Scientists turn single molecule clockwise or counterclockwise on demand

Argonne scientists report they can precisely rotate a single molecule on demand. The key ingredient is a single atom of europium, a rare earth element. It rests at the center of a complex of other atoms and gives the molecule many practical applications.

Scientists use machine learning to accelerate materials discovery

Scientists at Argonne National Laboratory have recently demonstrated an automated process for identifying and exploring promising new materials by combining machine learning (ML) and high performance computing.

Call for Papers – The International Halal Science and Technology Conference 2022 (IHSATEC): 15th Halal Science Industry and Business (HAISB)

The Halal Science Center, Chulalongkorn University, and Research Synergy Foundation, invites all to attend “The International Halal Science and Technology Conference 2022 (IHSATEC): 15th Halal Science Industry and Business (HAISB)” and has opened up a call for papers. The conference sessions will be on December 15-16, 2022 at Chulalongkorn University, Bangkok, Thailand.

New cathode design solves major barrier to better lithium-ion batteries

New method for preparing cathode materials eliminates stumbling block to better lithium-ion batteries. New structure for cathode particles could lead to new generation of longer-lasting and safer batteries able to power vehicles for longer driving ranges.

Computer hardware mimics brain functions

A multi-institutional team, including Argonne National Laboratory, has developed a material with which computer chips can be designed to reconfigure their circuits when presented with new information. It does so by mimicking functions in the human brain.

Pushing the Boundaries of Moore’s Law: How Can Extreme UV Light Produce Tiny Microchips?

Some analysts say that the end of Moore’s Law is near, but Patrick Naulleau, the director of Berkeley Lab’s Center for X-Ray Optics (CXRO), says that it could be decades before the modern chip runs out of room for improvement, thanks to advances in materials and instrumentation enabled by the CXRO.

Machine learning program for games inspires development of groundbreaking scientific tool

Scientists have developed a groundbreaking AI-based algorithm for modeling the properties of materials at the atomic and molecular scale. It should greatly speed up materials discovery.

Opening the gate to the next generation of information processing

Scientists have devised a means of achieving improved information processing with a new technology for effective gate operation. This technology has applications in classical electronics as well as quantum computing, communications and sensing.

Editors of MIT Technology Review name Argonne’s Jie Xu as a 2021 Innovator Under 35

The editors of MIT Technology Review have chosen Argonne’s Jie Xu as an Innovator Under 35 for 2021. She is one of only 35 innovators under the age of 35 named to this list. She is being recognized for her research on printable skin-like electronics.

Pivotal discovery in quantum and classical information processing

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.

Argonne and Sentient Science develop game-changing computer modeling program to improve discovery and design of new materials

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.

Battery Breakthrough Gives Boost to Electric Flight and Long-Range Electric Cars

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.

Six Argonne researchers receive DOE Early Career Research Program awards

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.

Capturing 3D microstructures in real time

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.