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Media Contacts
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.