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Media Contacts
![COHERENT collaborators were the first to observe coherent elastic neutrino–nucleus scattering. Their results, published in the journal Science, confirm a prediction of the Standard Model and establish constraints on alternative theoretical models. Image c COHERENT collaborators were the first to observe coherent elastic neutrino–nucleus scattering. Their results, published in the journal Science, confirm a prediction of the Standard Model and establish constraints on alternative theoretical models. Image c](/sites/default/files/styles/list_page_thumbnail/public/SLIDESHOW%202_collaboration.jpg?itok=icKSVyYi)
After more than a year of operation at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL), the COHERENT experiment, using the world’s smallest neutrino detector, has found a big fingerprint of the elusive, electrically neutral particles that interact only weakly with matter.
![ORNL-Lenvio_tech_license_signing_ceremony2 ORNL-Lenvio_tech_license_signing_ceremony2](/sites/default/files/styles/list_page_thumbnail/public/ORNL-Lenvio_tech_license_signing_ceremony2.jpg?itok=xcfN-PbJ)
Virginia-based Lenvio Inc. has exclusively licensed a cyber security technology from the Department of Energy’s Oak Ridge National Laboratory that can quickly detect malicious behavior in software not previously identified as a threat.
![ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones](/sites/default/files/styles/list_page_thumbnail/public/Sang_2016-P07680_0.jpg?itok=w0e5eR_U)
Researchers have long sought electrically conductive materials for economical energy-storage devices. Two-dimensional (2D) ceramics called MXenes are contenders. Unlike most 2D ceramics, MXenes have inherently good conductivity because they are molecular sheets made from the carbides ...
![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.
![ORNL’s Manjunath Gorentla Venkata helped develop a new approach to analyze thousands of genetic samples by connecting powerful computing resources. ORNL’s Manjunath Gorentla Venkata helped develop a new approach to analyze thousands of genetic samples by connecting powerful computing resources.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2016-P05087.jpg?itok=mSLI1AgK)
ORNL helps develop hybrid computational strategy for efficient sequencing of massive genome datasets
Computing experts at the Department of Energy’s Oak Ridge National Laboratory collaborated with a team of university researchers and software companies to develop a novel hybrid computational strategy to efficiently discover genetic variants
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
The Department of Energy’s Oak Ridge National Laboratory has received funding from DOE’s Exascale Computing Project (ECP) to develop applications for future exascale systems that will be 50 to 100 times more powerful than today’s fastest supercomputers.