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Media Contacts
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
Quantum experts from across government and academia descended on Oak Ridge National Laboratory on Wednesday, January 16 for the lab’s first-ever Quantum Networking Symposium. The symposium’s purpose, said organizer and ORNL senior scientist Nick Peters, was to gather quantum an...
Researchers used neutron scattering at Oak Ridge National Laboratory’s Spallation Neutron Source to investigate bizarre magnetic behavior, believed to be a possible quantum spin liquid rarely found in a three-dimensional material. QSLs are exotic states of matter where magnetism continues to fluctuate at low temperatures instead of “freezing” into aligned north and south poles as with traditional magnets.
By analyzing a pattern formed by the intersection of two beams of light, researchers can capture elusive details regarding the behavior of mysterious phenomena such as gravitational waves. Creating and precisely measuring these interference patterns would not be possible without instruments called interferometers.
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...
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...