Filter News
Area of Research
- (-) Biology and Environment (2)
- Advanced Manufacturing (4)
- Clean Energy (15)
- Computational Engineering (1)
- Computer Science (4)
- Fusion and Fission (1)
- Fusion Energy (7)
- Materials (12)
- Materials for Computing (2)
- National Security (1)
- Neutron Science (2)
- Nuclear Science and Technology (11)
- Nuclear Systems Modeling, Simulation and Validation (2)
- Quantum information Science (3)
- Supercomputing (7)
Date
News Topics
- (-) Composites (1)
- (-) Machine Learning (1)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (1)
- Big Data (1)
- Bioenergy (10)
- Biology (14)
- Biomedical (2)
- Biotechnology (2)
- Clean Water (3)
- Climate Change (9)
- Computer Science (3)
- Coronavirus (1)
- Decarbonization (2)
- Environment (17)
- Grid (2)
- High-Performance Computing (3)
- Hydropower (3)
- Materials (1)
- Mercury (1)
- Simulation (1)
- Sustainable Energy (9)
- Transportation (1)
Media Contacts
![Researchers found that moderate levels of ash — sometimes found as spheres in biomass — do not significantly affect the mechanical properties of biocomposites made up of corn stover, switchgrass and PLA thermoplastic. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-12/sampleRecolor_v4_0.png?h=4d1c0665&itok=rRlgS-4C)
The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.
![A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK](/sites/default/files/styles/list_page_thumbnail/public/2022-01/Observed%20data%20AI%20story%20tip.jpg?h=8e5dac0a&itok=wrAOsfIs)
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.