Skip to main content
A team of fusion scientists and engineers stand in front of ORNL’s Helium Flow Loop device. From back left to front right: Chris Crawford, Fayaz Rasheed, Joy Fan, Michael Morrow, Charles Kessel, Adam Carroll, and Cody Wiggins. Not pictured: Dennis Youchison and Monica Gehrig. Credit: Carlos Jones/ORNL.

To achieve practical energy from fusion, extreme heat from the fusion system “blanket” component must be extracted safely and efficiently. ORNL fusion experts are exploring how tiny 3D-printed obstacles placed inside the narrow pipes of a custom-made cooling system could be a solution for removing heat from the blanket.

LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy

It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

ORNL fusion scientist Elijah Martin is working with TAE Technologies to demonstrate the feasibility of field-reversed configuration reactors, a possible alternative to the traditional tokamak-based devices. Credit: ORNL.

ORNL manages the Innovation Network for Fusion Energy Program, or INFUSE, with Princeton Plasma Physics Laboratory, to help the private sector find solutions to technical challenges that need to be resolved to make practical fusion energy a reality.

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.

Burak Ozpineci is a globally recognized leader in power electronics research. He was named an ORNL Corporate Fellow in fall 2021. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Burak Ozpineci started out at ORNL working on a novel project: introducing silicon carbide into power electronics for more efficient electric vehicles. Twenty years later, the car he drives contains those same components.

U.S. Secretary of Energy Granholm tours ORNL’s world-class science facilities

Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges. 

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.

L-R: ORNL’s Omer Onar and Veda Galigekere with the dynamic wireless charging test bed at ORNL’s Grid Research Integration and Deployment Center. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Consumer buy-in is key to the future of a decarbonized transportation sector in which electric vehicles largely replace today’s conventionally fueled cars and trucks.