Researchers have achieved, for the first time, electronically adjustable interactions between microwaves and a phenomenon in certain magnetic materials called spin waves. This could have application in quantum and classical information processing.
A team of scientists from Argonne is using artificial intelligence to decode X-ray images faster, which could aid innovations in medicine, materials and energy.
Researchers collaborated to create a software program to accelerate discovery and design of new materials for applications allowing for a far more comprehensive understanding of materials from atomistic to mesoscopic scale than ever before.
Researchers at Berkeley Lab, in collaboration with Carnegie Mellon University, have developed a new battery material that could enable long-range electric vehicles that can drive for hundreds of miles on a single charge, and electric planes called eVTOLs for fast, environmentally friendly commutes.
Argonne scientists Michael Bishof, Maria Chan, Marco Govini, Alessandro Lovato, Bogdan Nicolae and Stefan Wild have received funding for their research as part of DOE’s Early Career Research Program.
Argonne researchers have invented a machine-learning based algorithm for quantitatively characterizing material microstructure in three dimensions and in real time. This algorithm applies to most structural materials of interest to industry.