Filter News
Area of Research
- (-) Climate and Environmental Systems (1)
- (-) Fusion Energy (4)
- (-) National Security (11)
- (-) Supercomputing (24)
- Advanced Manufacturing (1)
- Biological Systems (1)
- Biology and Environment (9)
- Clean Energy (12)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (7)
- Fusion and Fission (5)
- Isotopes (1)
- Materials (8)
- Materials for Computing (2)
- Neutron Science (4)
- Nuclear Science and Technology (2)
- Quantum information Science (2)
News Type
News Topics
- (-) Biomedical (4)
- (-) Computer Science (25)
- (-) Exascale Computing (3)
- (-) Fusion (4)
- (-) Grid (3)
- (-) Machine Learning (4)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (4)
- Artificial Intelligence (8)
- Big Data (7)
- Bioenergy (3)
- Biology (5)
- Biotechnology (1)
- Buildings (1)
- Climate Change (6)
- Coronavirus (3)
- Critical Materials (1)
- Cybersecurity (2)
- Decarbonization (1)
- Energy Storage (1)
- Environment (7)
- Frontier (3)
- High-Performance Computing (6)
- Materials (4)
- Materials Science (5)
- Microscopy (1)
- Nanotechnology (3)
- National Security (7)
- Neutron Science (1)
- Nuclear Energy (6)
- Quantum Computing (5)
- Quantum Science (4)
- Security (2)
- Simulation (4)
- Space Exploration (2)
- Summit (11)
- Sustainable Energy (1)
- Transportation (1)
Media Contacts
Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.
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.
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.
Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.