – from highly nonclassical building blocks. The work opens a new route towards quantum computing with non-binary systems, sensing and understanding quantum physics at a more fundamental level.

Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining a deeper understanding of element formation in stellar events such as neutron star mergers. For the first time, the scientists used deep learning with a neural network to model the energy release during r-process nucleosynthesis in hydrodynamic simulations. The results are published in the journal Physical Review D.

Monoterpenoid indole alkaloids (MIAs) are plant-derived molecules with unique pharmaceutical potential, but their highly complex and intricate structures make them difficult to produce in the laboratory. Now, researchers from Japan have developed a new strategy that enables the total synthesis of bisleuconothine A and bousigonine B, two biologically relevant oligomeric MIAs. Their findings lay the foundation for further studies of this family of molecules.  Monoterpenoid indole alkaloids (MIAs) are plant-derived molecules with unique pharmaceutical potential, but their highly complex and intricate structures make them difficult to produce in the laboratory. Now, researchers from Japan have developed a new strategy that enables the total synthesis of bisleuconothine A and bousigonine B, two biologically relevant oligomeric MIAs. Their findings lay the foundation for further studies of this family of molecules.  

Achieving high safety in energy storage systems is paramount but hindered by the catastrophic risks of thermal runaway propagation (TRP). This study develops a gradient-laminated ceramifiable silicone foam composite to resolve the inherent trade-off between thermal insulation and dynamic impact toughness. By integrating a polydimethylsiloxane foam matrix with a load-bearing glass fiber fabric skeleton, the material utilizes silane coupling agents for robust interfacial adhesion, while multiscale fillers promote synergistic ceramicization. Characterization reveals robust mechanical durability, maintaining stable elasticity across a wide temperature range (− 40 to 300 °C) and retaining 93% residual stress after 1,000 compression cycles. Under extreme thermal exposure, the foam transforms into a dense ceramic barrier, reducing total heat release by 54.4% and sustaining thermal protection for over 30 min. Crucially, during battery module testing, this architecture efficiently intercepts high-velocity gas jets and confines thermal runaway to a single cell. Fabricated via a scalable process, this composite paves a viable way for constructing intrinsically safe energy storage systems.