Updated software improves slicing for large-format 3D printing
Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (27)
- Biology and Soft Matter (1)
- Clean Energy (31)
- Computer Science (1)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Isotopes (1)
- Materials (19)
- Materials for Computing (4)
- National Security (12)
- Neutron Science (4)
- Supercomputing (16)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (12)
- (-) Advanced Reactors (4)
- (-) Artificial Intelligence (14)
- (-) Clean Water (5)
- (-) Climate Change (26)
- (-) Fusion (7)
- (-) Grid (13)
- (-) Materials Science (16)
- (-) Security (4)
- (-) Transportation (10)
- Big Data (9)
- Bioenergy (19)
- Biology (28)
- Biomedical (6)
- Biotechnology (3)
- Buildings (16)
- Chemical Sciences (15)
- Composites (3)
- Computer Science (20)
- Coronavirus (9)
- Critical Materials (4)
- Cybersecurity (7)
- Decarbonization (21)
- Element Discovery (1)
- Energy Storage (25)
- Environment (36)
- Exascale Computing (8)
- Fossil Energy (1)
- Frontier (10)
- High-Performance Computing (16)
- Hydropower (8)
- Irradiation (1)
- Isotopes (4)
- ITER (2)
- Machine Learning (10)
- Materials (37)
- Mercury (1)
- Microscopy (13)
- Nanotechnology (9)
- National Security (17)
- Net Zero (2)
- Neutron Science (12)
- Nuclear Energy (10)
- Partnerships (8)
- Physics (10)
- Polymers (5)
- Quantum Computing (7)
- Quantum Science (9)
- Simulation (6)
- Space Exploration (4)
- Summit (7)
- Sustainable Energy (25)
- Transformational Challenge Reactor (2)
Media Contacts
A novel method to 3D print components for nuclear reactors, developed by the Department of Energy’s Oak Ridge National Laboratory, has been licensed by Ultra Safe Nuclear Corporation.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant