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Media Contacts
Higher carbon dioxide levels caused 30 percent more wood growth in young forest stands across the temperate United States over a decade, according to an analysis led by Oak Ridge National Laboratory.
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
OAK RIDGE, Tenn., March 1, 2019—ReactWell, LLC, has licensed a novel waste-to-fuel technology from the Department of Energy’s Oak Ridge National Laboratory to improve energy conversion methods for cleaner, more efficient oil and gas, chemical and
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.
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 National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 8, 2019—The Department of Energy’s Oak Ridge National Laboratory has named Sean Hearne director of the Center for Nanophase Materials Sciences. The center is a DOE Office of Science User Facility that brings world-leading resources and capabilities to the nanoscience resear...
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.