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Media Contacts
![ORNL’s collaboration with Cincinati Children’s Hospital Medical Center will leverage the lab’s expertise in high-performance computing and safe, secure recordkeeping. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/CADES2019-P00182.jpg?h=c6980913&itok=P-o1DBeT)
Oak Ridge National Laboratory will partner with Cincinnati Children’s Hospital Medical Center to explore ways to deploy expertise in health data science that could more quickly identify patients’ mental health risk factors and aid in
![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.
![Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing. Using as much as 50 percent lignin by weight, a new composite material created at ORNL is well suited for use in 3D printing.](/sites/default/files/styles/list_page_thumbnail/public/2018-P09551.jpg?itok=q7Ri01Qb)
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.
![2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg 2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg](/sites/default/files/styles/list_page_thumbnail/public/2018-P07635%20BL-6%20user%20-%20Univ%20of%20Guelph-6004R_sm%5B2%5D.jpg?itok=DUdZNt_q)
A team of scientists, led by University of Guelph professor John Dutcher, are using neutrons at ORNL’s Spallation Neutron Source to unlock the secrets of natural nanoparticles that could be used to improve medicines.
![After a monolayer MXene is heated, functional groups are removed from both surfaces. Titanium and carbon atoms migrate from one area to both surfaces, creating a pore and forming new structures. Credit: ORNL, USDOE; image by Xiahan Sang and Andy Sproles. After a monolayer MXene is heated, functional groups are removed from both surfaces. Titanium and carbon atoms migrate from one area to both surfaces, creating a pore and forming new structures. Credit: ORNL, USDOE; image by Xiahan Sang and Andy Sproles.](/sites/default/files/styles/list_page_thumbnail/public/news/images/hTiC04_v2.jpg?itok=GeDQD6xS)
Scientists at the Department of Energy’s Oak Ridge National Laboratory induced a two-dimensional material to cannibalize itself for atomic “building blocks” from which stable structures formed. The findings, reported in Nature Communications, provide insights that ...
![Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy. Graphical representation of a deuteron, the bound state of a proton (red) and a neutron (blue). Credit: Andy Sproles/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/news/images/deuteron%5B4%5D.jpg?itok=hEV9C82i)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the