An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
ORNL’s Zhenglong Li led a team tasked with improving the current technique for converting ethanol to C3+ olefins and demonstrated a unique composite catalyst that upends current practice and drives down costs. The research was published in ACS Catalysis.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.
Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
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.
More than 6,000 veterans died by suicide in 2016, and from 2005 to 2016, the rate of veteran suicides in the United States increased by more than 25 percent.
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