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: This schematic of tokamak core-pedestal-boundary regions show what will be simulated by an ORNL project applying machine learning to plasma physics modeling. Credit: Giacomin et al., J. Comput. Phys., 463, (2022) 111294, https://doi.org/10.1016/j.jcp.2022.11294

ORNL will lead three new DOE-funded projects designed to bring fusion energy to the grid on a rapid timescale.

Attendees of SMC23 pose for their annual group photo in downtown Knoxville, TN.

ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.

Clouds of gray smoke in the lower left are funneled northward from wildfires in Western Canada, reaching the edge of the sea ice covering the Arctic Ocean. A second path of thick smoke is visible at the top center of the image, emanating from wildfires in the boreal areas of Russia’s Far East, in this image captured on July 13, 2023. Credit: NASA MODIS

Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.

HFIR

Creating energy the way the sun and stars do — through nuclear fusion — is one of the grand challenges facing science and technology. What’s easy for the sun and its billions of relatives turns out to be particularly difficult on Earth.

The Fuel Pellet Fueling Laboratory at ORNL is part of a suite of fusion energy R&D capabilities and provides test equipment and related diagnostics for carrying out experiments to develop pellet injectors for plasma fueling applications. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL will team up with six of eight companies that are advancing designs and research and development for fusion power plants with the mission to achieve a pilot-scale demonstration of fusion within a decade.

A study led by ORNL researchers examines the causes behind ordering of cations, the positive ions that help make double perovskite oxides look promising as an energy source. Credit: Getty Images

A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.

This image depicts a visualization of an outflow of galactic wind at a single point in time using Cholla. Credit: Evan Schneider/University of Pittsburgh

A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

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.

Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn

University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.