![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
- (-) Supercomputing (26)
- Biological Systems (1)
- Biology and Environment (34)
- Biology and Soft Matter (1)
- Clean Energy (29)
- Computational Biology (1)
- Fusion and Fission (3)
- Isotopes (3)
- Materials (14)
- Materials for Computing (5)
- National Security (11)
- Neutron Science (10)
- Nuclear Science and Technology (4)
- Quantum information Science (4)
News Topics
- (-) Biomedical (7)
- (-) Cybersecurity (2)
- (-) Decarbonization (3)
- (-) Nanotechnology (5)
- (-) Quantum Science (10)
- 3-D Printing/Advanced Manufacturing (2)
- Artificial Intelligence (21)
- Big Data (13)
- Bioenergy (3)
- Biology (6)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (1)
- Climate Change (12)
- Computer Science (45)
- Coronavirus (7)
- Energy Storage (1)
- Environment (13)
- Exascale Computing (12)
- Frontier (13)
- Grid (1)
- High-Performance Computing (20)
- Machine Learning (7)
- Materials (4)
- Materials Science (8)
- Mathematics (1)
- Microscopy (2)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (2)
- Physics (3)
- Quantum Computing (10)
- Security (1)
- Simulation (10)
- Software (1)
- Space Exploration (1)
- Summit (21)
- Sustainable Energy (3)
- Transportation (3)
Media Contacts
![Edge computing is both dependent on and greatly influencing a host of promising technologies including (clockwise from top left): quantum computing; high-performance computing; neuromorphic computing; and carbon nanotubes.](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Jones%20image%202-12-20.png?h=2e876d46&itok=fT3y4uz9)
We have a data problem. Humanity is now generating more data than it can handle; more sensors, smartphones, and devices of all types are coming online every day and contributing to the ever-growing global dataset.
![The image visualizes how the team’s multitask convolutional neural network classifies primary cancer sites. Image credit: Hong-Jun Yoon/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2020-02/shot_0.png?h=49ab6177&itok=IXL5Ingy)
As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.
![Researchers in ORNL’s Quantum Information Science group summarized their significant contributions to quantum networking and quantum computing in a special issue of Optics & Photonics News. Image credit: Christopher Tison and Michael Fanto/Air Force Research Laboratory.](/sites/default/files/styles/list_page_thumbnail/public/2020-01/DSC02403_0.jpg?h=da4d8213&itok=o3kOwP6p)
A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.
![The students analyzed diatom images like this one to compare wild and genetically modified strains of these organisms. Credit: Alison Pawlicki/Oak Ridge National Laboratory, US Department of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2019-11/RI4362007.png?h=37702503&itok=9lQReLRe)
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
![Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Slide1_0.png?h=c855054e&itok=aNbgxXsc)
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.
![Joseph Lukens, Raphael Pooser, and Nick Peters (from left) of ORNL’s Quantum Information Science Group developed and tested a new interferometer made from highly nonlinear fiber in pursuit of improved sensitivity at the quantum scale. Credit: Carlos Jones](/sites/default/files/styles/list_page_thumbnail/public/news/images/2018-P09674%5B4%5D.jpg?h=1d98ccbd&itok=ztuyXqpm)
By analyzing a pattern formed by the intersection of two beams of light, researchers can capture elusive details regarding the behavior of mysterious phenomena such as gravitational waves. Creating and precisely measuring these interference patterns would not be possible without instruments called interferometers.