![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
- (-) Isotopes (5)
- (-) Supercomputing (81)
- Advanced Manufacturing (4)
- Biological Systems (2)
- Biology and Environment (88)
- Biology and Soft Matter (1)
- Clean Energy (66)
- Climate and Environmental Systems (2)
- Computational Biology (1)
- Computational Engineering (2)
- Computer Science (6)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (11)
- Fusion Energy (7)
- Isotope Development and Production (1)
- Materials (33)
- Materials for Computing (2)
- Mathematics (1)
- National Security (25)
- Neutron Science (18)
- Nuclear Science and Technology (17)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (1)
- Sensors and Controls (1)
News Topics
- (-) Advanced Reactors (1)
- (-) Artificial Intelligence (36)
- (-) Bioenergy (9)
- (-) Climate Change (18)
- (-) Exascale Computing (22)
- (-) Security (5)
- (-) Space Exploration (6)
- 3-D Printing/Advanced Manufacturing (5)
- Big Data (19)
- Biology (11)
- Biomedical (22)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Computer Science (95)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (9)
- Environment (22)
- Frontier (28)
- Fusion (1)
- Grid (5)
- High-Performance Computing (38)
- Irradiation (1)
- Isotopes (25)
- Machine Learning (14)
- Materials (19)
- Materials Science (17)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (9)
- Net Zero (1)
- Neutron Science (13)
- Nuclear Energy (7)
- Partnerships (1)
- Physics (7)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Simulation (14)
- Software (1)
- Summit (42)
- Sustainable Energy (10)
- Transportation (6)
Media Contacts
![Small modular reactor computer simulation](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Nuclear_simulation_scale-up.jpg?h=5992a83f&itok=A0oscIPL)
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
![Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Slide1_0.png?h=c855054e&itok=aNbgxXsc)
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.
![(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/TourassiWH%5B1%5D.png?h=26b5064d&itok=HUC2iYmE)
OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the