Filter News
Area of Research
- (-) Biology and Environment (10)
- (-) Materials (9)
- Advanced Manufacturing (1)
- Building Technologies (3)
- Clean Energy (42)
- Computational Engineering (1)
- Computer Science (5)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (1)
- National Security (13)
- Neutron Science (3)
- Supercomputing (17)
News Topics
- (-) Buildings (5)
- (-) Machine Learning (11)
- 3-D Printing/Advanced Manufacturing (27)
- Advanced Reactors (4)
- Artificial Intelligence (15)
- Big Data (10)
- Bioenergy (51)
- Biology (73)
- Biomedical (20)
- Biotechnology (13)
- Chemical Sciences (35)
- Clean Water (14)
- Climate Change (43)
- Composites (11)
- Computer Science (34)
- Coronavirus (14)
- Critical Materials (13)
- Cybersecurity (5)
- Decarbonization (25)
- Energy Storage (37)
- Environment (100)
- Exascale Computing (6)
- Frontier (6)
- Fusion (8)
- Grid (8)
- High-Performance Computing (24)
- Hydropower (8)
- Irradiation (1)
- Isotopes (13)
- ITER (1)
- Materials (78)
- Materials Science (82)
- Mathematics (3)
- Mercury (7)
- Microscopy (34)
- Molten Salt (3)
- Nanotechnology (42)
- National Security (5)
- Net Zero (3)
- Neutron Science (36)
- Nuclear Energy (16)
- Partnerships (12)
- Physics (30)
- Polymers (18)
- Quantum Computing (3)
- Quantum Science (11)
- Renewable Energy (2)
- Security (3)
- Simulation (15)
- Space Exploration (2)
- Summit (11)
- Sustainable Energy (42)
- Transformational Challenge Reactor (3)
- Transportation (15)
Media Contacts
![A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK](/sites/default/files/styles/list_page_thumbnail/public/2022-01/Observed%20data%20AI%20story%20tip.jpg?h=8e5dac0a&itok=wrAOsfIs)
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
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.
![Distinguished Inventors](/sites/default/files/styles/list_page_thumbnail/public/2020-12/inventors.jpg?h=4631f1c1&itok=xhAGY0kv)
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
![The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/CrossVisOverview_2.png?h=fd2b4cf7&itok=Mz8wRoMo)
From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.
![Coronavirus graphic](/sites/default/files/styles/list_page_thumbnail/public/2020-04/covid19_jh_0.png?h=d1cb525d&itok=PyngFUZw)
In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.