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ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

An international team of researchers used Summit to model spin, charge and pair-density waves in cuprates, a type of copper alloy, to explore the materials’ superconducting properties. The results revealed new insights into the relationships between these dynamics as superconductivity develops. Credit: Jason Smith/ORNL

A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

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.

Santa Jansone-Popova, left, and Ilja Popovs quantify rare-earth element concentrations in liquid samples using a spectroscopy instrument. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

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.

Automated disassembly line aims to make battery recycling safer, faster

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.

ORNL’s green solvent enables environmentally friendly recycling of valuable Li-ion battery materials. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

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

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: 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.

The proposed Battery Identity Global Passport suggests a scannable QR code or other digital tag affixed to Li-ion batteries to identify materials for efficient end-of-life recycling. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory have devised a method to identify the unique chemical makeup of every lithium-ion battery around the world, information that could accelerate recycling, recover critical materials and resolve a growing waste stream.

Nesaraja split her effort between nuclear data evaluation and experimentation at ORNL’s now-closed Holifield Radioactive Ion Beam Facility. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Nuclear physicist Caroline Nesaraja of the Department of Energy’s Oak Ridge National Laboratory evaluates nuclear data vital to applied and basic sciences.