Skip to main content
ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.

The ORNL National Center for Computational Sciences is now home two Hewlett Packard Enterprise, or HPE, Cray EX supercomputers that will provide the U.S. Army and Air Force with global and regional numerical weather model outputs for planning and executing missions worldwide. Credit: Jason Smith/ORNL, U.S. Dept. of Energy and HPE Cray

The U.S. Air Force and Oak Ridge National Laboratory launched a new high-performance weather forecasting computer system that will provide a platform for some of the most advanced weather modeling in the world.

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

A multi-institutional team became the first to generate accurate results from materials science simulations on a quantum computer that can be verified with neutron scattering experiments and other practical techniques.

ORNL recognized the small businesses that have made a positive impact on ORNL’s operations at the virtual 2020 Small Business Awards. Credit: ORNL, U.S. Dept. of Energy

Thirty-two Oak Ridge National Laboratory employees were named among teams recognized by former DOE Secretary Dan Brouillette with Secretary’s Honor Awards as he completed his term. Four teams received new awards that reflect DOE responses to the coronavirus pandemic.

The TRITON model provides a detailed visualization of the flooding that resulted when Hurricane Harvey stalled over Houston for four days in 2017. Credit: Mario Morales-Hernández/ORNL, U.S. Dept. of Energy

A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.

An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy

Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.