An analysis by Oak Ridge National Laboratory shows that using less-profitable farmland to grow bioenergy crops such as switchgrass could fuel not only clean energy, but also gains in biodiversity.
Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
Researchers at ORNL designed a novel polymer to bind and strengthen silica sand for binder jet additive manufacturing, a 3D-printing method used by industries for prototyping and part production.
A new modeling capability developed at Oak Ridge National Laboratory incorporates important biogeochemical processes happening in river corridors for a clearer understanding of how water quality will be impacted by climate change, land use and
New data hosted through the Atmospheric Radiation Measurement Data Center at Oak Ridge National Laboratory will help improve models that predict climate change effects on the water supply in the Colorado River Basin.
Nearly a billion acres of land in the United States is dedicated to agriculture, producing more than a trillion dollars of food products to feed the country and the world. Those same agricultural processes, however, also produced an estimated 700 million metric tons of carbon dioxide equivalent in 2018, according to the U.S. Department of Agriculture.
New data hosted by Oak Ridge National Laboratory is helping scientists around the world understand the secret lives of plant roots as well as their impact on the global carbon cycle and climate change.
Oak Ridge National Laboratory worked with Colorado State University to simulate how a warming climate may affect U.S. urban hydrological systems.
Pengfei Cao, a polymer chemist at ORNL, has been chosen to receive a 2021 Young Investigator Award from the Polymeric Materials: Science and Engineering Division of the American Chemical Society, or ACS PMSE.
Scientists at Oak Ridge National Laboratory added new plant data to a computer model that simulates Arctic ecosystems, enabling it to better predict how vegetation in rapidly warming northern environments may respond to climate change.