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A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.
Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.
Scientists at the Department of Energy’s Oak Ridge National Laboratory have created a recipe for a renewable 3D printing feedstock that could spur a profitable new use for an intractable biorefinery byproduct: lignin.
A team of scientists, led by University of Guelph professor John Dutcher, are using neutrons at ORNL’s Spallation Neutron Source to unlock the secrets of natural nanoparticles that could be used to improve medicines.
Two leaders in US manufacturing innovation, Thomas Kurfess and Scott Smith, are joining the Department of Energy’s Oak Ridge National Laboratory to support its pioneering research in advanced manufacturing.
Scientists at the Department of Energy’s Oak Ridge National Laboratory induced a two-dimensional material to cannibalize itself for atomic “building blocks” from which stable structures formed. The findings, reported in Nature Communications, provide insights that ...
The construction industry may soon benefit from 3D printed molds to make concrete facades, promising lower cost and production time. Researchers at Oak Ridge National Laboratory are evaluating the performance of 3D printed molds used to precast concrete facades in a 42-story buildin...
Scientists at the Department of Energy’s Oak Ridge National Laboratory are the first to successfully simulate an atomic nucleus using a quantum computer. The results, published in Physical Review Letters, demonstrate the ability of quantum systems to compute nuclear ph...
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