Skip to main content

News

An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable

Members of the international team simulated changes to the start times of monsoon seasons across the globe, with warm colors representing onset delays. Credit: Moetasim Ashfaq and Adam Malin/Oak Ridge National Laboratory, U.S. Dept. of Energy

Scientists from the Department of Energy’s Oak Ridge National Laboratory and a dozen other international research institutions have produced the most elaborate set of projections to date that illustrates possible futures for major monsoon regions.

Before the demonstration, the team prepared QKD equipment (pictured) at ORNL. Image credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

For the second year in a row, a team from the Department of Energy’s Oak Ridge and Los Alamos national laboratories led a demonstration hosted by EPB, a community-based utility and telecommunications company serving Chattanooga, Tennessee.

Simulations forecast nationwide increase in human exposure to extreme climate events

OAK RIDGE, Tenn., May 5, 2020 — By 2050, the United States will likely be exposed to a larger number of extreme climate events, including more frequent heat waves, longer droughts and more intense floods, which can lead to greater risks for human health, ecosystem stability and regional economies.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days. 

This simulation of a fusion plasma calculation result shows the interaction of two counter-streaming beams of super-heated gas. Credit: David L. Green/Oak Ridge National Laboratory, U.S. Dept. of Energy

The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.

Illustration of a nitrogen dioxide molecule (depicted in blue and purple) captured in a nano-size pore of an MFM-520 metal-organic framework material as observed using neutron vibrational spectroscopy at Oak Ridge National Laboratory. Image credit: ORNL/Jill Hemman

An international team of scientists, led by the University of Manchester, has developed a metal-organic framework, or MOF, material

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.

The EPB Control Center monitors the company’s assets such as substations and buildings.

OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).

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.