Skip to main content
AIST Conference

As the United States transitions to clean energy, the country has an ambitious goal: cut carbon dioxide emissions in half by the year 2030, if not before. One of the solutions to help meet this challenge is found at ORNL as part of the Better Plants Program.

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. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

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.

Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy

Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.

The researchers embedded a programmable model into a D-Wave quantum computer chip. Credit: D-Wave

Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.

Snapshot of total temperature distribution at supersonic speed of mach 2.4. Total temperature allows the team to visualize the extent of the exhaust plumes as the temperature of the plumes is much greater than that of the surrounding atmosphere. Credit: NASA

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. 

As part of DOE’s HPC4Mobility initiative ORNL researchers developed machine learning algorithms that can control smart traffic lights at intersections to facilitate the smooth flow of traffic and increase fuel efficiency.

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

Alex Johs at ORNL's Spallation Neutron Source

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.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

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.

Coexpression_hi-res_image[1].jpg

While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.