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Media Contacts
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 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](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
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.
![At the salt–metal interface, thermodynamic forces drive chromium from the bulk of a nickel alloy, leaving a porous, weakened layer. Impurities in the salt drive further corrosion of the structural material. Credit: Stephen Raiman/Oak Ridge National Labora At the salt–metal interface, thermodynamic forces drive chromium from the bulk of a nickel alloy, leaving a porous, weakened layer. Impurities in the salt drive further corrosion of the structural material. Credit: Stephen Raiman/Oak Ridge National Labora](/sites/default/files/styles/list_page_thumbnail/public/story%20tip%20image%20BW%20only.jpg?itok=Vbc0iTLt)
Oak Ridge National Laboratory scientists analyzed more than 50 years of data showing puzzlingly inconsistent trends about corrosion of structural alloys in molten salts and found one factor mattered most—salt purity.
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
![exp_in_10_dry_tube.jpg exp_in_10_dry_tube.jpg](/sites/default/files/styles/list_page_thumbnail/public/exp_in_10_dry_tube.jpg?itok=cmBuu2CQ)
Scientists from Oak Ridge National Laboratory performed a corrosion test in a neutron radiation field to support the continued development of molten salt reactors.
![X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg](/sites/default/files/styles/list_page_thumbnail/public/X1800-REED-Maritime%20Risk%20Symposium%202018%20logo-AM%20V5-01.jpg?itok=_AN4HV63)
Thought leaders from across the maritime community came together at Oak Ridge National Laboratory to explore the emerging new energy landscape for the maritime transportation system during the Ninth Annual Maritime Risk Symposium.
![From left, Amit Naskar, Ngoc Nguyen and Christopher Bowland in ORNL’s Carbon and Composites Group bring a new capability—structural health monitoring—to strong, lightweight materials promising for transportation applications. From left, Amit Naskar, Ngoc Nguyen and Christopher Bowland in ORNL’s Carbon and Composites Group bring a new capability—structural health monitoring—to strong, lightweight materials promising for transportation applications.](/sites/default/files/styles/list_page_thumbnail/public/IMAGE1_%202018-P06604_0.jpg?itok=9-iSLuHf)
Carbon fiber composites—lightweight and strong—are great structural materials for automobiles, aircraft and other transportation vehicles. They consist of a polymer matrix, such as epoxy, into which reinforcing carbon fibers have been embedded. Because of differences in the mecha...
![Autonomous_vehicle_simulation_ORNL.jpg Autonomous_vehicle_simulation_ORNL.jpg](/sites/default/files/styles/list_page_thumbnail/public/Autonomous_vehicle_simulation_ORNL.jpg?itok=2pnITULi)
Self-driving cars promise to keep traffic moving smoothly and reduce fuel usage, but proving those advantages has been a challenge with so few connected and automated vehicles, or CAVs, currently on the road.
![Methanogen_mercury_study3.jpg Methanogen_mercury_study3.jpg](/sites/default/files/styles/list_page_thumbnail/public/Methanogen_mercury_study3.jpg?itok=a79hsOOv)
Biologists from Oak Ridge National Laboratory and the Smithsonian Environmental Research Center have confirmed that microorganisms called methanogens can transform mercury into the neurotoxin methylmercury with varying efficiency across species.