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Media Contacts
![The illustrations show how the correlation between lattice distortion and proton binding energy in a material affects proton conduction in different environments. Mitigating this interaction could help researchers improve the ionic conductivity of solid materials.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/Figure_Rosenthal_5-1-19_0.png?h=73c01546&itok=-tjVhDfm)
Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.
![ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-03/teamphotoforhighlight_0.jpg?h=a00326b7&itok=O4yDtVj6)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
![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.
![The interior of the Massachusetts Institute of Technology’s (MIT’s) Alcator C-Mod tokamak. A team led by Princeton Plasma Physics Laboratory’s C.S. Chang recently used the Titan supercomputer The interior of the Massachusetts Institute of Technology’s (MIT’s) Alcator C-Mod tokamak. A team led by Princeton Plasma Physics Laboratory’s C.S. Chang recently used the Titan supercomputer](/sites/default/files/styles/list_page_thumbnail/public/Chang1%20copy_0.jpg?itok=4mDUjXsj)
The same fusion reactions that power the sun also occur inside a tokamak, a device that uses magnetic fields to confine and control plasmas of 100-plus million degrees. Under extreme temperatures and pressure, hydrogen atoms can fuse together, creating new helium atoms and simulta...
![Arjun Shankar Arjun Shankar](/sites/default/files/styles/list_page_thumbnail/public/shankar.png?itok=qqOR_eUI)
The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...
![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...
![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.