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Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
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.
Scientists at the US Department of Energy’s Oak Ridge National Laboratory have demonstrated a method to insert genes into a variety of microorganisms that previously would not accept foreign DNA, with the goal of creating custom microbes to break down plants for bioenergy.
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.
Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.
Early career scientist Stephanie Galanie has applied her expertise in synthetic biology to a number of challenges in academia and private industry. She’s now bringing her skills in high-throughput bio- and analytical chemistry to accelerate research on feedstock crops as a Liane B. Russell Fellow at Oak Ridge National Laboratory.
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
Scientists at Oak Ridge National Laboratory have developed a low-cost, printed, flexible sensor that can wrap around power cables to precisely monitor electrical loads from household appliances to support grid operations.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
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.