Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
The Department of Energy’s Office of Science has selected three Oak Ridge National Laboratory scientists for Early Career Research Program awards.
Bruce Wilson, a group leader in the Environmental Sciences Division at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to the grade of senior member of the Association for Computing Machinery
Giri Prakash, data informatics scientist and director of the Department of Energy’s Atmospheric Radiation Measurement Data Center at Oak Ridge National Laboratory, has accepted an invitation from the National Academies of Sciences, Engineering, and Medicine to serve a four-year term on the U.S. National Committee for CODATA.
Matthew R. Ryder, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been named the 2020 Foresight Fellow in Molecular-Scale Engineering.
A multi-institutional research team found that changing environmental conditions are affecting forests around the globe, leading to increasing tree death and uncertainty about the ability of forests to recover.