Filter News
Area of Research
- (-) Supercomputing (52)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (90)
- Biology and Soft Matter (1)
- Clean Energy (68)
- Climate and Environmental Systems (1)
- Computational Biology (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (2)
- Fusion and Fission (6)
- Isotopes (4)
- Materials (42)
- Materials for Computing (7)
- National Security (17)
- Neutron Science (17)
- Nuclear Science and Technology (2)
- Quantum information Science (2)
News Type
News Topics
- (-) Bioenergy (4)
- (-) Biomedical (8)
- (-) Cybersecurity (4)
- (-) Energy Storage (4)
- (-) Environment (14)
- (-) Frontier (16)
- (-) Nanotechnology (7)
- (-) Quantum Computing (11)
- 3-D Printing/Advanced Manufacturing (4)
- Artificial Intelligence (24)
- Big Data (14)
- Biology (7)
- Biotechnology (1)
- Buildings (3)
- Chemical Sciences (2)
- Climate Change (13)
- Computer Science (52)
- Coronavirus (8)
- Decarbonization (4)
- Exascale Computing (14)
- Grid (2)
- High-Performance Computing (26)
- Isotopes (1)
- Machine Learning (9)
- Materials (9)
- Materials Science (11)
- Mathematics (1)
- Microscopy (3)
- Molten Salt (1)
- National Security (4)
- Net Zero (1)
- Neutron Science (7)
- Nuclear Energy (2)
- Physics (4)
- Quantum Science (11)
- Security (2)
- Simulation (12)
- Software (1)
- Space Exploration (2)
- Summit (22)
- Sustainable Energy (6)
- Transportation (4)
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.
The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...