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A research team led by ORNL’s Xiaohan Yang used a gene from agave to engineer higher yield, improved stress tolerance and greater carbon sequestration in tobacco plants. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Scientists at ORNL have discovered a single gene that simultaneously boosts plant growth and tolerance for stresses such as drought and salt, all while tackling the root cause of climate change by enabling plants to pull more carbon dioxide from the atmosphere.

Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.

Kashif Nawaz, researcher and group leader for multifunctional equipment integration in buildings technologies, is developing a platform for the direct air capture of carbon dioxide that can be retrofitted to existing rooftop heating, ventilation and air conditioning units.  Credit: ORNL/U.S. Dept. of Energy

When Kashif Nawaz looks at a satellite map of the U.S., he sees millions of buildings that could hold a potential solution for the capture of carbon dioxide, a plentiful gas that can be harmful when excessive amounts are released into the atmosphere, raising the Earth’s temperature.

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

New virtual tours of ORNL facilities include the Building Technologies Research and Integration Center, shown in dollhouse view. Credit: ORNL, U.S. Dept. of Energy

ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.

An interactive visualization shows potential progression of BECCS to address carbon dioxide reduction goals. Credit: ORNL, U.S. Dept. of Energy

The combination of bioenergy with carbon capture and storage could cost-effectively sequester hundreds of millions of metric tons per year of carbon dioxide in the United States, making it a competitive solution for carbon management, according to a new analysis by ORNL scientists.

Xunxiang Hu, a Eugene P. Wigner Fellow in ORNL’s Materials Science and Technology Division, designed this machine to produce large, crack-free pieces of yttrium hydride to be used as a moderator in the core of ORNL’s Transformational Challenge Reactor and other microreactors. Credit: Xunxiang Hu/ORNL, U.S. Dept. of Energy

About 60 years ago, scientists discovered that a certain rare earth metal-hydrogen mixture, yttrium, could be the ideal moderator to go inside small, gas-cooled nuclear reactors.

3D-printed 316L steel has been irradiated along with traditionally wrought steel samples. Researchers are comparing how they perform at various temperatures and varying doses of radiation. Credit: Jaimee Janiga/ORNL

It’s a new type of nuclear reactor core. And the materials that will make it up are novel — products of Oak Ridge National Laboratory’s advanced materials and manufacturing technologies.

Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.

Cars and coronavirus

Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.