Filter News
Area of Research
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (16)
- Clean Energy (10)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (5)
- Materials (5)
- Materials for Computing (1)
- National Security (6)
- Neutron Science (2)
- Supercomputing (13)
News Type
News Topics
- (-) Bioenergy (20)
- (-) Biomedical (5)
- (-) Composites (1)
- (-) Cybersecurity (6)
- (-) Exascale Computing (5)
- (-) Frontier (5)
- (-) Fusion (5)
- 3-D Printing/Advanced Manufacturing (11)
- Advanced Reactors (2)
- Artificial Intelligence (11)
- Big Data (7)
- Biology (19)
- Biotechnology (3)
- Buildings (5)
- Chemical Sciences (7)
- Clean Water (4)
- Climate Change (21)
- Computer Science (24)
- Coronavirus (3)
- Critical Materials (1)
- Decarbonization (15)
- Energy Storage (14)
- Environment (36)
- Grid (4)
- High-Performance Computing (10)
- Hydropower (3)
- Isotopes (1)
- ITER (1)
- Machine Learning (6)
- Materials (15)
- Materials Science (11)
- Mercury (2)
- Microscopy (9)
- Nanotechnology (6)
- National Security (9)
- Net Zero (2)
- Neutron Science (8)
- Nuclear Energy (11)
- Partnerships (2)
- Physics (5)
- Polymers (1)
- Quantum Computing (5)
- Quantum Science (5)
- Security (3)
- Simulation (4)
- Space Exploration (2)
- Summit (9)
- Sustainable Energy (16)
- Transformational Challenge Reactor (1)
- Transportation (8)
Media Contacts
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.