Filter News
Area of Research
- (-) Supercomputing (55)
- Advanced Manufacturing (4)
- Biology and Environment (62)
- Biology and Soft Matter (1)
- Clean Energy (83)
- Climate and Environmental Systems (1)
- Computer Science (3)
- Electricity and Smart Grid (1)
- Fuel Cycle Science and Technology (1)
- Fusion and Fission (29)
- Fusion Energy (5)
- Isotope Development and Production (1)
- Isotopes (4)
- Materials (43)
- Materials for Computing (6)
- National Security (25)
- Neutron Science (13)
- Nuclear Science and Technology (24)
- Quantum information Science (5)
News Type
News Topics
- (-) Climate Change (15)
- (-) Grid (4)
- (-) Machine Learning (12)
- (-) Nuclear Energy (3)
- (-) Quantum Science (20)
- (-) Sustainable Energy (8)
- 3-D Printing/Advanced Manufacturing (5)
- Artificial Intelligence (33)
- Big Data (15)
- Bioenergy (9)
- Biology (10)
- Biomedical (12)
- Biotechnology (2)
- Buildings (3)
- Chemical Sciences (4)
- Computer Science (76)
- Coronavirus (12)
- Cybersecurity (8)
- Decarbonization (4)
- Energy Storage (6)
- Environment (16)
- Exascale Computing (21)
- Frontier (26)
- High-Performance Computing (33)
- Isotopes (2)
- Materials (12)
- Materials Science (14)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (10)
- National Security (8)
- Net Zero (1)
- Neutron Science (13)
- Partnerships (1)
- Physics (8)
- Quantum Computing (15)
- Security (5)
- Simulation (12)
- Software (1)
- Space Exploration (2)
- Summit (36)
- Transportation (5)
Media Contacts
Researchers from institutions including ORNL have created a new method for statistically analyzing climate models that projects future conditions with more fidelity.
Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.
The world’s first exascale supercomputer will help scientists peer into the future of global climate change and open a window into weather patterns that could affect the world a generation from now.
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
The Exascale Small Modular Reactor effort, or ExaSMR, is a software stack developed over seven years under the Department of Energy’s Exascale Computing Project to produce the highest-resolution simulations of nuclear reactor systems to date. Now, ExaSMR has been nominated for a 2023 Gordon Bell Prize by the Association for Computing Machinery and is one of six finalists for the annual award, which honors outstanding achievements in high-performance computing from a variety of scientific domains.
A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
As extreme weather devastates communities worldwide, scientists are using modeling and simulation to understand how climate change impacts the frequency and intensity of these events. Although long-term climate projections and models are important, they are less helpful for short-term prediction of extreme weather that may rapidly displace thousands of people or require emergency aid.