![Debjani Singh](/sites/default/files/styles/featured_square_large/public/2024-08/2024-P12408.jpg?h=8f9cfe54&itok=bP5F6U4Y)
Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (16)
- Clean Energy (12)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (6)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (1)
- Fusion Energy (1)
- Materials (13)
- Materials for Computing (2)
- National Security (14)
- Neutron Science (12)
- Supercomputing (89)
News Topics
- (-) Artificial Intelligence (97)
- (-) Quantum Computing (37)
- (-) Summit (59)
- 3-D Printing/Advanced Manufacturing (125)
- Advanced Reactors (34)
- Big Data (60)
- Bioenergy (92)
- Biology (100)
- Biomedical (60)
- Biotechnology (23)
- Buildings (61)
- Chemical Sciences (70)
- Clean Water (31)
- Climate Change (104)
- Composites (29)
- Computer Science (195)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Decarbonization (82)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (112)
- Environment (198)
- Exascale Computing (40)
- Fossil Energy (6)
- Frontier (44)
- Fusion (57)
- Grid (66)
- High-Performance Computing (90)
- Hydropower (11)
- Irradiation (3)
- Isotopes (55)
- ITER (7)
- Machine Learning (49)
- Materials (145)
- Materials Science (145)
- Mathematics (9)
- Mercury (12)
- Microelectronics (4)
- Microscopy (51)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (71)
- Net Zero (14)
- Neutron Science (134)
- Nuclear Energy (110)
- Partnerships (49)
- Physics (63)
- Polymers (33)
- Quantum Science (71)
- Renewable Energy (2)
- Security (25)
- Simulation (49)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Sustainable Energy (130)
- Transformational Challenge Reactor (7)
- Transportation (97)
Media Contacts
![Caption: Participants gather for a group photo after discussing securing AI systems for critical national security data and applications. Photo by Liz Neunsinger/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/Picture1.jpg?h=1758acef&itok=hu9V4GaE)
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
![Chapman recognized for work as peer reviewer](/sites/default/files/styles/list_page_thumbnail/public/2024-05/2021-P07893.jpg?h=8f9cfe54&itok=Kv_xAmFf)
Joseph Chapman, a research scientist in quantum communications at ORNL, was given the Physical Review Applied Reviewer Excellence 2024 award for his work as a peer reviewer for the journal Physical Review Applied.
![From left, J.D. Rice, Trevor Michelson and Chris Seck look at a monitor in Seck’s lab. The three are wearing safety glasses to protect against the laser beams used by the scanning vibrometer, which is helping Seck quantify vibration of an appliance in his lab. Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/02-09-24%20Vibrometer%20Meas.jpg?h=d06c0bb9&itok=BaIHxm7O)
ORNL scientists are working on a project to engineer and develop a cryogenic ion trap apparatus to simulate quantum spin liquids, a key research area in materials science and neutron scattering studies.
![Jiafu Mao, left, and Yaoping Wang discuss their analysis of urban and rural vegetation resilience across the United States in the EVEREST visualization lab at ORNL. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/2024-P07278R.jpg?h=c6980913&itok=lVwfnfEq)
Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.
![The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory](/sites/default/files/styles/list_page_thumbnail/public/2024-05/CLS_AI-for-Energy-Workshop-Report_1600x900_shutterstock_209822020_R2.jpg?h=748c0655&itok=uYkfSuJp)
Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.
![The transportation and industrial sectors together account for more than 50% of the country’s carbon footprint. Defossilization could help reduce new emissions from these and other difficult-to-electrify segments of the U.S. economy.](/sites/default/files/styles/list_page_thumbnail/public/2024-05/GettyImages-887377090%20%281%29.jpg?h=73e7f248&itok=QYmqPfWv)
Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions.
Simulations performed on the Summit supercomputer at ORNL are cutting through that time and expense by helping researchers digitally customize the ideal alloy.
![Researchers relied on support from ORNL’s Quantum Computing User Program to simulate a key quantum state at one of the largest scales reported. The findings could mark a step toward improving quantum simulations. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2024-04/QCUP_Potterstudy.png?h=ae114f5c&itok=vAelg9M2)
Researchers simulated a key quantum state at one of the largest scales reported, with support from the Quantum Computing User Program, or QCUP, at ORNL.
![SOS26 attendees standing in front of the Kennedy Space Center on Merrit Island, Florida the night of their dinner reception provided by the conference sponsors. The keynote speaker was Rupak Biswas from NASA. Credit: Judy Potok/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/IMG_4436%5B16%5D%20%281%29.jpeg?h=51920af5&itok=cf3iVu5B)
Held in Cocoa Beach, Florida from March 11 to 14, researchers across the computing and data spectra participated in sessions developed by staff members from the Department of Energy’s Oak Ridge National Laboratory, or ORNL, Sandia National Laboratories and the Swiss National Supercomputing Centre.
![ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/powered%20by%20match.jpg?h=384e2afb&itok=wJegcDZm)
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.