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Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS. Credit: ORNL, U.S. Dept. of Energy

Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.

ORNL’s Ramesh Bhave poses in his lab in March 2019. Bhave developed the Membrane Solvent Extraction process, which can be used to recover cobalt and other metals from spent lithium-ion batteries. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Momentum Technologies Inc., a Dallas, Texas-based materials science company that is focused on extracting critical metals from electronic waste, has licensed an Oak Ridge National Laboratory process for recovering cobalt and other metals from spent

An interactive visualization shows potential progression of BECCS to address carbon dioxide reduction goals. Credit: ORNL, U.S. Dept. of Energy

The combination of bioenergy with carbon capture and storage could cost-effectively sequester hundreds of millions of metric tons per year of carbon dioxide in the United States, making it a competitive solution for carbon management, according to a new analysis by ORNL scientists.

Sergei Kalinin

Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.

ORNL's Battery Manufacturing Facility

Energy storage startup SPARKZ Inc. has exclusively licensed five battery technologies from the Department of Energy’s Oak Ridge National Laboratory designed to eliminate cobalt metal in lithium-ion batteries. The advancement is aimed at accelerating the production of electric vehicles and energy storage solutions for the power grid.

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the