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A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
A new technology for rare-earth elements chemical separation has been licensed to Marshallton Research Laboratories, a North Carolina-based manufacturer of organic chemicals for a range of industries.
Using novel data sets and computing systems, researchers at ORNL are simulating how climate change affects the safety and security of the country.
A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.
Analytical chemists at ORNL have developed a rapid way to measure isotopic ratios of uranium and plutonium collected on environmental swipes, which could help International Atomic Energy Agency analysts detect the presence of undeclared nuclear
A 25-year career with the U.S. Navy, commanding combat missions overseas, brought Tom Kollie back to where he came from — ready to serve his country in a new way.
Researchers at ORNL have developed a robotic disassembly system for spent electric vehicle battery packs to safely and efficiently recycle and reuse critical materials while reducing toxic waste.
Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.