Researchers find unexpected excitations in a Kagome layered material Researchers from the U.S. Department of Energy Ames National Laboratory have discovered an unexpected chiral excitation in the kagome layered topological magnet TbMn6Sn6.
Technology Review: How new magnets could accelerate climate action Ames National Laboratory scientist Matt Kramer is an expert source on magnetism in this MIT Technology Review news story about Minnesota-based start-up Niron Magnetics,
Rice University, Ames Lab team up on "stacked pancake" physics of magnetism Rice University teamed up with Ames National Laboratory to explain the behavior of magnetic materials
New superalloy could cut carbon emissions from power plants Sandia Laboratory partnered with Ames National Laboratory, Iowa State University, and Bruker Corporation.
Ames Lab scientist models a first: a pinwheel-shaped chiral nanostructure An Ames Laboratory scientist is a co-author of a paper published in Nature, of a newly discovered tetrahedral shaped chiral nanostructure
Ames Lab science featured in Optics & Photonics News Recent solar cell discoveries at Ames National Laboratory were featured in Optics & Photonic News
New discoveries made about a promising solar cell material, thanks to new microscope A team of scientists from the Department of Energy’s Ames National Laboratory developed a new characterization tool that allowed them to gain unique insight into a possible alternative material for solar cells.
Fundamental research improves understanding of new optical materials Scientists from Ames National Laboratory and Iowa State University developed a colloidal synthesis method for alkaline earth chalcogenides.
Ames National Laboratory research project awarded $4.5M to understand and control properties of rare earth materials The Department of Energy recently announced the winners for the 2022 Chemical and Materials Sciences to Advance Clean-Energy Technologies and Transform Manufacturing (CEM) awards.
Discovering materials for gas turbine engines through efficient predictive frameworks Current turbine blade materials have already reached their operational limit. To combat this problem, a team developed a framework capable of predicting the oxidation of high-entropy alloys.