Filter News
Area of Research
News Topics
- (-) Machine Learning (3)
- (-) Nanotechnology (4)
- (-) Net Zero (1)
- 3-D Printing/Advanced Manufacturing (19)
- Advanced Reactors (1)
- Artificial Intelligence (2)
- Big Data (3)
- Bioenergy (2)
- Biology (4)
- Biomedical (1)
- Biotechnology (1)
- Buildings (4)
- Chemical Sciences (3)
- Clean Water (1)
- Climate Change (7)
- Composites (4)
- Computer Science (6)
- Coronavirus (3)
- Critical Materials (2)
- Decarbonization (1)
- Energy Storage (16)
- Environment (15)
- Grid (7)
- High-Performance Computing (2)
- Isotopes (1)
- Materials (14)
- Materials Science (8)
- Mathematics (1)
- Microscopy (2)
- Molten Salt (1)
- Neutron Science (1)
- Physics (1)
- Polymers (4)
- Space Exploration (1)
- Statistics (1)
- Sustainable Energy (26)
- Transportation (13)
Media Contacts
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.
A research team led by Oak Ridge National Laboratory bioengineered a microbe to efficiently turn waste into itaconic acid, an industrial chemical used in plastics and paints.
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial
Seven ORNL scientists have been named among the 2020 Highly Cited Researchers list, according to Clarivate, a data analytics firm that specializes in scientific and academic research.
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.
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.