Machine-learning based algorithm characterizes 3D material microstructure in real time

In a study published in Nature, researchers investigated capacity fading mechanisms in cathodes. The findings will inform the development of longer lasting lithium ion batteries.

In a study published in Advanced Functional Materials, researchers designed a nanodevice to prevent peptides from forming dangerous plaques in the brain in order to halt development of Alzheimer’s disease.

When superconductivity material science meets nuclear physics

Novel technique for advancing the way semiconductors are made

Fueling technology with potential to disrupt hydrogen economy is recognized with top prize from Federal Laboratory Consortium

In a study published in ACS Nano, researchers deepened their understanding of photodynamics. Their discoveries could inform design of brighter single photon sources for biological, quantum information and nanophotonic applications.

In a study published in Nature Computational Materials, researchers developed a machine learning technique that combines topology and image processing to visualize 3D micro-structures and characterize features that affect their material properties.