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Two hybrid poplar plants, middle and right, engineered with the PtrXB38 hub gene exhibited a drastic increase in root and callus formation compared with a wild-type control plant, left. Credit: Tao Yao/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists identified a gene “hotspot” in the poplar tree that triggers dramatically increased root growth. The discovery supports development of better bioenergy crops and other plants that can thrive in difficult conditions while storing more carbon belowground.

ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House, held Sept. 11–13. Credit: ORNL, U.S. Dept. of Energy

ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House.

Neutron scattering experiments at the Spallation Neutron Source revealed how the dynamics between copper and oxygen make a special type of enzyme excel at breaking down biomass. Insights could lead to lowering the cost of biofuel production. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Nonfood, plant-based biofuels have potential as a green alternative to fossil fuels, but the enzymes required for production are too inefficient and costly to produce. However, new research is shining a light on enzymes from fungi that could make biofuels economically viable.

An open-source code developed by an ORNL-led team could provide new insights into the everyday operation of the nation’s power grid. Credit: Pixabay

Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine

ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.

Coronavirus graphic

In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.

Scientists created a novel polymer that is as effective as natural proteins in transporting protons through a membrane. Credit: ORNL/Jill Hemman

Biological membranes, such as the “walls” of most types of living cells, primarily consist of a double layer of lipids, or “lipid bilayer,” that forms the structure, and a variety of embedded and attached proteins with highly specialized functions, including proteins that rapidly and selectively transport ions and molecules in and out of the cell.

Smart Neighborhood homes

To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.

Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy

Illustration of the optimized zeolite catalyst, or NbAlS-1, which enables a highly efficient chemical reaction to create butene, a renewable source of energy, without expending high amounts of energy for the conversion. Credit: Jill Hemman, Oak Ridge National Laboratory/U.S. Dept. of Energy

Project bridges compute staff, resources at ORNL and VA health data to speed suicide risk screening for US veterans. Image Credit: Carlos Jones, ORNL

In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.