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![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.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Carbon_capture_neutrons_0.jpg?h=4137a28c&itok=ZBLNFjNc)
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.
![An ORNL-developed graphite foam, which could be used in plasma-facing components in fusion reactors, performed well during testing at the Wendlestein 7-X stellarator in Germany.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/W7-XPlasmaExposure_0.jpg?h=d5d04e3b&itok=uKiauhdF)
Scientists have tested a novel heat-shielding graphite foam, originally created at Oak Ridge National Laboratory, at Germany’s Wendelstein 7-X stellarator with promising results for use in plasma-facing components of fusion reactors.
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 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.