Filter News
Area of Research
- Advanced Manufacturing (6)
- Biology and Environment (18)
- Clean Energy (54)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (4)
- Fusion Energy (4)
- Isotopes (1)
- Materials (27)
- Materials for Computing (6)
- National Security (23)
- Neutron Science (14)
- Nuclear Science and Technology (11)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (3)
- Supercomputing (52)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (41)
- (-) Advanced Reactors (18)
- (-) Composites (5)
- (-) Computer Science (65)
- (-) Cybersecurity (13)
- (-) Grid (20)
- (-) Quantum Science (23)
- (-) Security (7)
- Artificial Intelligence (23)
- Big Data (22)
- Bioenergy (33)
- Biology (34)
- Biomedical (27)
- Biotechnology (5)
- Buildings (17)
- Chemical Sciences (20)
- Clean Water (7)
- Climate Change (36)
- Coronavirus (32)
- Critical Materials (6)
- Decarbonization (22)
- Element Discovery (1)
- Energy Storage (47)
- Environment (69)
- Exascale Computing (12)
- Fossil Energy (1)
- Frontier (11)
- Fusion (21)
- High-Performance Computing (19)
- Hydropower (8)
- Irradiation (1)
- Isotopes (12)
- ITER (2)
- Machine Learning (18)
- Materials (39)
- Materials Science (55)
- Mathematics (2)
- Mercury (3)
- Microscopy (22)
- Molten Salt (2)
- Nanotechnology (26)
- National Security (19)
- Net Zero (2)
- Neutron Science (44)
- Nuclear Energy (41)
- Partnerships (8)
- Physics (25)
- Polymers (12)
- Quantum Computing (7)
- Simulation (6)
- Space Exploration (6)
- Summit (24)
- Sustainable Energy (49)
- Transformational Challenge Reactor (7)
- Transportation (27)
Media Contacts
Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
Researchers at ORNL have developed an online tool that offers industrial plants an easier way to track and download information about their energy footprint and carbon emissions.
Researchers at ORNL recently demonstrated a new technology to better control how power flows to and from commercial buildings equipped with solar, wind or other renewable energy generation.
A crowd of investors and supporters turned out for last week’s Innovation Crossroads Showcase at the Knoxville Chamber as part of Innov865 Week. Sponsored by ORNL and the Tennessee Advanced Energy Business Council, the event celebrated deep-tech entrepreneurs and the Oak Ridge Corridor as a growing energy innovation hub for the nation.
In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.
Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.
When Hurricane Maria battered Puerto Rico in 2017, winds snapped trees and destroyed homes, while heavy rains transformed streets into rivers. But after the storm passed, the human toll continued to grow as residents struggled without electricity for months. Five years later, power outages remain long and frequent.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.