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For the past six years, some 140 scientists from five institutions have traveled to the Arctic Circle and beyond to gather field data as part of the Department of Energy-sponsored NGEE Arctic project. This article gives insight into how scientists gather the measurements that inform t...

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A shield assembly that protects an instrument measuring ion and electron fluxes for a NASA mission to touch the Sun was tested in extreme experimental environments at Oak Ridge National Laboratory—and passed with flying colors. Components aboard Parker Solar Probe, which will endure th...

Julie Smith

It may take a village to raise a child, according to the old proverb, but it takes an entire team of highly trained scientists and engineers to install and operate a state-of-the-art, exceptionally complex ion microprobe. Just ask Julie Smith, a nuclear security scientist at the Depa...

ORNL Director Thomas Zacharia (center, seated) visited Robertsville Middle School to present a check in support of the school’s CubeSat efforts.

Last November a team of students and educators from Robertsville Middle School in Oak Ridge and scientists from Oak Ridge National Laboratory submitted a proposal to NASA for their Cube Satellite Launch Initiative in hopes of sending a student-designed nanosatellite named RamSat into...

Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.
Oak Ridge National Laboratory provided significant contributions and coordination in the development of the Nuclear Energy Agency’s (NEA’s) recently released Spent Fuel Isotopic Composition (SFCOMPO) 2.0—the world’s largest open database for spent
ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

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

As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy

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...

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

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

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.

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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.