Water is everywhere – it covers the major part of Earth, circulates in the human body, and is found even in the smallest molecular clefts. However, what happens if water cannot flow freely, but is enclosed in such structures? Researchers of Karlsruhe Institute of Technology (KIT) and Constructor University in Bremen proved for the first time that enclosed water can influence its surroundings and favors binding between molecules. This discovery could open new paths for the design of drugs and new materials. The researchers report on their findings in the International Edition of the “Angewandte Chemie” journal. (DOI: 10.1002/anie.202505713)

Researchers at Fudan University have achieved a breakthrough by fabricating the first Field-Programmable Gate Array (FPGA) based on wafer-scale two-dimensional (2D) semiconductor materials. Integrating approximately 4,000 transistors, the chip represents a historical leap, moving 2D electronics from simple logic circuits to complex, reconfigurable functional systems. Critically, the 2D FPGA exhibits inherent radiation resistance, maintaining full functionality after enduring a total ionizing dose of 10 Mrad of gamma-ray irradiation, offering a physically superior core device for strategic sectors like aerospace and high-reliability computing.

A new study reveals that the impact humans are having on the Amazon rainforest is so profound it is even changing the evolutionary history and functionality of the forests.

Scientists used molecular simulations to reveal how polymer chains adhere to alumina surfaces. Adhesion depends on both polymer chemistry and surface termination, with different responses before and after yielding. These insights clarify metal–plastic bonding mechanisms and offer guidelines for designing stronger, lighter, and more sustainable hybrid materials for use in transportation.

X-ray absorption spectroscopy (XAS) provides valuable information about a material’s properties and electronic states. However, it requires extensive expertise and manual effort for conventional analysis. Now, researchers from Japan have developed a novel artificial intelligence-based approach for analyzing XAS data that can enable rapid, autonomous, and object material identification. This novel approach outperforms the previous studies in terms of higher accuracy, accelerating the development of new materials.