Researchers have resolved a long-standing debate about how water behaves when confined to spaces just a few molecules wide, showing that the chemistry of nanoconfined water is governed less by confinement itself than by pressure and the nature of the surrounding material. This finding could help scientists design more efficient batteries, fuel cells and nanofluidic technologies by providing a new way of controlling water reactivity at the molecular scale.

The researchers will use the FWF’s science awards, worth one million euros each, to identify quantum materials for future technologies and to ensure that autonomous AI systems are trustworthy.

A physics team led by the University of Iowa has described a “super expanded” magnetic cloud created by a coronal mass ejection on the sun. The team tracked the cloud as it approached Earth. The new information could lead to better predictions of future, super expanded magnetic clouds that could lead to satellite and telecommunications disruptions on Earth. 

Researchers have developed a water-responsive polyvinyl alcohol-based film reinforced with a chitosan-pectin hybrid polysaccharide that maintains mechanical stability under high humidity and transforms into a high-performance adhesive upon water activation and hot-pressing, offering a sustainable alternative to petroleum-based films and formaldehyde-containing adhesives.

SAN ANTONIO—June 24, 2026—Southwest Research Institute (SwRI) and St. Mary’s University are collaborating to develop a physics-based forecasting tool that can predict the degradation and durability of TiFe-based metal hydride vessels through a chemical and thermo-mechanical framework. It is supported by a new $125,839 grant from the St. Mary’s-SwRI Technology and Applied Research (S²TAR) Program, which fosters collaborations between researchers from both organizations.

By leveraging a classical mathematical function, researchers at the Simons Foundation’s Flatiron Institute developed a new method that enables molecular dynamics simulations to run 2.5 to seven times as fast — all without sacrificing accuracy. For the most popular software package for molecular dynamics simulations, GROMACS, the researchers achieved a fivefold speed increase in simulations run at high accuracy.

A tandem neural network capable of inferring key physical parameters of semiconductor materials from simple transistor measurements has been developed, as reported by researchers from Institute of Science Tokyo. While conventional approaches for this type of analysis require hours or even days, the proposed system produces results in under one millisecond with near-perfect accuracy.