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ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.

Small modular reactor computer simulation

In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.

Using artificial intelligence, Oak Ridge National Laboratory analyzed data from published medical studies to reveal the potential of direct and indirect impacts of bullying.

Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease. 

Desalination diagram

A team of scientists led by Oak Ridge National Laboratory used carbon nanotubes to improve a desalination process that attracts and removes ionic compounds such as salt from water using charged electrodes.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

Trees in an Oak Ridge National Laboratory plot

Higher carbon dioxide levels caused 30 percent more wood growth in young forest stands across the temperate United States over a decade, according to an analysis led by Oak Ridge National Laboratory.

ORNL will use state-of-the-art R&D tools at the Battery Manufacturing Facility to develop new methods for separating and reclaiming valuable materials from spent EV batteries.

The use of lithium-ion batteries has surged in recent years, starting with electronics and expanding into many applications, including the growing electric and hybrid vehicle industry. But the technologies to optimize recycling of these batteries have not kept pace.

Using neutrons from the TOPAZ beamline, which is optimal for locating hydrogen atoms in materials, ORNL researchers observed a single-crystal neutron diffraction structure of the insoluble carbonate salt formed by absorption of carbon dioxide from the air.

Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source to investigate the effectiveness of a novel crystallization method to capture carbon dioxide directly from the air.

CO2 release by mild heating of the BIG-bicarbonate solid. The released CO2 gas is trapped in the orange balloon, while the released water vapors are trapped by condensation in the ice-cooled U-shaped tube. Credit: Neil J. Williams and Erick Holguin.

Scientists at the Department of Energy’s Oak Ridge National Laboratory (ORNL) have developed a process that could remove CO2 from coal-burning power plant emissions in a way that is similar to how soda lime works in scuba diving rebreathers. Their research, published January 31 in...

Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w

A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.