High numerical aperture fluorescence microscopy can reveal fine biological detail, yet its shallow depth of field makes thick multicolor samples challenging to image without axial scanning. Researchers developed MANTIS, a single shot computational microscope that combines a learned meta-optic with neural reconstruction to generate sharp multispectral fluorescence images in samples up to 50 micrometers thick at NA 1.1. The method expands imaging depth and suppresses defocus blur, enabling clearer visualization of thick biological samples.

Researchers from the Okinawa Institute of Science and Technology (OIST) and Hiroshima University have discovered that a small magnetic field switches the layered quantum material CeTe₃ between competing electronic states that appear as striped or checkerboard patterns. Published July 23 in Nature Communications, the work reveals how magnetism can reorganize a quantum material’s entire electronic state.

Professor Dr Gert Aarts is known for his work on strongly interacting matter and for linking theoretical physics with machine learning. Wübben Stiftung Wissenschaft is funding Professor Gert Aarts’ appointment as Professor of Theoretical Physics at Bielefeld University with 1.58 million Euros over four years. Aarts assumes the position in August.

A research team has developed an interphase activator strategy to improve lithium-ion transport in garnet-polymer composite solid electrolytes. The strategy uses SbF₃ to reconstruct the surface of LLZTO garnet particles and regulate the surrounding PVDF-based polymer phase, creating a continuous pathway for lithium ions across the ceramic-polymer interface. The optimized electrolyte shows high lithium-ion conductivity, stable lithium-metal cycling, and strong full-cell performance at 30 ℃, highlighting its promise for safer and higher-energy solid-state lithium-metal batteries.

iant planet in our solar system. Currently, numerous engineers are engaged in efforts to deploy probes into the Jovian system, and some key technical research studies are also carried out for future Jovian system exploration missions. However, capturing into another planet’s system is a costly process, particularly for the Jovian system. The presence of 4 Galilean moons renders the gravity-assist technique a highly effective means of modifying the velocity of probes relative to Jupiter. However, if a Jovian moon is expected to be visited, the perijove of the spacecraft must be lower than the orbital radius of the moon. There are disadvantages to capturing with a low perijove. Firstly, the spacecraft is severely affected by the strong radiation of Jupiter, which is harmful to the electronic components on the spacecraft when it gets close to Jupiter. Secondly, an amount of fuel is consumed to raise the perijove to satisfy the requirements of subsequent objectives. In order to alleviate the disadvantages of low-perijove capture, one solution is to raise the perijove more efficiently by leveraging the solar gravity perturbation (SGP).

This perspective article proposes a paradigm shift from single-discipline pathogen control to an integrated, cross-disciplinary approach that combines earth science and environmental engineering. Led by Zheng-Yang Huo from Renmin University of China, an research team outlines how geochemical insights and advanced disinfection technologies can work together to achieve full-chain assessment and control of waterborne pathogens, addressing a persistent threat that causes over 10 million deaths annually worldwide.

Mechanical force redistributes reactivity through anisotropic, topology-dependent load transmission. Predicting which covalent bond in a complex molecule ruptures first under tension remains a central problem in mechanochemistry, biomaterials and chemically recyclable polymers. Bond dissociation energy is an incomplete proxy because it describes zero-force thermodynamic stability, whereas mechanochemical site selectivity is governed more directly by the peak force sustained along a prescribed loading path. Here we introduce covalent-bond peak force network (CBPFNet), a graph-attention model that predicts covalent-bond peak force (CBPForce) from relaxed molecular structures through a virtual-stretching workflow and avoids the hundreds of constrained geometry optimisations typically required for each candidate bond. In the CHON benchmark studied here, CBPFNet reproduces bond-ranking trends from density functional theory (DFT) and can be used for bond-level screening. Post hoc attribution analyses indicate that rupture selectivity depends on both bond identity and local stiffness contrast, with relatively rigid segments concentrating tensile stress on softer adjacent bonds. In oligopeptides, the model recovers the DFT weakest bond and highlights a serine-containing motif as a possible topology-dependent weak point under the same protocol. CBPFNet therefore extends screening beyond equilibrium bond stability toward bond-resolved peak-force ranking in sustainable polymer design and biomaterials.