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Scientists at the U.S. Department of Energy’s Brookhaven National Laboratory have new experimental evidence and a predictive theory that solves a long-standing materials science mystery: why certain crystalline materials shrink when heated.
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.
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
Isabelle Snyder calls faults as she sees them, whether it’s modeling operations for the nation’s power grid or officiating at the US Open Tennis Championships.
Sometimes solutions to the biggest problems can be found in the smallest details. The work of biochemist Alex Johs at Oak Ridge National Laboratory bears this out, as he focuses on understanding protein structures and molecular interactions to resolve complex global problems like the spread of mercury pollution in waterways and the food supply.
Tempering, the heating process that gives chocolate its appealing sheen and creamy texture, is a crucial part of crafting quality chocolate. But, at the molecular level, it gets a little tricky, and when done incorrectly, can render entire batches of chocolate gritty and unappetizing.
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.