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Two of the researchers who share the Nobel Prize in Chemistry announced Wednesday—John B. Goodenough of the University of Texas at Austin and M. Stanley Whittingham of Binghamton University in New York—have research ties to ORNL.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
A modern, healthy transportation system is vital to the nation’s economic security and the American standard of living. The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) is engaged in a broad portfolio of scientific research for improved mobility
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.
Materials scientists, electrical engineers, computer scientists, and other members of the neuromorphic computing community from industry, academia, and government agencies gathered in downtown Knoxville July 23–25 to talk about what comes next in
In Hong Wang’s world, nothing is beyond control. Before joining Oak Ridge National Laboratory as a senior distinguished researcher in transportation systems, he spent more than three decades studying the control of complex industrial systems in the United Kingdom.
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
The use of lithium-ion batteries has surged in recent years, starting with electronics and expanding into many applications, including the growing electric and hybrid vehicle industry. But the technologies to optimize recycling of these batteries have not kept pace.