Filter News
Area of Research
- Advanced Manufacturing (1)
- Biology and Environment (13)
- Clean Energy (11)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (7)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (1)
- Materials (13)
- Materials for Computing (1)
- National Security (18)
- Neutron Science (8)
- Supercomputing (56)
News Topics
- (-) Artificial Intelligence (101)
- (-) Machine Learning (50)
- (-) Quantum Computing (37)
- 3-D Printing/Advanced Manufacturing (128)
- Advanced Reactors (34)
- Big Data (60)
- Bioenergy (92)
- Biology (101)
- Biomedical (61)
- Biotechnology (24)
- Buildings (67)
- Chemical Sciences (73)
- Clean Water (31)
- Climate Change (105)
- Composites (30)
- Computer Science (198)
- Coronavirus (46)
- Critical Materials (29)
- Cybersecurity (35)
- Decarbonization (85)
- Education (5)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (112)
- Environment (200)
- Exascale Computing (42)
- Fossil Energy (6)
- Frontier (45)
- Fusion (58)
- Grid (66)
- High-Performance Computing (93)
- Hydropower (11)
- Irradiation (3)
- Isotopes (57)
- ITER (7)
- Materials (147)
- Materials Science (146)
- Mathematics (9)
- Mercury (12)
- Microelectronics (4)
- Microscopy (51)
- Molten Salt (9)
- Nanotechnology (60)
- National Security (72)
- Net Zero (14)
- Neutron Science (137)
- Nuclear Energy (111)
- Partnerships (51)
- Physics (64)
- Polymers (33)
- Quantum Science (72)
- Renewable Energy (2)
- Security (25)
- Simulation (51)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (59)
- Sustainable Energy (130)
- Transformational Challenge Reactor (7)
- Transportation (99)
Media Contacts
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
EPB, ORNL announce plans for research collaborative focused on energy resilience, quantum technology
EPB and ORNL marked 10 years of collaboration with the announcement of the new Collaborative for Energy Resilience and Quantum Science. The new joint research effort will focus on utilizing Chattanooga’s highly advanced and integrated energy and communications infrastructure to develop technologies and best practices for enhancing the resilience and security of the national power grid while accelerating the commercialization of quantum technologies.
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric
From July 15 to 26, 2024, the Department of Energy’s Oak Ridge National Laboratory will host the second U.S. Quantum Information Science, or QIS, Summer School.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
ORNL’s successes in QIS and its forward-looking strategy were recently recognized in the form of three funding awards that will help ensure the laboratory remains a leader in advancing quantum computers and networks.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
A team of researchers from the University of Southern California, the Renaissance Computing Institute at the University of North Carolina, and Oak Ridge, Lawrence Berkeley and Argonne National Laboratories have received a grant from the U.S. Department of Energy to develop the fundamentals of a computational platform that is fault tolerant, robust to various environmental conditions and adaptive to workloads and resource availability.
Despite its futuristic essence, artificial intelligence has a history that can be traced through several decades, and the ORNL has played a major role. From helping to drive fundamental and applied AI research from the field’s early days focused on expert systems, computer programs that rely on AI, to more recent developments in deep learning, a form of AI that enables machines to make evidence-based decisions, the lab’s AI research spans the spectrum.