![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
- Biology and Environment (25)
- Biology and Soft Matter (1)
- Clean Energy (22)
- Climate and Environmental Systems (1)
- Fusion and Fission (4)
- Fusion Energy (3)
- Materials (35)
- Materials for Computing (4)
- National Security (7)
- Neutron Science (11)
- Nuclear Science and Technology (8)
- Nuclear Systems Modeling, Simulation and Validation (1)
- Quantum information Science (3)
- Supercomputing (25)
News Topics
- (-) Advanced Reactors (18)
- (-) Climate Change (36)
- (-) Nanotechnology (26)
- (-) Physics (23)
- (-) Quantum Science (23)
- 3-D Printing/Advanced Manufacturing (40)
- Artificial Intelligence (22)
- Big Data (20)
- Bioenergy (31)
- Biology (33)
- Biomedical (27)
- Biotechnology (5)
- Buildings (17)
- Chemical Sciences (20)
- Clean Water (7)
- Composites (4)
- Computer Science (59)
- Coronavirus (32)
- Critical Materials (6)
- Cybersecurity (11)
- Decarbonization (22)
- Element Discovery (1)
- Energy Storage (46)
- Environment (65)
- Exascale Computing (11)
- Fossil Energy (1)
- Frontier (11)
- Fusion (20)
- Grid (20)
- High-Performance Computing (19)
- Hydropower (8)
- Irradiation (1)
- Isotopes (12)
- ITER (2)
- Machine Learning (18)
- Materials (39)
- Materials Science (53)
- Mathematics (2)
- Mercury (2)
- Microscopy (21)
- Molten Salt (2)
- National Security (19)
- Net Zero (2)
- Neutron Science (42)
- Nuclear Energy (41)
- Partnerships (8)
- Polymers (12)
- Quantum Computing (7)
- Security (7)
- Simulation (6)
- Space Exploration (6)
- Summit (24)
- Sustainable Energy (49)
- Transformational Challenge Reactor (7)
- Transportation (25)
Media Contacts
![Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2022-05/CCSD%20Neuro-climate.png?h=845c699a&itok=AJbSKZF8)
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
![ORNL scientists created a geodemographic cluster for the Atlanta metro area that identifies risk factors related to climate impacts. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/climateMapCorrection_0.jpg?h=5c1b3784&itok=ijIvJETa)
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.
![Technology developed at ORNL to monitor plant productivity and health at wide scales has been licensed to Logan, Utah-based instrumentation firm Campbell Scientific Inc.](/sites/default/files/styles/list_page_thumbnail/public/2022-05/93F4DF26.jpg?h=68b07240&itok=9kcq1b8W)
Technology developed at ORNL to monitor plant productivity and health at wide scales has been licensed to Logan, Utah-based instrumentation firm Campbell Scientific Inc.
![Jim Szybist, Propulsion Science section head at ORNL, is applying his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Picture1_6.jpg?h=b67478d5&itok=3BWDWSU8)
What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.
![A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/PFC%20Surface%20v3%20300dpi_1.jpg?h=9c3ba2fc&itok=s8arZbEt)
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
![Physicist Charles Havener uses the NASA end station at ORNL’s Multicharged Ion Research Facility to simulate the origin of X-ray emissions from space. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/2021-P08920_0.jpg?h=c6980913&itok=zfXx31gD)
Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.
![With seismic and acoustic data recorded by remote sensors near ORNL’s High Flux Isotope Reactor, researchers could predict whether the reactor was on or off with 98% accuracy. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Seismo%20acoustic%20draft%20v3_0.jpg?h=2e111cc1&itok=0oLpYDc8)
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
![Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.](/sites/default/files/styles/list_page_thumbnail/public/2022-04/CCSD_NeuralNetworkBanner.png?h=b16f811b&itok=fxqDEvs_)
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
![Earth Day](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Earth%20image.png?h=8f74817f&itok=5rQ_su9Z)
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
![Elizabeth Herndon uses spectroscopic techniques at ORNL to analyze the chemical composition of leaves and other environmental samples to better understand the soil carbon cycle. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/herndon1_0.jpg?h=e9eb73b3&itok=7hv7ziII)
ORNL biogeochemist Elizabeth Herndon is working with colleagues to investigate a piece of the puzzle that has received little attention thus far: the role of manganese in the carbon cycle.