Skip to main content
This illustration demonstrates how atomic configurations with an equiatomic concentration of niobium (Nb), tantalum (Ta) and vanadium (V) can become disordered. The AI model helps researchers identify potential atomic configurations that can be used as shielding for housing fusion applications in a nuclear reactor. Credit: Massimiliano Lupo Pasini/ORNL, U.S. Dept. of Energy

A study led by the Department of Energy’s Oak Ridge National Laboratory details how artificial intelligence researchers created an AI model to help identify new alloys used as shielding for housing fusion applications components in a nuclear reactor. The findings mark a major step towards improving nuclear fusion facilities.

Red background fading into black from top to bottom. Over top the background are 20 individual rectangles lined up in three rows horizontally with a red and blue line moving through it.

ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline exposing more of the material to light for increased photo-activation and better photochemistry data capture.

Frances Pleasonton seals a vacuum chamber in 1951.

The old photos show her casually writing data in a logbook with stacks of lead bricks nearby, or sealing a vacuum chamber with a wrench. ORNL researcher Frances Pleasonton was instrumental in some of the earliest explorations of the properties of the neutron as the X-10 Site was finding its postwar footing as a research lab.

Vincente Guiseppe, co-spokesperson of the Majorana Collaboration and a research staff member at ORNL, in front of the Majorana Demonstrator shield on the 4850 Level of SURF. Credit: Nick Hubbard/Sanford Underground Research Facility

For nearly six years, the Majorana Demonstrator quietly listened to the universe. Nearly a mile underground at the Sanford Underground Research Facility, or SURF, in Lead, South Dakota, the experiment collected data that could answer one of the most perplexing questions in physics: Why is the universe filled with something instead of nothing?

Initially, Celeritas will accelerate simulation of data from the Compact Muon Solenoid detector (shown schematically) at CERN’s Large Hadron Collider. Credit: Seth Johnson/ORNL, U.S. Dept. of Energy

Scientists at the Department of Energy’s Oak Ridge National Laboratory are leading a new project to ensure that the fastest supercomputers can keep up with big data from high energy physics research.

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.

Nesaraja split her effort between nuclear data evaluation and experimentation at ORNL’s now-closed Holifield Radioactive Ion Beam Facility. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Nuclear physicist Caroline Nesaraja of the Department of Energy’s Oak Ridge National Laboratory evaluates nuclear data vital to applied and basic sciences. 

ORNL Sign

Seven ORNL scientists have been named among the 2020 Highly Cited Researchers list, according to Clarivate, a data analytics firm that specializes in scientific and academic research.

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.

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.