Researchers from the Department of Precision Instruments at Tsinghua University have developed a novel model-based deep learning framework that significantly enhances the temporal resolution of computational microscopy. By training a neural network that learns the inherent spatiotemporal correlations in dynamic processes, the team achieved high-fidelity, time-resolved imaging of live biological samples, pushing the boundaries of label-free microscopy. The progress is published in the journal PhotoniX.

Researchers have created a spray-on polyurea nanocomposite coating reinforced with functionalized graphene. The coating delivers high strength and stretchability, strong adhesion across substrates, and durable performance after heat, salt-spray, and UV aging. It also resists corrosion and provides fast, reliable strain sensing for real-time damage detection—offering a scalable protective coating for infrastructure and automotive structures.

A research team led by Chalmers University of Technology, Sweden, have presented a new way to produce hydrogen gas without the scarce and expensive metal platinum. Using sunlight, water and tiny particles of electrically conductive plastic, the researchers show how the hydrogen can be produced efficiently, sustainably and at low cost.