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Media Contacts
![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.
![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.
![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.
![Elizabeth Herndon uses spectroscopic techniques at ORNL to analyze the chemical composition of leaves and other environmental samples to better understand the soil carbon cycle. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/herndon1_0.jpg?h=e9eb73b3&itok=7hv7ziII)
ORNL biogeochemist Elizabeth Herndon is working with colleagues to investigate a piece of the puzzle that has received little attention thus far: the role of manganese in the carbon cycle.
![Dongarra in 2019 with Oak Ridge National Laboratory's Summit supercomputer](/sites/default/files/styles/list_page_thumbnail/public/2022-03/I%29%20Dongarra_IBM_Summit_Superomputer.jpeg?h=4bf1c8f5&itok=9sM8m0Iz)
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
![ORNL’s Joseph Lukens runs experiments in an optics lab. Credit: Jason Richards/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-03/2017-P08409.jpg?h=3c3b5e37&itok=vGSsxt7p)
Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum
![QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/QLAN%20submit_0.jpg?h=cd715a88&itok=JV1MjQHH)
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
![The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/E3SM_0.jpg?h=d5571230&itok=lKS66vCl)
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
![A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Quantum%20Illustration%20V3_0.png?h=2e111cc1&itok=Bth5wkD4)
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.