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Media Contacts
![Collaborators at ORNL’s Center for Nanophase Materials Sciences used advanced microscopy to enhance materials for next-generation devices. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/STORY-TIP_0.jpg?h=4687655f&itok=sFt8Cgoj)
Researchers at Oak Ridge National Laboratory and Korea’s Sungkyunkwan University are using advanced microscopy to nanoengineer promising materials for computing and electronics in a beyond-Moore era.
![Adrian Sabau](/sites/default/files/styles/list_page_thumbnail/public/2022-06/Adrian_portrait_2022-P03462a.jpg?h=8f9cfe54&itok=u-N-Am33)
Adrian Sabau of the Department of Energy’s Oak Ridge National Laboratory has been named an ASM International Fellow.
![Frontier has arrived, and ORNL is preparing for science on Day One. Credit: Carlos Jones/ORNL, Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Frontier%20endcap.jpg?h=c6980913&itok=5i5DUzQz)
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
![MDF Exterior](/sites/default/files/styles/list_page_thumbnail/public/2022-06/2021-p07609.jpg?h=be3e4b3a&itok=YfKK7Wy2)
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
![A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/PFC%20Surface%20v3%20300dpi_1.jpg?h=9c3ba2fc&itok=s8arZbEt)
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
![The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines](/sites/default/files/styles/list_page_thumbnail/public/2022-05/UF4%20hydrate.png?h=d318f057&itok=spT-Dg48)
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
![Miaofang Chi](/sites/default/files/styles/list_page_thumbnail/public/2022-05/2021-P09692.jpg?h=49ab6177&itok=WB5z93IO)
Miaofang Chi, a scientist at ORNL, has been elected a Fellow of the Microscopy Society of America.
![ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
![Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.](/sites/default/files/styles/list_page_thumbnail/public/2022-04/CCSD_NeuralNetworkBanner.png?h=b16f811b&itok=fxqDEvs_)
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
![Earth Day](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Earth%20image.png?h=8f74817f&itok=5rQ_su9Z)
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.