Filter News
Area of Research
- (-) Nuclear Systems Modeling, Simulation and Validation (1)
- (-) Supercomputing (83)
- Advanced Manufacturing (4)
- Biological Systems (2)
- Biology and Environment (136)
- Biology and Soft Matter (1)
- Clean Energy (106)
- Climate and Environmental Systems (5)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Energy Frontier Research Centers (1)
- Functional Materials for Energy (1)
- Fusion and Fission (31)
- Fusion Energy (15)
- Isotopes (6)
- Materials (112)
- Materials for Computing (14)
- Mathematics (1)
- National Security (16)
- Neutron Science (103)
- Nuclear Science and Technology (25)
- Quantum information Science (2)
News Topics
- (-) Advanced Reactors (2)
- (-) Bioenergy (9)
- (-) Biomedical (17)
- (-) Critical Materials (3)
- (-) Environment (21)
- (-) Exascale Computing (22)
- (-) Fusion (1)
- (-) Nanotechnology (11)
- (-) Neutron Science (13)
- 3-D Printing/Advanced Manufacturing (5)
- Artificial Intelligence (36)
- Big Data (19)
- Biology (11)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (17)
- Computer Science (95)
- Coronavirus (14)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (8)
- Frontier (28)
- Grid (5)
- High-Performance Computing (38)
- Isotopes (1)
- Machine Learning (14)
- Materials (15)
- Materials Science (16)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- National Security (8)
- Net Zero (1)
- Nuclear Energy (5)
- Partnerships (1)
- Physics (7)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Security (5)
- Simulation (14)
- Software (1)
- Space Exploration (3)
- Summit (42)
- Sustainable Energy (10)
- Transportation (6)
Media Contacts
![(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.
![Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.
![Reaching rare earths_v2.png Reaching rare earths_v2.png](/sites/default/files/styles/list_page_thumbnail/public/Reaching%20rare%20earths_v2.png?itok=Zz2arLKz)
Scientists from the Critical Materials Institute used the Titan supercomputer and Eos computing cluster at ORNL to analyze designer molecules that could increase the yield of rare earth elements found in bastnaesite, an important mineral
![Arjun Shankar Arjun Shankar](/sites/default/files/styles/list_page_thumbnail/public/shankar.png?itok=qqOR_eUI)
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...