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This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

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.

Frontier supercomputer

A multi-institutional team, led by a group of investigators at Oak Ridge National Laboratory, has been studying various SARS-CoV-2 protein targets, including the virus’s main protease. The feat has earned the team a finalist nomination for the Association of Computing Machinery, or ACM, Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.

ORNL’s collaboration with Cincinati Children’s Hospital Medical Center will leverage the lab’s expertise in high-performance computing and safe, secure recordkeeping. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

There are more than 17 million veterans in the United States, and approximately half rely on the Department of Veterans Affairs for their healthcare.

A selfie from the Curiosity rover as it explores the surface of Mars. Like many spacecraft, Curiosity uses a radioisotope power system to help fuel its mission. Credit: NASA/JPL-Caltech/MSSS

Radioactive isotopes power some of NASA’s best-known spacecraft. But predicting how radiation emitted from these isotopes might affect nearby materials is tricky

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

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In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.

Edge computing is both dependent on and greatly influencing a host of promising technologies including (clockwise from top left): quantum computing; high-performance computing; neuromorphic computing; and carbon nanotubes.

We have a data problem. Humanity is now generating more data than it can handle; more sensors, smartphones, and devices of all types are coming online every day and contributing to the ever-growing global dataset.

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Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.

An artist rendering of the SKA’s low-frequency, cone-shaped antennas in Western Australia. Credit: SKA Project Office.

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.