![This photo is of a male scientist sitting at a desk working with materials, wearing protective glasses.](/sites/default/files/styles/featured_square_large/public/2024-07/2023-P08173.jpg?h=c6980913&itok=LnJLvflD)
Filter News
Area of Research
- (-) Clean Energy (35)
- (-) Materials (22)
- (-) Supercomputing (14)
- Advanced Manufacturing (1)
- Biology and Environment (16)
- Computational Engineering (1)
- Computer Science (6)
- Electricity and Smart Grid (2)
- Fusion and Fission (17)
- Fusion Energy (11)
- National Security (19)
- Neutron Science (6)
- Nuclear Science and Technology (7)
- Quantum information Science (1)
- Sensors and Controls (1)
News Type
News Topics
- (-) Fusion (5)
- (-) Grid (28)
- (-) Machine Learning (10)
- (-) Mercury (2)
- (-) Physics (15)
- (-) Security (4)
- 3-D Printing/Advanced Manufacturing (51)
- Advanced Reactors (5)
- Artificial Intelligence (24)
- Big Data (18)
- Bioenergy (15)
- Biology (12)
- Biomedical (16)
- Biotechnology (3)
- Buildings (25)
- Chemical Sciences (12)
- Clean Water (9)
- Climate Change (26)
- Composites (12)
- Computer Science (72)
- Coronavirus (17)
- Critical Materials (10)
- Cybersecurity (7)
- Decarbonization (21)
- Energy Storage (45)
- Environment (51)
- Exascale Computing (13)
- Fossil Energy (1)
- Frontier (14)
- High-Performance Computing (23)
- Hydropower (2)
- Isotopes (8)
- Materials (48)
- Materials Science (46)
- Mathematics (3)
- Microelectronics (1)
- Microscopy (15)
- Molten Salt (1)
- Nanotechnology (18)
- National Security (4)
- Net Zero (3)
- Neutron Science (20)
- Nuclear Energy (18)
- Partnerships (5)
- Polymers (12)
- Quantum Computing (15)
- Quantum Science (15)
- Simulation (12)
- Software (1)
- Space Exploration (7)
- Statistics (1)
- Summit (28)
- Sustainable Energy (44)
- Transformational Challenge Reactor (2)
- Transportation (49)
Media Contacts
![ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/SAW%20sensors%202021-P01084_0.jpg?h=8f9cfe54&itok=H3Fe6A_G)
A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.
![Verónica Melesse Vergara speaks with third and fourth graders at East Side Intermediate School in Brownsville. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/EWeek_vergara_0.jpg?h=c44fcfa1&itok=-FdYpHed)
Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.
![Pella Marion](/sites/default/files/styles/list_page_thumbnail/public/2021-03/WMMPA%20Pella%20Marion%20790_Small.jpg?h=f14a4ec1&itok=ItU-Ca6U)
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
![The researchers embedded a programmable model into a D-Wave quantum computer chip. Credit: D-Wave](/sites/default/files/styles/list_page_thumbnail/public/2021-02/P5-o5czF_0.jpg?h=b69e0e0e&itok=wCU6WIp_)
Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.
![ORNL’s Marcel Demarteau inspects experiments along Neutrino Alley at the Spallation Neutron Source, which makes neutrinos as a byproduct. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-12/2020-P15166_0.jpg?h=c6980913&itok=GkpktZzV)
Marcel Demarteau is director of the Physics Division at the Department of Energy’s Oak Ridge National Laboratory. For topics from nuclear structure to astrophysics, he shapes ORNL’s physics research agenda.
![Suman Debnath is using simulation algorithms to accelerate understanding of the modern power grid and enhance its reliability and resilience. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Suman%20Debnath%20Square.jpg?h=439d043c&itok=1umME5uH)
Planning for a digitized, sustainable smart power grid is a challenge to which Suman Debnath is using not only his own applied mathematics expertise, but also the wider communal knowledge made possible by his revival of a local chapter of the IEEE professional society.
![Cars and coronavirus](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Transportation-Gauging_pandemic_impact_ORNL_0.jpg?h=4a7d1ed4&itok=Xqx4kknO)
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
![The hybrid inverter developed by ORNL is an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and interact efficiently with the utility power grid. Credit: Carlos Jones, ORNL/U.S. Dept of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2020-P09169.jpg?h=42d56c10&itok=Yb1_gWYE)
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.
![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.
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.