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A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

A traffic-camera view of Shallowford Road, one of the more than 350 intersections in Chattanooga studied by Oak Ridge National Laboratory researchers.

The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.

As part of the Next-Generation Ecosystem Experiments Arctic project, scientists are gathering and incorporating new data about the Alaskan tundra into global models that predict the future of our planet. Credit: ORNL/U.S. Dept. of Energy

Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet 

Researchers studying secondary metabolites in the fungus Aspergillus flavus, pictured, found unique mixes of metabolites corresponding to genetically distinct populations. The finding suggests local environmental conditions play a key role in secondary metabolite production, influencing the discovery of drugs and other useful compounds. Credit: Tomás Allen Rush/ORNL, U.S. Dept. of Energy.

Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in

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.

Vittorio Badalassi, left, of Oak Ridge National Laboratory leads the Fusion Energy Reactor Models Integrator, or FERMI, project, and collaborates with ORNL computational physicist David Green. FERMI applies fission platforms to fusion reactor design. Credit: Commonwealth Fusion Systems and Colby Earles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory expertise in fission and fusion has come together to form a new collaboration, the Fusion Energy Reactor Models Integrator, or FERMI

Belinda Akpa applies her diverse expertise and high-performance computing to accelerate the drug discovery process and increase the chances of success when candidate molecules go to clinical trials. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Belinda Akpa is a chemical engineer with a talent for tackling big challenges and fostering inclusivity and diversity in the next generation of scientists.

Rich Giannone uses bioanalytical mass spectrometry to examine proteins, the primary driver in biological systems.

Rich Giannone uses bioanalytical mass spectrometry to examine proteins, the primary driver in biological systems.

ATOM logo

The Accelerating Therapeutics for Opportunities in Medicine , or ATOM, consortium today announced the U.S. Department of Energy’s Oak Ridge, Argonne and Brookhaven national laboratories are joining the consortium to further develop ATOM’s artificial intelligence, or AI-driven, drug discovery platform.

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.