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Media Contacts
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
Material surfaces and interfaces may appear flat and void of texture to the naked eye, but a view from the nanoscale reveals an intricate tapestry of atomic patterns that control the reactions between the material and its environment. Electron microscopy allows researchers to probe...
Officials responsible for anticipating the demand for electric vehicle charging stations could get help through a sophisticated new method developed at Oak Ridge National Laboratory. The method considers electric vehicle volume and the random timing of vehicles arriving at cha...
Geospatial scientists at Oak Ridge National Laboratory have developed a novel method to quickly gather building structure datasets that support emergency response teams assessing properties damaged by Hurricanes Harvey and Irma. By coupling deep learning with high-performance comp...
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...
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...
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...
Researchers used neutrons to probe a running engine at ORNL’s Spallation Neutron Source
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 ...