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In autonomous vehicles laboratory

Oak Ridge National Laboratory and Department of Energy officials dedicated the launch of two clean energy research initiatives that focus on the recycling and recovery of advanced manufacturing materials and on connected and autonomous vehicle technologies.

ORNL scientists used new techniques to create long lengths of a composite copper-carbon nanotube material with improved properties for use in electric vehicle traction motors. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

Scientists at Oak Ridge National Laboratory used new techniques to create a composite that increases the electrical current capacity of copper wires, providing a new material that can be scaled for use in ultra-efficient, power-dense electric vehicle traction motors.

ORNL researchers developed a quantum, or squeezed, light approach for atomic force microscopy that enables measurement of signals otherwise buried by noise. Credit: Raphael Pooser/ORNL, U.S. Dept. of Energy

Researchers at ORNL used quantum optics to advance state-of-the-art microscopy and illuminate a path to detecting material properties with greater sensitivity than is possible with traditional tools.

Simulation of short polymer chains

Oak Ridge National Laboratory scientists have discovered a cost-effective way to significantly improve the mechanical performance of common polymer nanocomposite materials.

ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy

An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.

Researchers at Oak Ridge National Laboratory shed new light on elusive chemical processes at the liquid-liquid interface during solvent extraction of cobalt (dark blue). Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Real-time measurements captured by researchers at ORNL provide missing insight into chemical separations to recover cobalt, a critical raw material used to make batteries and magnets for modern technologies.

Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Analyses of lung fluid cells from COVID-19 patients conducted on the nation’s fastest supercomputer point to gene expression patterns that may explain the runaway symptoms produced by the body’s response to SARS-CoV-2. Credit: Jason B. Smith/ORNL, U.S. Dept. of Energy

A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.

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.