News

Guy in blue button down shirt crossing his arm and leaning against a wall.
Marthi receives IEEE senior member honor
Woman with dark brown hair pulled back into a bun holds a clipboard
Keeping aging structures safe
Four thermometers are pictured across the top of the image with an image of a city in the bottom left, with a color block version of that city in the bottom right.
Building energy around changing climate

Filter News

Area of Research

News Type

Date

News Topics

Media Contacts

Connect with ORNL

A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Self-driving microscopes discover shortcuts to new materials

Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.

With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

Seismic — Feeling it out

An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.

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

VA, ORNL and Harvard develop novel method to identify complex medical relationships

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.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

Retro technique advances modern bacterial engineering for bioenergy

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

Caption: This computer-generated image of the JET tokamak shows what one would see if its walls were transparent, revealing the plasma inside. Credit: UK Atomic Energy Authority

ORNL experts help measure new world record for fusion energy

A new fusion record was announced February 9 in the United Kingdom: At the Joint European Torus, or JET, the team documented the generation of 59 megajoules of sustained fusion energy, more than doubling the

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

AI — Revealing hidden biology

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

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

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

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.

Larry Baylor, left, and Andrew Lupini have been elected fellows of the American Physical Society. Credit: ORNL, U.S. Dept. of Energy

Baylor, Lupini elected fellows of American Physical Society

ORNL's Larry Baylor and Andrew Lupini have been elected fellows of the American Physical Society.

The first central solenoid module arrived at the ITER site in St. Paul-lez-Durance, France on Sept. 9. Credit: ITER Organization

US ITER – Power trip

Staff at Oak Ridge National Laboratory organized transport for a powerful component that is critical to the world’s largest experiment, the international ITER project.

For the first time in 25 years, scientists will use deuterium and tritium to create a plasma inside the chamber of the Joint European Torus in the United Kingdom to study nuclear fusion. As in the earlier experiments, diagnostics systems developed by ORNL will play a key role in monitoring the plasma. Credit: EUROfusion

Fusion – Helping JET soar

Equipment and expertise from Oak Ridge National Laboratory will allow scientists studying fusion energy and technologies to acquire crucial data during landmark fusion experiments in Europe.