![Sphere that has the top right fourth removed (exposed) Colors from left are orange, dark blue with orange dots, light blue with horizontal lines, then black. Inside the exposure is green and black with boxes.](/sites/default/files/styles/featured_square_large/public/2024-06/slicer.jpg?h=56311bf6&itok=bCZz09pJ)
Filter News
Area of Research
News Topics
- (-) Big Data (2)
- (-) Bioenergy (1)
- (-) Cybersecurity (2)
- (-) Exascale Computing (1)
- (-) Isotopes (3)
- (-) Microscopy (2)
- (-) Polymers (2)
- (-) Security (2)
- 3-D Printing/Advanced Manufacturing (1)
- Biology (2)
- Biomedical (1)
- Climate Change (1)
- Composites (1)
- Computer Science (7)
- Energy Storage (2)
- Environment (2)
- Fusion (3)
- Grid (2)
- Materials Science (5)
- Molten Salt (1)
- Nanotechnology (1)
- Nuclear Energy (4)
- Physics (2)
- Space Exploration (2)
- Transportation (3)
Media Contacts
![Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy. Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2012-P03136%281%29.jpg?itok=i0w1NZWs)
A team of researchers from Oak Ridge National Laboratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scient...
![ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones](/sites/default/files/styles/list_page_thumbnail/public/Sang_2016-P07680_0.jpg?itok=w0e5eR_U)
Researchers have long sought electrically conductive materials for economical energy-storage devices. Two-dimensional (2D) ceramics called MXenes are contenders. Unlike most 2D ceramics, MXenes have inherently good conductivity because they are molecular sheets made from the carbides ...
![The Transforming Additive Manufacturing through Exascale Simulation project (ExaAM) is building a new multi-physics modeling and simulation platform for 3D printing of metals The Transforming Additive Manufacturing through Exascale Simulation project (ExaAM) is building a new multi-physics modeling and simulation platform for 3D printing of metals](/sites/default/files/styles/list_page_thumbnail/public/ECP%20release%20graphic%202_0.jpg?itok=JzmmCpGX)
Oak Ridge National Laboratory experts are playing leading roles in the recently established Department of Energy’s (DOE’s) Exascale Computing Project (ECP), a multi-lab initiative responsible for developing the strategy, aligning the resources, and conducting the R&D necessary to achieve the nation’s imperative of delivering exascale computing by 2021.