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Media Contacts
![ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/news/images/01_Cybersecurity_guarding_autonomous_vehicles.jpg?itok=qaErb8Ia)
A new Oak Ridge National Laboratory-developed method promises to protect connected and autonomous vehicles from possible network intrusion. Researchers built a prototype plug-in device designed to alert drivers of vehicle cyberattacks. The prototype is coded to learn regular timing...
![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...
![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 Image](/sites/default/files/styles/list_page_thumbnail/public/2017-S00094_2.jpg?itok=ZGWBnMOv)
Researchers used neutrons to probe a running engine at ORNL’s Spallation Neutron Source
![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.
![Vanadium atoms (blue) have unusually large thermal vibrations that stabilize the metallic state of a vanadium dioxide crystal. Red depicts oxygen atoms.](/sites/default/files/styles/list_page_thumbnail/public/2020-06/82289_web.jpg?h=05d1a54d&itok=_5hHRzzR)
For more than 50 years, scientists have debated what turns particular oxide insulators, in which electrons barely move, into metals, in which electrons flow freely.